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a/blog/0.1-release/banner.svg b/blog/0.1-release/banner.svg new file mode 100644 index 0000000000..64da6257d1 --- /dev/null +++ b/blog/0.1-release/banner.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/0.1-release/image.svg b/blog/0.1-release/image.svg new file mode 100644 index 0000000000..a9b4c74fa0 --- /dev/null +++ b/blog/0.1-release/image.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/0.1-release/index.mdx b/blog/0.1-release/index.mdx new file mode 100644 index 0000000000..79d1857b99 --- /dev/null +++ b/blog/0.1-release/index.mdx @@ -0,0 +1,37 @@ +--- +title: Introducing OpenLineage 0.1.0 +date: 2021-09-03 +author: Julien Le Dem +image: ./image.svg +banner: ./banner.svg +description: We are pleased to announce the initial release of OpenLineage. This release includes the core specification, data model, clients, and integrations with common data tools. +--- +We are pleased to announce the initial release of OpenLineage. This release includes the core specification, data model, clients, and integrations with common data tools. + +![](./banner.svg#full-width) + + + +We are pleased to announce the initial release of OpenLineage. This is the culmination of a broad community effort, and establishes a common framework for data lineage collection and analysis. + +We want to thank [all the contributors](https://github.com/OpenLineage/OpenLineage/graphs/contributors) as well all the projects and companies involved in the design (in alphabetical order): [Airflow](https://airflow.apache.org), [Astronomer](https://www.astronomer.io), [Datakin](https://datakin.com), [Data Mesh](https://datameshlearning.com), [dbt](https://www.getdbt.com), [Egeria](https://egeria.odpi.org), [GetInData](https://getindata.com), [Great Expectations](https://greatexpectations.io), [Iceberg](https://iceberg.apache.org) (and others that I am probably forgetting). + +This release includes: +* The initial 1-0-0 release of the [OpenLineage specification](https://github.com/OpenLineage/OpenLineage/blob/main/spec/OpenLineage.md) +* A core lineage model of Jobs, Runs and Datasets + * Core facets + * Data Quality Metrics and statistics + * Dataset schema + * Source code location + * SQL +* Clients that send OpenLineage events to an HTTP backend + * Java + * Python +* [Integrations](https://github.com/OpenLineage/OpenLineage/tree/main/integration) that collect lineage metadata as OpenLineage events + * Apache Airflow with support for BigQuery, Great Expectations, Postgres, Redshift, Snowflake + * Apache Spark + * dbt + +This is only the beginning. We invite everyone interested to [consult and contribute to the roadmap](https://github.com/OpenLineage/OpenLineage/projects). The roadmap currently contains, among other things: adding support for [Kafka](https://github.com/OpenLineage/OpenLineage/issues/152), [BI dashboards](https://github.com/OpenLineage/OpenLineage/issues/207), and [column level lineage](https://github.com/OpenLineage/OpenLineage/issues/148)...but you can influence it by participating! + +Follow the [repo](https://github.com/OpenLineage/OpenLineage) to stay updated. And, as always, you can [join the conversation](http://bit.ly/OpenLineageSlack) on Slack. diff --git a/blog/backfilling-airflow-dags-using-marquez/backfill.png b/blog/backfilling-airflow-dags-using-marquez/backfill.png new file mode 100644 index 0000000000000000000000000000000000000000..e6efff733d3bef21d828bb5c21dbd12896c6735a GIT binary patch literal 29362 zcmeFZ2T)Yq(k=`L1`tt6A`(Oa$r&Xl1<4sCgXAzEVaQPgRDvQ&GDv1flH&j(ARs|< z1|<$T51G3L-vCwb|JOO+z30|fw?3)DVb9)cuhqNz>F(7}?>7o^61dp6vC+`ba3!BU zRzgF&AdQBGL2&sZIMTLQHVOViw^x!7Ma%2Bg8+Xh7(bIVk(EWG2cIvaVW8hcyMQ_c z{GbJxqhX$YMnj_k|AV2D(Et863FFUiFGwd{`13Oc0qVrS5lBB6M8jO=nZq+#8D2vh z2(y8a&2wXBXUGfG326Mzyx=3m*uj9(8DeE^&+9Beb$SLb_>4NtLPdFcii4#9)iYTI zN--NdV@fV&PG(jrL2OD&N`5;d6JDjq;(uHY{t}=vb8vXU%fjO1l1kPZxcd>RbaAvZ$zxR8PKgW4&Y;S01{=&iB#+ni}uEBE~sDl6%73xNR z{rf#n2Xm9Z?__QN$FjfzSy11wuraf;{53YXlpl4JSKiLt7~B~(z91X_>6zz_{c#_D z7SzqpOy>7WPmhA73S#rK{3SL)Y?&{#8fa+3Xp)abRGiV5#xBJXJQ;3Yzx4R(>l^sD 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b/blog/backfilling-airflow-dags-using-marquez/image.svg new file mode 100644 index 0000000000..ff8de4f793 --- /dev/null +++ b/blog/backfilling-airflow-dags-using-marquez/image.svg @@ -0,0 +1,51 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/backfilling-airflow-dags-using-marquez/index.mdx b/blog/backfilling-airflow-dags-using-marquez/index.mdx new file mode 100644 index 0000000000..5488fee7d2 --- /dev/null +++ b/blog/backfilling-airflow-dags-using-marquez/index.mdx @@ -0,0 +1,218 @@ +--- +title: Backfilling Airflow DAGs using Marquez +date: 2021-06-30 +author: Willy Lulciuc +image: ./image.svg +banner: ./banner.svg +description: In this blog post, we'll discuss how lineage metadata can be used to automatically backfill DAGs with complex upstream and downstream dependencies. +--- +In this blog post, we'll discuss how lineage metadata can be used to automatically backfill DAGs with complex upstream and downstream dependencies. + +![](./banner.svg#full-width) + + + +You've just deployed an Airflow [DAG](https://airflow.apache.org/docs/apache-airflow/stable/concepts/dags.html#dags) that calculates the total sum of weekly food orders. You were able to identify what input tables to query, the frequency in which your DAG would run, and made sure analysts knew the resulting output table to use in their weekly food order trends report. The DAG only needs to run once a week, and with the DAG managed and scheduled via [Airflow](https://airflow.apache.org), you feel confident that the aggregated food order data will be available every Sunday morning for the weekly report. + +As a developer, you're monitoring your DAG for errors and after only a few DAG runs, you're alerted that your DAG suddenly started to fail! Before you begin troubleshooting the root cause of the DAG failure, you notify the analytics team that the food order data will be incorrect for the week. After viewing the DAG error logs and a few email exchanges, you eventually discover that an upstream DAG had failed to write food order data for certain daily table partitions. Now, backfilling the missing data can be a manual and tedious task. As you sip your morning coffee, you think to yourself, _there must be a better way_. Yes, there is and collecting DAG lineage metadata would be a great start. + +In this blog post, we'll briefly introduce you to how backfills are handled in Airflow, then discuss how lineage metadata can be used to backfill DAGs with more complex upstream and downstream dependencies. + +## 1. Brief Intro to Backfilling Airflow DAGs + +Airflow supports [backfilling](https://airflow.apache.org/docs/apache-airflow/stable/dag-run.html#backfill) DAG runs for a historical time window given a _start_ and _end_ date. Let's say our `example.etl_orders_7_days` DAG started failing on `2021-06-06`, and we wanted to reprocess the daily table partitions for that week (assuming all partitions have been backfilled upstream). In order to run the backfill for `example.etl_orders_7_days`, using the Airflow [CLI](https://airflow.apache.org/docs/apache-airflow/stable/cli-and-env-variables-ref.html), you open up a terminal and execute the following `backfill` [command](https://airflow.apache.org/docs/apache-airflow/stable/cli-and-env-variables-ref.html#backfill): + +``` +# Backfill weekly food orders +$ airflow dags backfill \ + --start-date 2021-06-06 \ + --end-date 2021-06-06 \ + example.etl_orders_7_days +``` + +Now, the backfill was fairly straightforward but they're not always trivial. That is, we still have the following open questions: + +* How quickly can data quality issues be identified and explored? +* What alerting rules should be in place to notify downstream DAGs of possible upstream processing issues or failures? +* What effects (if any) would upstream DAGs have on downstream DAGs if dataset consumption was delayed? + +Next, we'll demonstrate how lineage metadata managed with [Marquez](https://marquezproject.ai) can help answer some of these questions (and more!) by maintaining inter-DAG dependencies and cataloging historical runs of DAGs. + +## 2. Exploring Lineage Metadata using Marquez + +> **Note:** To seed the Marquez HTTP API server with the sample lineage metadata used in this blog post, see the [Write Sample Lineage Metadata to Marquez](https://marquezproject.github.io/marquez/quickstart.html#write-sample-lineage-metadata-to-marquez) section in Marquez's [quickstart](https://marquezproject.github.io/marquez/quickstart.html) guide. + +#### 2.1 COLLECT DAG LINEAGE METADATA + +![](./lineage-graph.png) + +> **Figure 1:** DAG lineage metadata. + +[Marquez](https://marquezproject.ai) is an open source metadata service for the collection, aggregation, and visualization of a data ecosystem’s metadata. Marquez has integration support for Airflow with minimal configuration. Using the [`marquez-airflow`](https://github.com/MarquezProject/marquez/tree/main/integrations/airflow) library, DAG lineage metadata will be collected automatically during DAG execution using the [OpenLineage](https://openlineage.io) standard, then stored in Marquez’s centralized data model. To learn more about how lineage metadata is stored and versioned in Marquez, see the [Data Model](https://marquezproject.github.io/marquez/quickstart.html#marquez-data-model) section in Marquez's [quickstart](https://marquezproject.github.io/marquez/quickstart.html) guide. + +The Airflow integration gives us two important benefits: + +* **DAG Metadata:** Each DAG has a code version, inputs and outputs, run args, and run state transitions. Keeping a global historical log of DAG runs linked to code will quickly highlight upstream dependencies errors and minimize downstream impact. +* **Lineage Metadata:** Each DAG may have one or more upstream dependency. Keeping track of inter-DAG dependencies will allow for teams within an organization to safely depend on one another’s datasets, while also understanding which DAGs will be impacted downstream of a DAG failure. + +In this blog, we won't go into how to enable lineage metadata collection for Airflow DAGs. But, we encourage you to take a look at Marquez's Airflow [example](https://github.com/MarquezProject/marquez/tree/main/examples/airflow) to learn how to troubleshoot DAG failures using Marquez. + +#### 2.2 GET LINEAGE METADATA VIA REST API + +In Marquez, each dataset and job has its own globally unique node ID that can be used to query the lineage graph. The [LineageAPI](https://marquezproject.github.io/marquez/openapi.html#tag/Lineage/paths/~1lineage/get) returns a set of **nodes** consisting of **edges**. An edge is **directed** and has a defined **origin** and **destination**. A lineage graph may contain the following node types: `dataset::`, `job::`. + +So, let's start by querying the lineage graph for our `example.etl_orders_7_days` DAG using the node ID `job:food_delivery:example.etl_orders_7_days`. You'll notice in the returned lineage graph that the DAG _input_ datasets are `public.categories`, `public.orders`, and `public.menus` with `public.orders_7_days` as the _output_ dataset: + +##### REQUEST + +``` +$ curl -X GET "http://localhost:5000/api/v1-beta/lineage?nodeId=job:food_delivery:example.etl_orders_7_days" +``` + +##### RESPONSE + +`200 OK` + +``` +{ + "graph": [{ + "id": "job:food_delivery:example.etl_orders_7_days", + "type": "JOB", + "data": { + "type": "BATCH", + "id": { + "namespace": "food_delivery", + "name": "example.etl_orders_7_days" + }, + "name": "example.etl_orders_7_days", + "createdAt": "2021-06-06T14:50:13.931946Z", + "updatedAt": "2021-06-06T14:57:54.037399Z", + "namespace": "food_delivery", + "inputs": [ + {"namespace": "food_delivery", "name": "public.categories"}, + {"namespace": "food_delivery", "name": "public.menu_items"}, + {"namespace": "food_delivery", "name": "public.orders"}, + {"namespace": "food_delivery", "name": "public.menus"} + ], + "outputs": [ + {"namespace": "food_delivery", "name": "public.orders_7_days"} + ], + "location": "https://github.com/example/jobs/blob/2294bc15eb49071f38425dc927e48655530a2f2e/etl_orders_7_days.py", + "context": { + "sql": "INSERT INTO orders_7_days (order_id, placed_on, discount_id, menu_id, restaurant_id, menu_item_id, category_id)\n SELECT o.id AS order_id, o.placed_on, o.discount_id, m.id AS menu_id, m.restaurant_id, mi.id AS menu_item_id, c.id AS category_id\n FROM orders AS o\n INNER JOIN menu_items AS mi\n ON menu_items.id = o.menu_item_id\n INNER JOIN categories AS c\n ON c.id = mi.category_id\n INNER JOIN menu AS m\n ON m.id = c.menu_id\n WHERE o.placed_on >= NOW() - interval '7 days';" + }, + "description": "Loads newly placed orders weekly.", + "latestRun": { + "id": "5c7f0dc4-d3c1-4f16-9ac3-dc86c5da37cc", + "createdAt": "2021-06-06T14:50:36.853459Z", + "updatedAt": "2021-06-06T14:57:54.037399Z", + "nominalStartTime": "2021-06-06T14:54:00Z", + "nominalEndTime": "2021-06-06T14:57:00Z", + "state": "FAILED", + "startedAt": "2021-06-06T14:54:14.037399Z", + "endedAt": "2021-06-06T14:57:54.037399Z", + "durationMs": 220000, + "args": {}, + "location": "https://github.com/example/jobs/blob/2294bc15eb49071f38425dc927e48655530a2f2e/etl_orders_7_days.py", + "context": { + "sql": "INSERT INTO orders_7_days (order_id, placed_on, discount_id, menu_id, restaurant_id, menu_item_id, category_id)\n SELECT o.id AS order_id, o.placed_on, o.discount_id, m.id AS menu_id, m.restaurant_id, mi.id AS menu_item_id, c.id AS category_id\n FROM orders AS o\n INNER JOIN menu_items AS mi\n ON menu_items.id = o.menu_item_id\n INNER JOIN categories AS c\n ON c.id = mi.category_id\n INNER JOIN menu AS m\n ON m.id = c.menu_id\n WHERE o.placed_on >= NOW() - interval '7 days';" + }, + "facets": {} + } + }, + "inEdges": [ + {"origin": "dataset:food_delivery:public.categories", "destination": "job:food_delivery:example.etl_orders_7_days"}, "destination": "job:food_delivery:example.etl_orders_7_days"}, + {"origin": "dataset:food_delivery:public.orders", "destination": "job:food_delivery:example.etl_orders_7_days"}, + {"origin": "dataset:food_delivery:public.menus", "destination": "job:food_delivery:example.etl_orders_7_days"} + ], + "outEdges": [ + {"origin": "job:food_delivery:example.etl_orders_7_days", "destination": "dataset:food_delivery:public.orders_7_days"} + ] + } + }, ...] +} +``` + +## 3. Using Lineage Metadata to Backfill Airflow DAGs + +#### 3.1 BACKFILLING + +![](./backfill.png) + +> **Figure 2:** Backfilled daily table partitions. + +To run a backfill for `example.etl_orders_7_days` using the DAG lineage metadata stored in Marquez, we'll need to query the lineage graph for the upstream DAG where the error originated. Now, let's assume the `example.etl_orders` DAG upstream of `example.etl_orders_7_days` failed to write some of the daily table partitions needed for the weekly food order trends report (see **Figure 2**). To fix the weekly trends report, we'll first need to backfill the missing daily table partitions `public.orders_2021_06_04`, `public.orders_2021_06_05`, and `public.orders_2021_06_06`: + +``` +# Backfill daily food orders +$ airflow dags backfill \ + --start-date 2021-06-04 \ + --end-date 2021-06-06 \ + example.etl_orders +``` + +![](./inter-dag-deps.png) + +> **Figure 3:** Airflow inter-DAG dependencies. + +Then, using the script `backfill.sh` defined below, we can easily backfill all DAGs downstream of `example.etl_orders`: + +##### `backfill.sh` + +> **Note:** Make sure you have [`jq`](https://stedolan.github.io/jq/download) installed before running `backfill.sh`. + +```bash +#!/bin/bash +# +# Backfill DAGs automatically using lineage metadata stored in Marquez. +# +# Usage: $ ./backfill.sh + +set -e + +# Backfills DAGs downstream of the given node ID, recursively. +backfill_downstream_of() { + node_id="${1}" + # Get out edges for node ID + out_edges=($(echo $lineage_graph \ + | jq -r --arg NODE_ID "${node_id}" '.graph[] | select(.id==$NODE_ID) | .outEdges[].destination')) + for out_edge in "${out_edges[@]}"; do + # Run backfill if out edge is a job node (i.e. => ) + if [[ "${out_edge}" = job:* ]]; then + dag_id="${out_edge##*:}" + echo "backfilling ${dag_id}..." + airflow backfill --start_date "${start_date}" --end_date "${start_date}" "${dag_id}" + fi + # Follow out edges downstream, recursively + backfill_downstream_of "${out_edge}" + done +} + +start_date="${1}" +end_date="${2}" +dag_id="${3}" + +# (1) Build job node ID (format: 'job::') +node_id="job:food_delivery:${dag_id}" + +# (2) Get lineage graph +lineage_graph=$(curl -s -X GET "http://localhost:5000/api/v1-beta/lineage?nodeId=${node_id}") + +# (3) Run backfill +backfill_downstream_of "${node_id}" +``` + +When you run the script `backfill.sh`, it will output all backfilled DAGs to the console: + +``` +$ ./backfill.sh 2021-06-06 2021-06-06 example.etl_orders +backfilling example.etl_orders_7_days... +backfilling example.etl_delivery_7_days... +backfilling example.delivery_times_7_days... +``` + +## 4. Conclusion + +In this blog post, we showed how easy it can be to automate backfilling DAGs downstream of a data quality issue using lineage metadata stored in Marquez. With only two steps, we were able to backfill missing daily table partitions, then automatically re-run failed DAGs downstream of the upstream DAG where the error originated. But, what measures can we put in place to detect low-quality data issues faster, therefore avoiding backfills altogether? Since Marquez collects DAG run metadata that can be viewed using the [Runs API](https://marquezproject.github.io/marquez/openapi.html#tag/Jobs/paths/~1jobs~1runs~1{id}/get), building automated processes that periodically check DAG run states and quickly notifying teams of upstream data quality issue (or missed SLAs) in a timely fashion is just one possible preventive measure. + +We encourge you to explore Marquez's opinionated [Metadata API](https://marquezproject.github.io/marquez/openapi.html) and define your own automated process(es) for analyzing lineage metadata! If you need help or have any questions, you can always join our [Slack](http://bit.ly/MarquezSlack) channel or reach out to us on [Twitter](https://twitter.com/MarquezProject). diff --git a/blog/backfilling-airflow-dags-using-marquez/inter-dag-deps.png b/blog/backfilling-airflow-dags-using-marquez/inter-dag-deps.png new file mode 100644 index 0000000000000000000000000000000000000000..b653803f4a85e19347791816262dd06bf0b512f1 GIT binary patch literal 51268 zcmeFZRajlivNnt*xP{;@L4rF>+##7rAOv?07Tn$465N6YcXxLu5L_lsaQAPJz0O|i zoP93;oBw$ZaMQt`MxtmK~4%4i2w--3JO(5T3itd3bqvr3fckTCGccy zluHNr2W_V)B??tKO0)}nP%u)JF_x8udJEhmK*2!2f`Wan0$fl*W>9c{?xCQlf&YN0 zOz6K$GhzO#6t*=J_P_3-9iA)th5d*Hgs7Q)RJB)?1%nK%Et&KTt@VwVoGrgRSAgPo z1_8I0M)rDS&XyKdb|7Z~ia#|#!2R=MW(u-DRqV|LC{$$?$i%E|jmS8eIG9){1d+(d z$oOpyjX{dyl7GDpd=j8AwYUEQVrF)7a$<5~XR@|6VP@s!QT|KFf5{OyvNNzX`(kfqZAJDhS5M#C!CruZ;<=%J|NTo(do$y|Te7nI%Phb^ z=I0V-Rwfqaf6E45<$rz(lD9Q80$P5SFUZROr{;fq_E$Un%+HPgLz#bB`sXQNsvr_S 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unBj~E} zC%@t#J|^%*kvf6bP@5zsrkqVXe**u3S=l^L^mH$F>Th)ud*UMNk9H`Qo682Vd^%i6 z63#FoxbchdA|;n`>>Sjgx%hBT8fFQXy_ILGeiZO zoWl@S4yj^sX6D4G?8tWp>Exr(wwlN(uKg!WNGXsIf;UM-mkh z0eRIk=nk8>+8RZ6WvRCy-n z1F9$`l%bJ2@&-C_A3-Ji(kS9v!fvG&dYZC(W?c=x$!MZ-5FI0Ujf1!|cDS(RfOCSl zrixRBqXM_kx2A(5L#nhvWbF|f1$UD3hT(fgNTXmiW*JjuA#-;GC>!V$EEIHcuf+5; z#K)-j>Z}RHxzQwAz4+E|5}-YNU17um_f3;M7+vcK%G=;mr_)SEOh2Duzg8Z0aIi=~ zICF_tIM$vW*GkqT=ARd`KP!%ov5^u$@0d|X2Zo_`=OZHBBPl6!ntaDl7eCjS+_mq? zx_PWqM(Nf5mGOHZYz{+Wg7XS%=#7?Kf_bx2zP>29QVQdHdbi*sHv&F4sHNa2kpKqs zL37>Pms5UF6S-46+@4vlP)?KM5|WRwfiFhY4_CHaeZlEZ0Up?)X7QN1Dc2q2rvl;I zqc}+rBgqqcns#b2{gZ+&Z8Z(EUC8-cnA$YH$;UT%Q8>$YpKB9->|^?4A$1bZP5>pU zB8t{_HukXK67JNFt9p=;0$wKc z7IqA3LNU!TDTgefGr5M0BA)7*Sy62jKFXS)eCG<4#m-srqp#0%CFpAWc3A90Z=LM4 zdcYoAi|nCohreb}I(U)?9m|1wR zdUY00-D?Bw7}`er!vn)YCCxsgl_KRy`bd?_*B10f)E1y56mmGEYmuc1qiq=d^}u?x zj~!J#h=$J~Ys$!A`UQ8Vf>*DA?K#Wj)5$z`xIvElw>rYeElG&R^Ymzj!m6}x?Swqi zl}7nS!m&=4A=AYKSFA3YtX?Hs9k?=H*c_YGj1e8hOTi z{o3{)b$+~Wc-#3Z=lt}DB?H!}Nbx@7jWX<5KjO&XhZ>{7_m zTzMLU|$w=gK!nU_>FLsc9L;i{jgm~ z(t*&>p}Z1NDiTU;Hy)1|z@!S1HH;-BAzjF8LUwk=;OA} ziP^(X!tGV|l#UijKosYG&@qx{%obih>x3Fst;7IXL7?OtvGj}mSiAgv_v`SQ^7Ab1 zvdFV1RrVyY4DxY?vY3oOk=CVR4M}8~%!5cvoZ$R?QK~ZRqG&+;aD4->&`<(2CCX4! zdH>UtkV9lV%ZXri68qbexZ~A>l5(Z5Oo?;<-(JSZD^O6At66^ZZwrE*3LF4xK5t0= z?Pa{70ofY=MmW!Har|*d5a@{*;J&c_+cg0hS`x_6HZ!E>{=GZ}2S~5tlu%l|{%x+< wVTqpS{ck{j+eo7SyF>q5L;t + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/column-lineage/image.svg b/blog/column-lineage/image.svg new file mode 100644 index 0000000000..6042cf181e --- /dev/null +++ b/blog/column-lineage/image.svg @@ -0,0 +1,36 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/column-lineage/index.mdx b/blog/column-lineage/index.mdx new file mode 100644 index 0000000000..98d701fc4c --- /dev/null +++ b/blog/column-lineage/index.mdx @@ -0,0 +1,86 @@ +--- +title: The Current State of Column-level Lineage +date: 2022-09-02 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: Column-level lineage helps organizations navigate a complex regulatory landscape. +--- + +Column-level lineage helps organizations navigate a complex regulatory landscape. + +![](./banner.svg#full-width) + + + +### Overview & background + +Long one of our most requested new features, column-level lineage was added to the [Spark integration](https://github.com/OpenLineage/OpenLineage/tree/main/integration/spark) with the release of [OpenLineage 0.9.0](https://github.com/OpenLineage/OpenLineage/releases/tag/0.9.0). Project committer Paweł Leszczyński ([@pawel-big-lebowski](https://github.com/pawel-big-lebowski)) authored the relevant pull requests ([#645](https://github.com/OpenLineage/OpenLineage/pull/645), [#698](https://github.com/OpenLineage/OpenLineage/pull/698), [#738](https://github.com/OpenLineage/OpenLineage/pull/738) and [#772](https://github.com/OpenLineage/OpenLineage/pull/772)). In its current form, column-level lineage in OpenLineage is limited to the Spark integration and not yet visible in the [Marquez](https://marquezproject.ai/) UI. But this is only the first step in a broader, ongoing project to implement the feature across the project, and we’d love your help. + +Column-level lineage is a worthy pursuit. It dramatically extends the reach of OpenLineage’s metadata capture, providing finely grained information about datasets' dependencies. As Paweł and project lead Julien Le Dem ([@julienledem](https://github.com/julienledem)) wrote in the initial proposal, “Not only can we know that a dependency exists, but we are also able to understand which input columns are used to produce output columns. This allows [for] answering questions like ‘Which root input columns are used to construct column x?’” + +Another reason to pursue column-level lineage: the demands of regulatory compliance. Bodies such as the [GDPR](https://gdpr-info.eu/), [HIPAA](https://www.hhs.gov/hipaa/index.html), [CCPA](https://oag.ca.gov/privacy/ccpa), [BCBS](https://www.bis.org/bcbs/) and [PCI](https://www.pcisecuritystandards.org/) have instituted requirements for data accuracy and integrity that compel companies and organizations to obtain deeper insight into their datasets and pipelines. + +### Why start with the Spark integration? + +As Julien and Paweł's proposal [suggests](https://github.com/OpenLineage/OpenLineage/tree/main/proposals/148), the Spark integration was a logical starting point for adding column-level lineage. This is so because the integration relies on implementing visitors that traverse a `LogicalPlan` and extract meaningful information when encountered. These data include outputs and inputs with their schemas (which we were already identifying, in fact). The `LogicalPlan` also exposes the expressions that derive the output columns from the input columns. They can be inspected to derive column-level lineage. Traversing the `LogicalPlan` allows for the capturing of all the dependencies required to build column-level lineage. + +### A new facet in the spec + +In the process of implementing column-level lineage, Paweł and Julien contributed a new facet schema, `ColumnLineageDatasetFacet`, to the OpenLineage spec. This facet uses fields to relay data points about dependencies. These are properties of items in the `InputField` property of the facet (`namespace`, `name` and `field`), as well as two human-readable string fields (`transformationDescription`, `transformationType`) for conveying information about dataset transformations. The last field, `transformationType`, may be especially useful for those whose companies or organizations need to track the usage of sensitive personal information. + +An example of a `columnLineage` facet in the outputs array of a lineage event: + + { + "namespace": "{namespace of the outputdataset}", + "name": "{name of the output dataset}", + "facets": { + "schema": { + "fields": [ + { "name": "{first column of the output dataset}", "type": "{its type}"}, + { "name": "{second column of the output dataset}", "type": "{its type}"}, + ... + ] + }, + "columnLineage": { + "{first column of the output dataset}": { + "inputFields": [ + { "namespace": "{input dataset namespace}", name: "{input dataset name}", "field": "{input dataset column name}"}, + ... other inputs + ], + "transformationDescription": "identical", + "transformationType": "IDENTITY" + }, + "{second column of the output dataset}": ..., + ... + } + } + } + +### How it works + +As we’ve seen, column-level lineage is being collected via the new `columnLineage` dataset facet. For each output, this facet contains a list of the output's fields along with the input fields used to create it. The input fields are identified by a `namespace`, `name` and `field`. But how is OpenLineage obtaining the data about dependencies that the facet relays? + +In PR [#698](https://github.com/OpenLineage/OpenLineage/pull/698), Paweł describes the mechanism this way: +1. The core mechanism first gets an output schema and logical plan as inputs. +2. Then, the `OutputFieldsCollector` class traverses the plan to gather the outputs. Outputs can be extracted from Aggregate or Project, and each output field has an `ExprId` (expression ID) that is attached from the plan. +3. Next, the `InputFieldsCollector` class is used to collect inputs that can be extracted from `DataSourceV2Relation`, `DataSourceV2ScanRelation`, `HiveTableRelation` or `LogicalRelation`. Each input field takes its `ExprId` from the plan, and each input is identified by a `DatasetIdentifier`, which means it contains the name and namespace of a dataset and an input field. +4. Finally, the `FieldDependenciesCollector` traverses the plan to identify dependencies between different `ExprIds`. Dependencies map parent expressions to children expressions. This is used to identify the inputs used to evaluate certain outputs. + +### What’s next? + +Work on extending column-level lineage in the project is ongoing. For example, project committer Will Johnson ([@wjohnson](https://github.com/wjohnson)) has opened a PR ([#963](https://github.com/OpenLineage/OpenLineage/issues/963)) to add support for common dataframe operations not covered due to the initial focus on Spark. As Will writes in the PR, + +> Currently, the Column Lineage Input Field Collectors work mainly for Spark SQL operations and Data Source V2. +> This leaves out normal dataframe operations like inserting into HDFS without the use of a Hive table. +> Column Lineage should support this scenario as many users will want to see column lineage for operations outside of SQL and Hive Metastore backed tables. + +Also, Paweł has written enhancements that will [enable column-level lineage in the case of altered table and column names](https://github.com/OpenLineage/OpenLineage/issues/993) and [allow one to extend column-level lineage without contributing to OpenLineage](https://github.com/OpenLineage/OpenLineage/issues/738) (to avoid exposing proprietary code, for example). + +Meanwhile, over in Marquez, Julien has contributed a [proposal](https://github.com/MarquezProject/marquez/issues/2045) to add a column-level endpoint to the project that would leverage OpenLineage’s `ColumnLineageDatasetFacet`. This approach would add column lineage to an existing endpoint by embedding the `columnLineage` facet in the data section of the `DATASET` nodes. + +### How can I contribute? + +We welcome contributions to this ongoing effort at implementing column-level lineage in OpenLineage! If you’re interested in contributing, one of our existing [integrations](https://github.com/OpenLineage/OpenLineage/tree/main/integration) might be a good place to start. OpenLineage’s growing list of integrations includes Airflow, dbt, Dagster and Flink. + +Sounds fun? Check out our [new contributor guide](https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md) to get started. diff --git a/blog/data-agility-day/banner.svg b/blog/data-agility-day/banner.svg new file mode 100644 index 0000000000..dfbfc266cc --- /dev/null +++ b/blog/data-agility-day/banner.svg @@ -0,0 +1,36 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/data-agility-day/image.svg b/blog/data-agility-day/image.svg new file mode 100644 index 0000000000..6313a1ac98 --- /dev/null +++ b/blog/data-agility-day/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/data-agility-day/index.mdx b/blog/data-agility-day/index.mdx new file mode 100644 index 0000000000..7089083e6d --- /dev/null +++ b/blog/data-agility-day/index.mdx @@ -0,0 +1,23 @@ +--- +title: Video - OpenLineage at Data Agility Day +date: 2021-11-17 +author: Ross Turk +image: ./image.svg +banner: ./banner.svg +description: At Data Agility Day 2021, Julien Le Dem and Kevin Mellott outlined their approach to data lineage and discussed various approaches to implementing it in the real world. +--- +At Data Agility Day 2021, Julien Le Dem and Kevin Mellott outlined their approach to data lineage and discussed various approaches to implementing it in the real world. + +![](./banner.svg#full-width) + + + +OpenLineage made an appearance at Data Agility Day 2021, when contributors Julien Le Dem and Kevin Mellott took the virtual stage for a casual conversation about data lineage. The result was both informative and enjoyable. + +If you couldn't make the event this year, that's okay! The video is now available, and it's *almost* as good as being there in person. + + + +Julien Le Dem is the creator and lead engineer of OpenLineage. Kevin Mellott implemented the Enterprise Data Platform at Northwestern Mutual, and recently shared [a post detailing his team’s experiences](/blog/openlineage-at-northwestern-mutual). + +The video is also available at the [Data Agility Day site](https://dataagility.io/october2021/nw-mutual-datakin/), where you can keep an eye out for future events. diff --git a/blog/data-lineage-meetup/banner.svg b/blog/data-lineage-meetup/banner.svg new file mode 100644 index 0000000000..494c681fa3 --- /dev/null +++ b/blog/data-lineage-meetup/banner.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/data-lineage-meetup/image.svg b/blog/data-lineage-meetup/image.svg new file mode 100644 index 0000000000..dbaf56b865 --- /dev/null +++ b/blog/data-lineage-meetup/image.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/data-lineage-meetup/index.mdx b/blog/data-lineage-meetup/index.mdx new file mode 100644 index 0000000000..1db2660cb0 --- /dev/null +++ b/blog/data-lineage-meetup/index.mdx @@ -0,0 +1,38 @@ +--- +title: Happening Soon - Our First Meetup! +date: 2023-02-08 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: The inaugural Data Lineage Meetup will take place on March 9th in Providence, RI. +--- +The inaugural Data Lineage Meetup will take place on March 9th in Providence, RI. + +![](./banner.svg#full-width) + + + +Join us on Thursday, March 9, 2023 from 6-8 pm in Providence, Rhode Island to learn more about the present and future of OpenLineage. Meet other members of the ecosystem, learn about the project’s goals and fundamental design, and participate in a discussion about the future of the project. Bring your ideas and vision for OpenLineage! + +Food will be provided, and the meetup is open to all, no registration needed. Don't miss this opportunity to influence the direction of this important new standard! We hope to see you there. + +### Time, Place & Format + +Date: March 9, 2023 +Time: 6-8 pm ET +Address: [CIC](https://cic.com/providence), [225 Dyer Street](https://goo.gl/maps/NYBbs4ht91dWWaRs9) +City: Providence, RI, US 02903 +Format: In-person + +#### Getting There +- Air: the nearest airport is T.F. Green/PVD. Boston Logan is also within 1.5-2 hours' driving distance. +- Rail: Amtrak serves [PVD](https://goo.gl/maps/eAMNPcpQVJkqwyS76), which is within walking distance of CIC. +- Road: garages and lots are a short walk away from the venue, and metered street parking is also available nearby. + - [Richmond Garage](https://goo.gl/maps/nG8j8Vk6ko75GXaH9) + - [South Street Landing garage](https://goo.gl/maps/QYrbo1oaiU4J3fi69) + - [Clifford parking lot](https://goo.gl/maps/qHoLkRcGmWpxeHhJ8) + +#### Getting In +- Check in with the CIC concierge inside the north entrance. The concierge will direct you to the Hope Island Room on the 3rd floor. + +### Hope to see you there! diff --git a/blog/dataquality_expectations_facet/bad_data.png b/blog/dataquality_expectations_facet/bad_data.png new file mode 100644 index 0000000000000000000000000000000000000000..c032eadacefe9f4fd3ee70456de655c5b9d7ec01 GIT binary patch literal 355750 zcmV)*K#9MJP)3vcrJ(El(ne^U6NGBCSLI*(+vA12z zs=I6Nf>NaS-t2XYt9v}>aZc_bM0TIw^LhPveC{%nnc*(i`Mr+wysrDd(xStV5gP@o z*@Ucw7}$~$kd z+l7eo_eXR8$GHP9F7!3&WZBKw2ro}Wc`wlKi}mwET6mPoBF8V&WJXqOGIGpm$W5>!H^qvqcsb6I zF)#&$Al!SQD#FJfk)jA$k6RcFvz+6kkVyTEyo5AV+w##?UW1W=x1hrdp6^$;E)2pKb5%#>F$=;P~NBv1`W()koV7W5-8_@zDo+@cPSd;;{!F!eCc7 zTB|D2P?(42vSKVQ%|}C#9W{AbsK`#&^Tl&ll#zsjG@e&8a+70WPm=SMXhL>Ev?|9O zE%!qda!jGHMFqni6NWN*Z@rxJ=E5Ab7U$}Em3$WWm!`z23i%n)A<|CxAUi4uxiP^g zPK-pQB@T5tDQL{MprtSitwlC;72DBMmWQQf`B)~uvtK^5zbF?gR$$k2f+y7wYlPi;qM}vRUq> zWK>x#sIggPX+=qD3T&~lNDdA`tdF#B^A{j=o~J6@(-V;k7HC_U5EO*uun<`W%KLoe 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Developers used +our libraries and a microservice we maintained to “trigger” an experiment for a customer- that is, the customer was +randomized into either control or treatment and the resulting assignment was recorded in the logs, which my team +consumed in the analysis of the data later on. One of the interesting parts of my job was helping our users diagnose +problems with their experiment results. + +A classic example was a Kindle developer who was prototyping a new feature for book pages that would make the site more +engaging for Kindle owners- perhaps a “look inside” feature, or maybe some better recommendations. A customer would come +to the website and the developer’s code would determine if the customer belonged in _Control_ or _Treatment_. If _Control_, +the assignment was logged and no feature was shown- the site looked to the customer as it always had. But if the +assignment was _Treatment_, the code would check the customer’s account to determine if they owned a Kindle device and, +if yes, the assignment was logged and the customer saw the fancy new feature on the books page. + +The experiment showed the developer’s feature would be wildly successful- an increase of over $10 in Kindle book +purchases per customer on average over the course of the 2 weeks the experiment ran- projected to be tens of billions of +dollars in annual revenue due to this one feature! + +With data in hand, the developer requested tons of resources to build the feature up to production standards. After +three months and two dozen people’s labor, the feature was ready to ship. The developers deployed their new service and +the incredible feature was unleashed. For days afterward, everyone watched the metrics dashboards waiting for that +hockey stick uptick in the revenue graphs 📈. But it never materialized! The graph was flat. No change at all! Weeks +went by. Nothing. How could the experiment results be so far from reality? + +Of course, if you’ve ever run A/B tests, you probably already recognized the developer’s mistake. In their randomization +logic, customers who were assigned control were logged and forgotten, while customers who were assigned treatment were +logged only after validating that they owned a Kindle device. It turned out the total number of customers who came to +amazon.com was far greater than the number of customers who owned a Kindle device. And if you divide the total sum of +Kindle book sales by all of the amazon.com customers, regardless of whether they own a Kindle device, that average +will come out quite a lot lower than if you calculate the average Kindle book revenue from only customers who own Kindles. + +![Yoda says, poorly run experiments lead to bad data. Bad data leads to bad insights. Bad insights lead to bad decisions. Bad decisions lead to suffering](./bad_experiment.png) + +In reality, this story never happened. Why? Because we knew the adage- Bad Data is Worse than No Data. In the story, +people took data of poor quality and used it to justify bad decisions. In our system, we checked the quality of the data +and, if we detected assignment imbalances, we simply invalidated the experiment and hid the results. Over the years, I +can’t count the number of times our users asked us to just give them partial results or just exclude certain segments or +to let them know if things were “trending” the right way. Our policy was firm- if we couldn’t trust the quality of the +data, the results were meaningless and we would not surface them in our system. + +## Data-Driven Depends On Data-Quality + +Today, most businesses consider themselves data-driven. The stereotype of the maverick CEO leading with his or her gut +is mostly antiquated, with a handful of exceptions. And yet, even though people know intellectually that data is only +useful if it is correct, we tend to stop digging once we find some data that confirms our pre-existing assumptions. We +justify bad decisions by claiming that they are “data-based” without ever validating the quality of our sources. Where +did that data come from? How old is it? Is the logic that generated it correct? Is it derived from some other dataset? +What is the quality of that dataset? +![Data-driven: You keep using that word. I do not think it means what you think it means](./data_driven.png) + +Thankfully, data quality validation is becoming more and more common in data engineering organizations. In part, this is +due to the prevalence of new tools and their integration with common workflow engines which we already use to schedule +the jobs that generate and process our data. One such tool that has been gaining in popularity is called [_Great +Expectations_](https://docs.greatexpectations.io), a Python-based framework for defining assertions about data sets +which easily integrates with existing workflow tools, such as Airflow. + +In software development, testing the behavior of our code with unit and integration tests has been common practice for +years. Similarly, using Great Expectations, a data engineer can assert that a dataset has a row count that falls within +an expected range, that column values are not null, or that values match a specified regular expression. One can even +create custom expectations, such as validating that the number of records in treatment is roughly the same as the number +of records in control (this post is not intended to be an in-depth tutorial on setting up Great Expectations; if you +want to read more on its capabilities and to get started, I recommend the going through +the [Quick Start tutorial](https://docs.greatexpectations.io/en/latest/guides/tutorials/quick_start.html)). + +### A Sample Assertion Suite + +As a simple example, imagine a table of new customers that you need to import into your Data Warehouse. Before +importing, we want to check the data quality of this new batch of customers. One example suite of assertions we could +test is below: + +```json +{ + "data_asset_type": "Dataset", + "expectation_suite_name": "customers_suite", + "expectations": [ + { + "expectation_type": "expect_table_row_count_to_be_between", + "kwargs": { + "max_value": 1000, + "min_value": 100 + }, + "meta": {} + }, + { + "expectation_type": "expect_table_column_count_to_equal", + "kwargs": { + "value": 8 + }, + "meta": {} + }, + { + "expectation_type": "expect_table_columns_to_match_ordered_list", + "kwargs": { + "column_list": [ + "id", + "created_at", + "updated_at", + "name", + "email", + "address", + "phone", + "city_id" + ] + }, + "meta": {} + }, + { + "expectation_type": "expect_column_values_to_be_unique", + "kwargs": { + "column": "email" + }, + "meta": {} + } + ], + "meta": { + // ... + } +} + +``` + +This sample suite contains 4 data quality assertions- that the dataset contains between 100 and 1000 rows, that the +table contains exactly 8 columns, that they match the explicit list of column names we expect, and that the `email` column +contains only distinct values. + +### Adding Data Quality Checks to an Airflow pipeline + +With a suite of assertions in hand, we can update our Airflow DAG to only import data into our Data Warehouse if it +matches our expectations. A simple DAG might look like this + +```python +from airflow import DAG +from airflow.contrib.operators.bigquery_operator import BigQueryOperator +from airflow.utils.dates import days_ago +from great_expectations_provider.operators.great_expectations import GreatExpectationsOperator + +dag = DAG( + 'etl_customers', + schedule_interval='@daily', + catchup=False, + default_args=default_args, + description='Loads newly registered customers daily.' +) + +t1 = BigQueryOperator( + task_id='if_not_exists', + sql=''' + CREATE TABLE IF NOT EXISTS food_delivery.customers ( + id INT64, + created_at TIME, + updated_at TIME, + name STRING, + email STRING, + address STRING, + phone STRING, + city_id INT64 + ) + ''', + use_legacy_sql=False, + dag=dag +) + +t2 = GreatExpectationsOperator( + expectation_suite_name='customers_suite', + batch_kwargs={ + 'table': 'tmp_customers', + 'datasource': 'food_delivery_db' + }, + dag=dag + task_id='customers_expectation', +) + +t3 = BigQueryOperator( + task_id='etl', + sql=''' + SELECT id, created_at, updated_at, name, email, address, phone, city_id + FROM food_delivery.tmp_customers + ''', + destination_dataset_table='airflow_marquez.food_delivery.customers', + use_legacy_sql=False, + dag=dag +) + +t1 >> t2 >> t3 +``` + +This is great! Our DAG creates our target table in BigQuery (if it doesn’t already exist), checks the quality of the +`tmp_customers` table by running the `customers_suite` defined earlier, then imports _only if all_ of the data quality +checks pass. + +And thus ended all data quality problems forever. + +Just kidding. + +Because reality is never so straightforward. In reality, the recommendations team wanted to start generating +recommendations for new customers without waiting until the next day, so they built a data pipeline to start consuming +from the `tmp_customers` table directly. And the supply chain folks wanted to start detecting what recipes are gaining +popularity so they can predict what supplies will need to be restocked sooner, so they started reading from the both +`tmp_orders` table and the `tmp_customers` table before they’re available in the DW. Oh, and the scheduling team needs +an idea of the geography of the various customers that are ordering and what the distances are between restaurants and +customers so they can get the right number of drivers in the right neighborhoods and of course the marketing team wants +to use all of this data to make predictions about how much to spend on the right search engine and social media ads and +they absolutely cannot wait until tomorrow at 8AM to update their models. +![I am the gatekeeper](./gatekeeper.png) + +## Tracing Data Quality With OpenLineage Facets + +Users are never satisfied with the way things are supposed to work. There’s always a reason to work around gatekeepers- +oftentimes, very good reasons that have real business impact- and data engineering is full of creative and resourceful +people who absolutely will find a way to get at that data. Even at Amazon, the experiment data was available in the +click stream logs, so resourceful users could (and sometimes did) calculate their own experiment results if they really +wanted to. So it’s important not just to have data quality checks, but to trace the impact of that data throughout an +organization. + +The OpenLineage standard uses [Facets](https://openlineage.io/blog/extending-with-facets/) to augment the core data +model with useful information about the jobs, runs, and datasets reported on. One interesting detail about facets is +that they can be attached to an entity after the fact. In the Marquez reference implementation, a dataset version is +created every time a job run writes to or otherwise modifies a dataset. _Output_ facets, such as the new record count or +the number of bytes written, are attached directly to the dataset version when the job run completes. But consuming +jobs can also attach facets to the version of the dataset that exists at the start time of the job’s execution. + +In the OpenLineage Airflow integration, Great Expectations tasks, such as the one in our example DAG above, are +evaluated after they run and the expectation results (as well as some other data quality metrics) are collected +into a +[DataQuality Metrics Input Dataset Facet](https://github.com/OpenLineage/OpenLineage/blob/main/spec/OpenLineage.json#L446-L499) +, which is reported to the server along with the rest of the lineage metadata. In Marquez, we recognize the version of +the dataset that was read by the job run and the data quality metadata is permanently associated with that dataset +version. The impact of this is that any job that reads that data, whether it happens before or after the dataset quality +assertion, can be linked to the data quality facet recorded (provided that the dataset version doesn’t change between +the data quality check and the read job). + +This integration is extremely straightforward to get working. If you already have the Marquez Airflow DAG running in +your Airflow workflows, there’s nothing to do! Great Expectations tasks are already being detected and the metrics and +assertion statuses are already being reported to your configured instance of Marquez. + +If you’ve never integrated Marquez with your Airflow setup, add a couple +of [environment variables](https://github.com/OpenLineage/OpenLineage/tree/main/integration/airflow#configuration) +and [change one line of code](https://github.com/OpenLineage/OpenLineage/tree/main/integration/airflow#usage): + +```diff +- from airflow import DAG ++ from marquez_airflow import DAG +from airflow.contrib.operators.bigquery_operator import BigQueryOperator +from airflow.utils.dates import days_ago +from great_expectations_provider.operators.great_expectations import GreatExpectationsOperator +``` + +I’ve previously written +about [how to determine the version of the dataset that was read by a particular job run](https://openlineage.io/blog/explore-lineage-api/) +. With Great Expectations now integrated into my Airflow DAG, I want to see what the data quality metrics are for the +latest version of the `customers` dataset that was processed by my ETL job. I’ll hit my datakin demo instance: + +```bash +$ curl "https://demo.datakin.com/api/v1/namespaces/food_delivery/jobs/etl.etl_delivery_7_days" | jq | less +{ + "id": { + "namespace": "food_delivery", + "name": "etl.etl_delivery_7_days" + }, + "type": "BATCH", + "name": "etl.etl_delivery_7_days", + "createdAt": "2021-07-23T19:32:03.401782Z", + "updatedAt": "2021-08-06T05:11:03.604573Z", + "namespace": "food_delivery", + "inputs": [ + { + "namespace": "food_delivery", + "name": "public.customers" + }, + //... + ], + "latestRun": { + "id": "1043e596-ccb8-4bfb-8fc2-7ee066253248", + "jobVersion": { + "namespace": "food_delivery", + "name": "etl.etl_delivery_7_days", + "version": "bc6c294b-b0eb-3160-a06d-1ff9ba3a4e1c" + }, + "inputVersions": [ + { + "namespace": "food_delivery", + "name": "public.customers", + "version": "4c33f292-40a9-304d-b43f-c7ffb2256e7f" + }, + // ... + ], + // ... + } +} +``` + +With the input version of the `public.customers` dataset, I can query Marquez for all the metadata we have about that +specific version of the dataset. + +```bash +$ curl "https://demo.datakin.com/api/v1/namespaces/food_delivery/datasets/public.customers/versions/4c33f292-40a9-304d-b43f-c7ffb2256e7f" | jq | less +{ + "id": { + "namespace": "food_delivery", + "name": "public.customers" + }, + "type": "DB_TABLE", + "name": "public.customers", + "physicalName": "public.customers", + "createdAt": "2021-08-06T05:02:59.189118Z", + "version": "4c33f292-40a9-304d-b43f-c7ffb2256e7f", + "namespace": "food_delivery", + "sourceName": "analytics_db", + "fields": [ + { + "name": "id", + "type": "INTEGER", + "tags": [], + "description": "The unique ID of the customer." + }, + // ... + ], + "facets": { + "stats": { + "size": 53362712, + "rowCount": 4969 + }, + "dataSource": { + "uri": "jdbc:postgresql://localhost:3306/deliveries", + "name": "analytics_db" + }, + "description": "A table for customers.", + "dataQuality": { + "bytes": 53362712, + "rowCount": 4969, + "columnMetrics": { + "id": { + "nullCount": 0, + "distinctCount": 4969 + }, + "name": { + "nullCount": 0, + "distinctCount": 4969 + }, + "email": { + "nullCount": 0, + "distinctCount": 4969 + } + } + }, + "greatExpectations_assertions": { + "assertions": [ + { + "success": true, + "expectationType": "expect_table_row_count_to_be_between" + }, + { + "success": true, + "expectationType": "expect_column_to_exist" + }, + { + "success": true, + "columnId": "id", + "expectationType": "expect_column_values_to_be_unique" + }, + { + "success": true, + "columnId": "id", + "expectationType": "expect_column_values_to_not_be_null" + }, + { + "success": true, + "columnId": "created_at", + "expectationType": "expect_column_values_to_not_be_null" + }, + //.... + ] + } + } +} +``` + +Note the `facets` field contains several properties- `stats`, `dataSource`, `description`, `dataQuality` +and `greatExpectations_assertions`. Each of those describes some attribute about the dataset version. Some of the facets +are attached at write-time, some are attached later- when the dataset is read. + +In our [Datakin demo](https://demo.datakin.com), we have a lot more assertions than what I included in the sample suite +above and that can be seen in this response. In addition to counting rows and columns, we also validate that id columns +are unique and non-null, timestamps fall within specified ranges (did you know that if you accidentally write a +timestamp too far in the future, certain JDBC drivers will overflow the Calendar instance they use for converting +timezones?), and emails match expected regular expressions. + +With the ability to attach data quality facets to dataset versions and the ability to trace the specific versions of +datasets read by and written to by specific job runs, I can trust whether the data I’m looking at is good data or bad +data. And if my data quality checks fail, I can find out whether I need to contact somebody over in marketing or +recommendations to [backfill their pipelines](https://openlineage.io/blog/backfilling-airflow-dags-using-marquez/) once +the issue has been corrected. + +![Good data, bad data](./bad_data.png) + +Whether your business is an e-commerce shop that wants to improve its customer experience or a music streaming service +that wants to make better listening recommendations or an autonomous vehicle company trying to improve the car’s ability +to detect double parked vehicles, the quality of your data is paramount to making good decisions. Quality testing tools +are out there and, chances are, they already work with the pipeline workflow tool you’re using today. 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to Visualize dbt Models +date: 2021-09-21 +author: Ross Turk +image: ./image.svg +banner: ./banner.svg +description: Each time dbt runs, it generates a trove of metadata about datasets and the work it performs with them. In this post, I’d like to show you how to harvest this metadata and put it to good use. +--- +Each time dbt runs, it generates a trove of metadata about datasets and the work it performs with them. In this post, I’d like to show you how to harvest this metadata and put it to good use. + +![](./banner.svg#full-width) + + + +```toc +``` + +The first time I built a data warehouse was in a completely different era, even though it wasn’t all that long ago. It was a few dozen tables + a collection of loader scripts and an ETL tool. If I’m honest, calling the whole thing a “data warehouse” is a bit grandiose, but it worked. + +At the time, my defining question was “how can I make all of my most important data available for study without spending more than it’s worth?” Because my database capacity wasn’t infinite, I couldn’t keep all of my data forever. The jobs I wrote would pull data from operational data stores, perform a bunch of slicing and aggregation, and load summary data into the warehouse. They shoveled bits every night from one server to another, performing calculations in between - and that meant they had to run on a beefy server with close proximity to my data. + +Skip forward to the current day and here I am, building and running models from a cafe over pretty shaky wifi. **My, how things have changed.** + +Cloud data warehouses like [Google BigQuery](https://cloud.google.com/bigquery/), [Amazon Redshift](https://aws.amazon.com/redshift/), and [Snowflake](https://www.snowflake.com) have created a new economic and technological possibility: we can now pretty much just load everything - including our entire operational data stores - into a single warehouse. Once everything is in one place, data can be sliced up and analyzed much more quickly. This is where [dbt](https://www.getdbt.com) shines, at making transformations within a cloud data warehouse easy. And we all know what happens when you make something easy: it finds a way to happen a lot. People are doing more complex transformations than ever before, and the need for lineage context is becoming greater than ever. + +Fortunately, each time dbt runs it generates a trove of metadata about datasets and the work it performs with them. In this post, I’d like to show you how to harvest this metadata and put it to good use. + +# Our Example + +For our example, let’s choose the kind of experiment that I might run in my day-to-day life. I’m the head of marketing at [Datakin](https://datakin.com), which means the metrics I’m most interested in are usually about some sort of human behavior. + +I ask questions like: +* Does [x] technology space matter, and to whom? Is it waxing or waning? +* Are there adjacent ecosystems we should be collaborating with? +* Who are the influencers in this space? Who are the major contributors? +* What challenges are users facing? What does successful adoption look like? + +There are a lot of ways to try to answer these questions. None of them are any more reliable than human behavior itself, and every resulting metric requires analysis and judgment. But there are still some pretty fun things to discover. And what better data source to mine to understand technical audiences than [Stack Overflow](https://www.stackoverflow.com)? + +So let’s see what we can learn from the Stack Overflow [public data set in BigQuery](https://cloud.google.com/blog/topics/public-datasets/google-bigquery-public-datasets-now-include-stack-overflow-q-a). But not the whole thing; it is very large, so let’s study just a part of it. I created a [sample dbt project](http://github.com/rossturk/stackostudy/) that contains a handful of models to study all of the questions and answers we can find about the topic of ELT. These models: + +* Create slices of the key Stack Overflow tables, pulling them into a separate BigQuery project. These slices only contain the rows that are related to questions tagged with “elt”. That way, we can query them tortuously all day long without scanning through gobs of partitions and running up our bill. +* Augment these slices by performing some helpful calculations - in this case, the number of upvotes/downvotes per question. +* Populate two summary tables for consumption by a BI system of some sort: a daily summary table that can be used to study trends and a user summary table that can be used to learn about the most influential contributors. + +This is exactly the kind of experiment I have run multiple times over the years, across numerous stacks. It’s usually pretty messy. But this time, after running all of these models, we will be rewarded with a gorgeous [Marquez](https://marquezproject.ai/) lineage graph. We’ll be able to see how everything fits together. + +# Setting Everything Up + +First, if you haven’t already, run through the excellent [dbt tutorial](https://docs.getdbt.com/tutorial/setting-up). It will show you how to create a BigQuery project, provision a service account, download a JSON key, and set up your local dbt environment. The rest of this example assumes that you have created a BigQuery project where our models can be run, and you know how to properly configure dbt to connect to it. + +Next, let’s start a local Marquez instance to store our lineage metadata. Make sure you have Docker running, and then: + +```bash +git clone https://github.com/MarquezProject/marquez.git && cd marquez +./docker/up.sh +``` + +Check to make sure Marquez is up by visiting [http://localhost:3000](http://localhost:3000). You should see an empty Marquez instance with a message saying there isn’t any data. Also, you should be able to see the server output from your requests in the terminal window where Marquez is running. Keep this window open until we’re done. + +Now, let’s open a new terminal window/pane and clone the GitHub project containing our models: + +```bash +git clone https://github.com/rossturk/stackostudy.git && cd stackostudy +``` + +Next we need to install dbt and its integration with OpenLineage. I like to do this in a Python virtual environment because I make mistakes - as we all do - and I enjoy knowing that I can burn everything down and start over quickly if I need to. Virtual environments make this easy. To create one and install everything we need, run the following commands: + +```bash +python -m venv virtualenv +source virtualenv/bin/activate +pip install dbt dbt-openlineage +``` + +dbt learns how to connect to your BigQuery project by looking for a matching profile in `~/.dbt/profiles.yml`. Create or edit this file so it contains a section with your BigQuery connection details. You will need to point to the location of a file containing the JSON key for your service account. If you aren’t sure, you can follow [this section](https://docs.getdbt.com/tutorial/create-a-project-dbt-cli#connect-to-bigquery) in the dbt documentation. My `profiles.yml` looked like this when I was done: + +```yaml +stackostudy: + target: dev + outputs: + dev: + type: bigquery + method: service-account + keyfile: /Users/rturk/.dbt/dbt-example.json + project: dbt-example + dataset: stackostudy + threads: 1 + timeout_seconds: 300 + location: US + priority: interactive +``` + +Run `dbt debug` to make sure that you have everything configured correctly. + +```bash +% dbt debug +Running with dbt=0.20.1 +dbt version: 0.20.1 +python version: 3.8.12 +python path: /opt/homebrew/Cellar/dbt/0.20.1_1/libexec/bin/python3 +os info: macOS-11.5.2-arm64-arm-64bit +Using profiles.yml file at /Users/rturk/.dbt/profiles.yml +Using dbt_project.yml file at /Users/rturk/projects/stackostudy/dbt_project.yml + +Configuration: + profiles.yml file [OK found and valid] + dbt_project.yml file [OK found and valid] + +Required dependencies: + - git [OK found] + +Connection: + method: service-account + database: stacko-study + schema: stackostudy + location: US + priority: interactive + timeout_seconds: 300 + maximum_bytes_billed: None + Connection test: OK connection ok +``` + +# A Few Important Details + +There are a couple of considerations to make when designing dbt models for use with OpenLineage. By following these conventions, you can help OpenLineage collect the most complete metadata possible. + +First, when working with datasets outside of your dbt project, define them in a schema YAML file inside the `models/` directory: + +```yaml +version: 2 + +sources: + - name: stackoverflow + database: bigquery-public-data + schema: stackoverflow + tables: + - name: posts_questions + - name: posts_answers + - name: users + - name: votes +``` + +This contains the name of the external dataset - in this case, `bigquery-public-datasets`, and lists the tables that are used by the models in this project. It doesn’t matter what the file is named, as long as it ends with `.yml` and is inside the `models/` directory, so I called mine `schema.yml` 🤷‍♂️ If you hardcode dataset and table names into your queries instead, dbt will likely run successfully but dataset metadata will be incompletely collected. + +When writing queries, be sure to use the `{{ ref() }}` and `{{ source() }}` jinja functions when referring to data sources. The `{{ ref() }}` function can be used to refer to tables within the same model, and the `{{ source() }}` function refers to tables we have defined in `schema.yml`. That way, dbt will properly keep track of the relationships between datasets. For example, to select from both an external dataset and one in this model: + +```sql +select * from {{ source('stackoverflow', 'posts_answers') }} +where parent_id in (select id from {{ ref('filtered_questions') }} ) +``` + +# Performing a Run + +Okay! We are ready to perform a run. Before we do, though, there’s one last step we need to take. + +Run `dbt docs generate`. This will cause dbt to create a `target/catalog.json` file containing the schemas of each dataset referred to in the models. This file will be parsed by the dbt OpenLineage integration and sent to our Marquez server. If it doesn’t exist, a lineage graph will still be generated but schema details won’t be available in Marquez. + +```bash +dbt docs generate +Running with dbt=0.20.1 +Found 8 models, 0 tests, 0 snapshots, 0 analyses, 164 macros, 0 operations, 0 seed files, 4 sources, 0 exposures + +12:15:10 | Concurrency: 1 threads (target='dev') +12:15:10 | +12:15:10 | Done. +12:15:10 | Building catalog +12:15:26 | Catalog written to /Users/rturk/projects/stackostudy/target/catalog.json +``` + +The OpenLineage integration for dbt is implemented as a wrapper, `dbt-ol`. This wrapper runs dbt and, after it completes, analyzes the `target/catalog.json`, `target/run_results.json` and `target/manifest.json` files. It sends corresponding OpenLineage events to the endpoint specified in the `OPENLINEAGE_URL` environment variable. + +To run the models: + +```bash +% OPENLINEAGE_URL=http://localhost:5000 dbt-ol run +Running with dbt=0.20.1 +Found 8 models, 0 tests, 0 snapshots, 0 analyses, 164 macros, 0 operations, 0 seed files, 4 sources, 0 exposures + +12:35:41 | Concurrency: 1 threads (target='dev') +12:35:41 | +12:35:41 | 1 of 8 START incremental model stackostudy.filtered_questions........ [RUN] +12:35:46 | 1 of 8 OK created incremental model stackostudy.filtered_questions... [MERGE (0.0 rows, 34.6 GB processed) in 4.52s] +12:35:46 | 2 of 8 START incremental model stackostudy.filtered_answers.......... [RUN] +12:35:51 | 2 of 8 OK created incremental model stackostudy.filtered_answers..... [MERGE (0.0 rows, 26.8 GB processed) in 5.22s] +12:35:51 | 3 of 8 START incremental model stackostudy.filtered_votes............ [RUN] +12:36:05 | 3 of 8 OK created incremental model stackostudy.filtered_votes....... [MERGE (0.0 rows, 6.5 GB processed) in 14.58s] +12:36:05 | 4 of 8 START incremental model stackostudy.filtered_users............ [RUN] +12:36:21 | 4 of 8 OK created incremental model stackostudy.filtered_users....... [MERGE (0.0 rows, 2.5 GB processed) in 16.09s] +12:36:21 | 5 of 8 START view model stackostudy.summary_daily.................... [RUN] +12:36:23 | 5 of 8 OK created view model stackostudy.summary_daily............... [OK in 1.01s] +12:36:23 | 6 of 8 START view model stackostudy.answer_stats..................... [RUN] +12:36:23 | 6 of 8 OK created view model stackostudy.answer_stats................ [OK in 0.96s] +12:36:23 | 7 of 8 START view model stackostudy.question_stats................... [RUN] +12:36:24 | 7 of 8 OK created view model stackostudy.question_stats.............. [OK in 0.88s] +12:36:24 | 8 of 8 START view model stackostudy.user_stats....................... [RUN] +12:36:26 | 8 of 8 OK created view model stackostudy.user_stats.................. [OK in 1.21s] +12:36:26 | +12:36:26 | Finished running 4 incremental models, 4 view models in 45.39s. + +Completed successfully + +Done. PASS=8 WARN=0 ERROR=0 SKIP=0 TOTAL=8 +Emitted 16 openlineage events +``` + +Note the output showing the number of OpenLineage events emitted to Marquez. + +# Reviewing the Output + +If everything ran successfully you should be able to see a list of jobs when you navigate to http://localhost:3000. Upon clicking a job, you will see a lineage graph that looks similar to this: + +![The stackostudy Marquez lineage graph](./graph.png) + +Our set of models, previously represented by SQL inside text files, has become more easily digestible. The dependencies between datasets are now completely obvious. Data engineers can throw away their remaining whiteboards, hooray! + +There’s something satisfying about seeing models represented in two-dimensional space. But more importantly, this integration allows us to capture the state of a dbt pipeline as it runs. Using a long-running instance of Marquez (or another OpenLineage-compatible metadata repository) this information can be studied as it changes over time. + +To see how the OpenLineage dbt integration works, visit its [GitHub repository](https://github.com/OpenLineage/OpenLineage/tree/main/integration/dbt). diff --git a/blog/explore-lineage-api/banner.svg b/blog/explore-lineage-api/banner.svg new file mode 100644 index 0000000000..4476723c0d --- /dev/null +++ b/blog/explore-lineage-api/banner.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/explore-lineage-api/image.svg b/blog/explore-lineage-api/image.svg new file mode 100644 index 0000000000..74d466627e --- /dev/null +++ b/blog/explore-lineage-api/image.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/explore-lineage-api/index.mdx b/blog/explore-lineage-api/index.mdx new file mode 100644 index 0000000000..034e6175a7 --- /dev/null +++ b/blog/explore-lineage-api/index.mdx @@ -0,0 +1,476 @@ +--- +title: Exploring Lineage History via the Marquez API +date: 2021-07-08 +author: Michael Collado +image: ./image.svg +banner: ./banner.svg +description: Taking advantage of recent changes to the Marquez API, this post shows how to diagnose job failures and explore the impact of code changes on downstream dependents. +--- +Taking advantage of recent changes to the Marquez API, this post shows how to diagnose job failures and explore the impact of code changes on downstream dependents. + +![](./banner.svg#full-width) + + + +Managing a data pipeline means tracking changes. Sometimes changes to your code, sometimes changes to +somebody else’s schema, sometimes to the contents of the data itself. Sometimes you need to +trace the root cause of a problem- somebody changed an int to a string and all the downstream consumers +broke. + +Sometimes you want to make a change and see how your consumers were affected- do all the jobs +run significantly faster after you filter out “unused” records? Or did somebody [rely on those +“unused” records](https://www.hyrumslaw.com/) to be present in the data? + +Do the recommendation models perform better after you "improved" the data cleaning job upstream? Can +you be certain it was your change that improved the performance? + +Sometimes the data itself just looks wrong and you need a way to verify that nothing has broken. Why +was there a huge drop in traffic to the food delivery site yesterday? Was there an outage you didn't +hear about? Competitors outbidding your ads? Or did the website developers simply stop logging some +critical event, corrupting every table in your data warehouse? + +Typically, we think of data lineage in static terms- + +> Job A produces Dataset X, which is consumed by Job B which joins it with Dataset Y and produces +Dataset Z, which is consumed by… + +It’s a map +that we use to get our heads around the dependencies that exist between the datasets we use to make +good decisions (how much inventory should I stock in the warehouse to ensure customers get timely +deliveries?) or to make technical features our customers will love (how can I compile the perfect +road trip playlist given this customer's listening history?). + +But data lineage is much more than a static map of inputs and outputs. _Real time_ lineage and faceted +metadata give us visibility into how the map changes over time and even allow us to look back in +history to see how changes in one part of the map cause ripples in other areas. Taking advantage of some +recent changes to the Marquez API, we’ll demonstrate how to diagnose job failures and how to explore +the impact of code changes on downstream dependents. + +## Getting Started + +To get started, we need a running instance of Marquez with a little bit of seed data. For these +exercises, we'll assume you have a terminal with the following programs installed + +* [docker](https://www.docker.com/products/docker-desktop) +* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) +* [curl](https://curl.se/download.html) +* [jq](https://stedolan.github.io/jq/download/) +* less (optional) + +Download and install any dependencies you don't already have. You'll need the docker daemon running +(see the docs for your platform to get that started). Then check out the Marquez repository +from Github and run the docker image locally: + +```bash +git clone https://github.com/MarquezProject/marquez +cd marquez +./docker/up.sh --seed +``` + +This script uses `docker-compose` to spin up a self-contained installation of Marquez, including a +local database container, web frontend, and service instance. Additionally, it populates a set of +sample data that's useful for exploring the API. You'll know when the seed job is done when you see +the following line in the output logs +``` +seed-marquez-with-metadata exited with code 0 +``` + +Once the seed job is done, we can begin exploring the API. + +### The Jobs +In a separate terminal window, type the following command +```bash +curl "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/" | jq | less +``` + +The output returned should look something like the following +```json +{ + "jobs": [ + { + "id": { + "namespace": "food_delivery", + "name": "example.delivery_times_7_days" + }, + "type": "BATCH", + "name": "example.delivery_times_7_days", + "createdAt": "2021-06-24T21:50:39.229759Z", + "updatedAt": "2021-06-24T22:05:45.321952Z", + "namespace": "food_delivery", + "inputs": [ + { + "namespace": "food_delivery", + "name": "public.delivery_7_days" + } + ], + "outputs": [], + "location": "https://github.com/example/jobs/blob/2294bc15eb49071f38425dc927e48655530a2f2e/delivery_times_7_days.py", + "context": { + "sql": "INSERT INTO top_delivery_times (order_id, order_placed_on, order_dispatched_on, order_delivered_on, order_delivery_time,\n customer_email, restaurant_id, driver_id)\n SELECT order_id, order_placed_on, order_delivered_on, DATEDIFF(minute, order_placed_on, order_delivered_on) AS order_delivery_time,\n customer_email, restaurant_id, driver_id\n FROM delivery_7_days\nGROUP BY restaurant_id\nORDER BY order_delivery_time DESC\n LIMIT 1;" + }, + "description": "Determine weekly top delivery times by restaurant.", + "latestRun": { + "id": "f4fada30-dfcc-400c-9391-2d7a506b9139", + "createdAt": "2021-06-24T21:50:59.509739Z", + "updatedAt": "2021-06-24T22:05:45.321952Z", + "nominalStartTime": "2021-06-24T22:02:00Z", + "nominalEndTime": "2021-06-24T22:05:00Z", + "state": "FAILED", + "startedAt": "2021-06-24T22:02:39.321952Z", + "endedAt": "2021-06-24T22:05:45.321952Z", + "durationMs": 186000, + "args": {}, + "jobVersion": { + "namespace": "food_delivery", + "name": "example.delivery_times_7_days", + "version": "e9eafa5b-e334-358d-a3b4-61c8d3de75f3" + }, + "inputVersions": [ + { + "namespace": "food_delivery", + "name": "public.delivery_7_days", + "version": "a40ec54f-b8e1-35f7-b868-58b27383b5ff" + } + ], + "outputVersions": [], + "context": { + "sql": "INSERT INTO top_delivery_times (order_id, order_placed_on, order_dispatched_on, order_delivered_on, order_delivery_time,\n customer_email, restaurant_id, driver_id)\n SELECT order_id, order_placed_on, order_delivered_on, DATEDIFF(minute, order_placed_on, order_delivered_on) AS order_delivery_time,\n customer_email, restaurant_id, driver_id\n FROM delivery_7_days\nGROUP BY restaurant_id\nORDER BY order_delivery_time DESC\n LIMIT 1;" + }, + "facets": {} + }, + "facets": {} + }, + ... + ] +} +``` +For brevity, I only included a single job- in this case, a job called `example.delivery_times_7_days` +in the `food_delivery` namespace (which we specified in the curl command). Your output will include +many more jobs. + +There are a few things in the job output worth noting. The first is the id of the job: + +```json + "id": { + "namespace": "food_delivery", + "name": "example.delivery_times_7_days" + }, +``` +There is no version information in the id, as this API refers to the unversioned job information. The +job itself is mutable, in the sense that each time you query the API, the content of the job may +change as new versions are created. + +The response includes the set of input and output datasets, as well as the current job source location: +```json + "inputs": [ + { + "namespace": "food_delivery", + "name": "public.delivery_7_days" + } + ], + "outputs": [], + "location": "https://github.com/example/jobs/blob/2294bc15eb49071f38425dc927e48655530a2f2e/delivery_times_7_days.py", +``` +If a new version of the job is created, any or all of these fields can change. + +### The Job Run +The next thing to notice is the `latestRun` field. This includes information about the latest Run +of this job: +```json + "latestRun": { + "id": "f4fada30-dfcc-400c-9391-2d7a506b9139", + "createdAt": "2021-06-24T21:50:59.509739Z", + "updatedAt": "2021-06-24T22:05:45.321952Z", + "nominalStartTime": "2021-06-24T22:02:00Z", + "nominalEndTime": "2021-06-24T22:05:00Z", + "state": "FAILED", + "startedAt": "2021-06-24T22:02:39.321952Z", + "endedAt": "2021-06-24T22:05:45.321952Z", + "durationMs": 186000, + "args": {}, + "jobVersion": { + "namespace": "food_delivery", + "name": "example.delivery_times_7_days", + "version": "e9eafa5b-e334-358d-a3b4-61c8d3de75f3" + }, + "inputVersions": [ + { + "namespace": "food_delivery", + "name": "public.delivery_7_days", + "version": "a40ec54f-b8e1-35f7-b868-58b27383b5ff" + } + ], + "outputVersions": [], + "context": { + "sql": "INSERT INTO top_delivery_times (order_id, order_placed_on, order_dispatched_on, order_delivered_on, order_delivery_time,\n customer_email, restaurant_id, driver_id)\n SELECT order_id, order_placed_on, order_delivered_on, DATEDIFF(minute, order_placed_on, order_delivered_on) AS order_delivery_time,\n customer_email, restaurant_id, driver_id\n FROM delivery_7_days\nGROUP BY restaurant_id\nORDER BY order_delivery_time DESC\n LIMIT 1;" + }, + "facets": {} + }, +``` +Here, we see explicit version information in the `jobVersion`, the `inputVersions`, and the +`outputVersions` fields. This is included because every Run is tied to exactly one immutable +version of a job and one immutable version of each input dataset and each output dataset (it's worth +noting that a Run can be tied to one version of a dataset as its input and another version of the +same dataset as its output- a SQL `MERGE` statement is one common use case supported by this). + +The other important field to notice in the Run structure is the `state` +```json + "state": "FAILED", +``` +Uh-oh. Looks like the last time this job ran, it failed. + +## Tracing Failures + +The first question we have when diagnosing a failure is + +> Is this the first time it's failed? Or has it been broken a while? + +Let's use the API to find out. Checking previous runs is easily accomplished by hitting the job's `runs` +API. Job runs are returned in descending order by start time, so the latest runs should be at the top. +Since we only want to check whether (and which) previous runs failed, we can use the following command: +```bash +curl "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/example.delivery_times_7_days/runs" | \ + jq '.runs | map({"id": .id, "state": .state})' | less +``` + +I get the following output: +```json +[ + { + "id": "cb436906-1c66-4ce4-b7ac-ceebfd1babf8", + "state": "FAILED" + }, + { + "id": "34bd4d60-82a6-4cac-ad76-815e6d95a93c", + "state": "COMPLETED" + }, + { + "id": "352c67c3-c8d7-4b3a-b7da-8532aa9b8335", + "state": "COMPLETED" + }, + { + "id": "0c62b1cc-2e43-44d0-9443-0a1d9768fece", + "state": "COMPLETED" + }, + { + "id": "5900de19-12f7-4a6e-8118-8e0792d98f65", + "state": "COMPLETED" + }, + ... +] +``` +This is an incomplete list of jobs, but it's obvious from this sampling that this is the first job failure +in the recent execution history. What we want to see now is what changed between the last successful +run and this one. We'll need to grab the `id` fields of each of the runs we want to compare. The run +ids in the seed data are randomly generated, so they'll be different if you're following along. Grab +the run ids with the following shell commands: +```bash +FAILED_RUN_ID=$(curl "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/example.delivery_times_7_days/runs" | jq -r '.runs[0].id') +SUCCESSFUL_RUN_ID=$(curl "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/example.delivery_times_7_days/runs" | jq -r '.runs[1].id') +``` +To get a specific run, we call the `/jobs/runs` API. Since each Run ID is required to be unique, the +API doesn't require a namespace or a job name. We can get the failed job run with +```bash +curl "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq | less +``` +The output is the same as the `latestRun` field of the `JobVersions` API. Recall the output of that +API includes these three important fields: the `jobVersion`, the `inputVersions` +and the `outputVersions`. +```json + "jobVersion": { + "namespace": "food_delivery", + "name": "example.delivery_times_7_days", + "version": "e9eafa5b-e334-358d-a3b4-61c8d3de75f3" + }, + "inputVersions": [ + { + "namespace": "food_delivery", + "name": "public.delivery_7_days", + "version": "a40ec54f-b8e1-35f7-b868-58b27383b5ff" + } + ], + "outputVersions": [], +``` +These fields give us what we need to trace the lineage of the specific job runs we want to compare. + +### Job Versions +The first thing to look at is the `jobVersion`. Nearly 100% of the time, a job failure can be traced +to a code change. Let's compare the job version of the failed run with the job version of the successful +one: +```bash +diff <(curl -s "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq -r '.jobVersion.version') \ + <(curl -s "http://localhost:5000/api/v1/jobs/runs/$SUCCESSFUL_RUN_ID" | jq -r '.jobVersion.version') +1c1 +< e9eafa5b-e334-358d-a3b4-61c8d3de75f3 +--- +> 92d801c0-021e-3c3d-ba18-c9e8504b143d +``` +Right away, we see there is a difference. A number of factors contribute to the job versioning logic +in Marquez: +* The source code location +* The job context +* The list of input datasets +* The list of output datasets + +The version generation code is a deterministic function of these four inputs, so if any of them change, +the version will change. Let's find out what changed between the two job versions. To do the diff, +we ought to get rid of anything we expect to differ ahead of time: the `version`, the `createdAt` +and `updatedAt` timestamps, and the `latestRun`. The `version` field is also nested within the job +version's `id` field, so we'll omit that too. +```bash +FAILED_JOB_VERSION=$(curl -s "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq -r '.jobVersion.version') +SUCCESSFUL_JOB_VERSION=$(curl -s "http://localhost:5000/api/v1/jobs/runs/$SUCCESSFUL_RUN_ID" | jq -r '.jobVersion.version') + +diff <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/example.delivery_times_7_days/versions/$FAILED_JOB_VERSION" | \ + jq 'del(.["id", "version", "createdAt", "updatedAt", "latestRun"])') \ + <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/jobs/example.delivery_times_7_days/versions/$SUCCESSFUL_JOB_VERSION" | \ + jq 'del(.["id", "version", "createdAt", "updatedAt", "latestRun"])') +14c14,23 +< "outputs": [] +--- +> "outputs": [ +> { +> "namespace": "food_delivery", +> "name": "public.top_delivery_times" +> }, +> { +> "namespace": "food_delivery", +> "name": "public.discounts" +> } +> ] +``` +Oh, interesting! The two job versions only differ because of the output datasets. This is an +interesting point that should be addressed in the Marquez API- the version generation is constructed +when the run completes, _even if the job run failed_. Sometimes this has no impact on the versioning, +as the output datasets can be determined before the job run executes. But sometimes we see impacts +like this where a job run failed before we had a chance to discover the output datasets. + +## Tracing Upstream Lineage + +So what gives? The job code didn't actually change! So what caused the failure? + +Here's where the lineage tracking becomes useful. Recall again, the run output gave us +3 interesting fields: the `jobVersion`, the `inputVersions`, and the `outputVersions`. +We already know that the `outputVersions` is empty because the latest failed run didn't have +a chance to determine the outputs. But we can take a look at the input datasets. + +### Dataset Versions +```bash +diff <(curl -s "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq -r '.inputVersions') \ + <(curl -s "http://localhost:5000/api/v1/jobs/runs/$SUCCESSFUL_RUN_ID" | jq -r '.inputVersions') +5c5 +< "version": "a40ec54f-b8e1-35f7-b868-58b27383b5ff" +--- +> "version": "5e439f1f-1a44-3700-961f-60c79c75a1ec" +``` + +Dataset versions work differently from job versions. They don't only change when the structure changes. +Every time a job run _modifies or writes to_ a dataset, the dataset version changes. Unless a job schedule is more +frequent than its upstream job's schedule (e.g., an hourly job consuming a daily generated dataset), +it is expected that each job run consumes a different version of a dataset. To find out if there is +a significant difference, we have to compare the two versions with the dataset's `versions` API. + +We know there's only a single input dataset, so we'll keep this simple, but you could also write a loop to +check multiple input datasets if needed. + +In this post, we omit the structure of the `datasetVersion`, but you can explore it yourself with the following: +```bash +FAILED_DATASET_VERSION=$(curl -s "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq -r '.inputVersions[0].version') +curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$FAILED_DATASET_VERSION" | jq | less +``` + +As with the job versions, we'll omit some of the data we expect to be different in order to produce +a useful diff: + +```bash +FAILED_DATASET_VERSION=$(curl -s "http://localhost:5000/api/v1/jobs/runs/$FAILED_RUN_ID" | jq -r '.inputVersions[0].version') +SUCCESSFUL_DATASET_VERSION=$(curl -s "http://localhost:5000/api/v1/jobs/runs/$SUCCESSFUL_RUN_ID" | jq -r '.inputVersions[0].version') + +diff <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$FAILED_DATASET_VERSION" | \ + jq 'del(.["id", "version", "createdAt", "createdByRun"])') \ + <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$SUCCESSFUL_DATASET_VERSION" | \ + jq 'del(.["id", "version", "createdAt", "createdByRun"])') +58c58 +< "type": "VARCHAR", +--- +> "type": "INTEGER", +``` + +Hey! Somehow one of the fields was converted from a an `INT` to a `VARCHAR`! One of the helpful fields +in the `version` API is the `createdByRun`, which is similar to the `jobVersion`'s `latestRun`. +It provides the job run that last altered the dataset, creating the new version. + +We can quickly compare the job versions of the runs that created these two dataset versions: + +```bash +diff <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$FAILED_DATASET_VERSION" | \ + jq '.createdByRun.jobVersion') \ + <(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$SUCCESSFUL_DATASET_VERSION" | \ + jq '.createdByRun.jobVersion') +4c4 +< "version": "c222a72e-92cc-3bb6-b3b7-c174cbc76387" +--- +> "version": "76c375bf-58ac-3d19-b94f-424fe2784601" +``` + +And we can do a quick comparison of the two job versions. Since the job name is different, +we'll let jq generate the endpoints for us + +```bash +diff <(curl -s $(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$FAILED_DATASET_VERSION" | \ + jq -r '.createdByRun.jobVersion | "http://localhost:5000/api/v1/namespaces/" + .namespace + "/jobs/" + .name + "/versions/" + .version') | \ + jq 'del(.["id", "version", "createdAt", "updatedAt", "latestRun"])') \ + <(curl -s $(curl -s "http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.delivery_7_days/versions/$SUCCESSFUL_DATASET_VERSION" | \ + jq -r '.createdByRun.jobVersion | "http://localhost:5000/api/v1/namespaces/" + .namespace + "/jobs/" + .name + "/versions/" + .version') | \ + jq 'del(.["id", "version", "createdAt", "updatedAt", "latestRun"])') +4c4 +< "location": "https://github.com/example/jobs/blob/c87f2a40553cfa4ae7178083a068bf1d0c6ca3a8/etl_delivery_7_days.py", +--- +> "location": "https://github.com/example/jobs/blob/4d0b5d374261fdaf60a1fc588dd8f0d124b0e87f/etl_delivery_7_days.py", +``` +And there it is. Because nearly 100% of the time, a job failure can be traced to a code change. In +this example, the job immediately upstream decided to change the output schema of its dataset. In +reality, it's not always so straightforward. Sometimes the upstream job is just a passthrough- maybe +it applies some filters to a subset of the columns and writes out whatever schema it's given. +In that case, the job immediately upstream would have succeeded without a change in the job version. +Or the code change in the upstream job could be innocuous. Maybe someone added a comment or fixed an +unrelated bug. We might do some follow up and discover we have to continue our search upstream. + +But the Marquez API actually gives us that ability. Using the `/lineage` API, we can even explore the +downsteam impact of changes. So if you owned the `etl_delivery_7_days` job and wanted to see what the +impact of changing the varchar to an int was on running jobs, the following jq recursive script +will let you walk the downstream jobs and show the state of the last run: +```bash +# For readability, the jq filter is in a file broken into multiple lines +cat recurse.jq + .graph as $graph | .graph[] + | select(.id == "job:food_delivery:example.etl_delivery_7_days") + | recurse(.outEdges[] | .destination as $nodeId | $graph[] | select(.id == $nodeId)) + | select(.type == "JOB") + | {"id": .id, "state": .data.latestRun.state} + +curl -s "http://localhost:5000/api/v1-beta/lineage?nodeId=job:food_delivery:example.etl_delivery_7_days" | jq -f recurse.jq less +{ + "id": "job:food_delivery:example.etl_delivery_7_days", + "state": "COMPLETED" +} +{ + "id": "job:food_delivery:example.delivery_times_7_days", + "state": "FAILED" +} +``` +In this post, we did everything manually with bash (because the shell is your most powerful tool when +debugging a live outage you've never encountered before; and let's be honest- how many outages _aren't_ +something you've never encountered before), but this could easily have been done in Java or Go or Python. +The [openapi spec](https://github.com/MarquezProject/marquez/blob/main/spec/openapi.yml) +in the Marquez repo can be used to generate a client in whatever language you want to write your ops +tool in. So build some tooling and help your next debugging session run a little more smoothly. + +> But wait! What about the times when the job isn't _failing_, but the data is wrong! + +Ah, the data quality checks! This is where the extensibility of the OpenLineage model comes to our +rescue with a field in the responses that we completely glossed over +```json + "facets": {} +``` +But I think that's a topic for another post. diff --git a/blog/extending-with-facets/banner.svg b/blog/extending-with-facets/banner.svg new file mode 100644 index 0000000000..6a0eb2549f --- /dev/null +++ b/blog/extending-with-facets/banner.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/extending-with-facets/image.svg b/blog/extending-with-facets/image.svg new file mode 100644 index 0000000000..07a396cb74 --- /dev/null +++ b/blog/extending-with-facets/image.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/extending-with-facets/index.mdx b/blog/extending-with-facets/index.mdx new file mode 100644 index 0000000000..ebdd499d35 --- /dev/null +++ b/blog/extending-with-facets/index.mdx @@ -0,0 +1,85 @@ +--- +title: Extending OpenLineage with Facets +date: 2021-07-27 +author: Julien Le Dem +image: ./image.svg +banner: ./banner.svg +description: Facets are a self-contained definition of one aspect of a job, dataset, or run at the time the event happened. They make the OpenLineage model extensible. +--- +Facets are a self-contained definition of one aspect of a job, dataset, or run at the time the event happened. They make the OpenLineage model extensible. + +![](./banner.svg#full-width) + + + +# Building consensus + +OpenLineage is an open source project, part of the LFAI&Data foundation, that standardizes lineage collection in the data ecosystem. In this increasingly rich ecosystem - that includes SQL-driven data warehouses, programmatic data processing frameworks like Spark or Pandas, and machine learning - it is near-impossible to maintain a clear and sane view of data lineage across everything without the collaboration of the ecosystem around a shared standard. Open source collaboration is a very powerful mechanism that can produce widely-adopted standard APIs. + +[OpenLineage draws a clear parallel with OpenTelemetry](https://openlineage.io/blog/openlineage-takes-inspiration-from-opentelemetry/) which provides a standard API to collect traces and metrics in the service world. It also draws from the experience of the Apache Parquet and Apache Arrow projects, which aim to define standard columnar data representations at-rest and in-memory. + +## Open Source +Standardizing an API through open source collaboration can be challenging. On one end, you need to get input and feedback from the people who will use the API in different contexts. On the other, you want to avoid getting stuck in disagreements arising from the different and sometimes incompatible viewpoints that inevitably drive these discussions. Thankfully, there are mechanisms to help organize and decouple those disagreements and drive discussions towards conclusion. + +A community driven open source project works very differently from a product you buy off the shelf. At the very moment you start using it - maybe starting by reading the doc - you become part of the community and start sharing a little bit of ownership. As with any software, you might encounter problems... but in this case, you immediately become part of the solution. In a healthy community, how much of the solution you become is entirely up to you. + +Maybe you spotted a typo and reported it. Maybe you opened a pull request to fix it. You might propose an improvement, or even build one yourself. All of those contributions, no matter how small, make the project better for everyone. That very powerful flywheel motion gathers momentum and drives very successful open source projects. + +One of the success factors of such an open source project is how much it can minimize the friction for new community members who want to contribute. The easier it is to contribute, the faster the project will acquire momentum. It’s not about getting other people’s input, it’s about giving them a share of ownership and encouraging them to drive the areas where they can most effectively contribute. + +In a multi-faceted domain like data lineage, enabling others to lead discussions is critical. + +## Making progress +In this context, we need mechanisms to converge often and make incremental progress. + +You definitely want to avoid having a big monolithic spec that takes a long time to reach consensus on - if you ever do. A discussion around a large ultra-spec that combines specifications from multiple related domains will lose steam. We need to keep conversations focused on the topics that individual contributors care about. It is critical to subdivide the specification in concrete and granular decision points where consistent and significant progress can be made. + +Not everyone will care about all the aspects of the specification, and that is fine. We need to make sure contributors can easily focus on the aspects they do care about. This need for a very granular decision making process, one where we can make progress independently on different aspects of the spec, leads naturally into decomposition of the specification into smaller independent subsets. + +This will keep conversations focused and moving. It also decouples workstreams where consensus can be reached from those that are more contentious. + +For example the contributors interested in data quality might be different from the ones interested in column-level lineage or query performance. + +## Embracing different points of view +Depending on their perspective, contributors may have very different opinions on how to model a certain aspect of data. Or they may have different use-cases in mind. Instead of pitting different view-points against each other and forcing alignment on every point, it is sometimes beneficial to allow them to be expressed separately. + +For example, when you ask a data practitioner "what is data lineage?" they may have very different definitions for it. +- Some care about how a specific metric is derived from the raw data, and need column level lineage. +- Some will care about compliance with privacy regulations and need relevant metadata to locate sensitive data and trace its movement. +- Some will care about the reliability of data delivery and need data freshness and quality metrics - in particular, how they change over time in correlation with changes in the system. + +All those are valid view points that deserve to be captured appropriately and can be defined independently in a framework that allows them to cohabitate. + +# Mechanics + +OpenLineage is purposefully providing a faceted model around a minimalistic core spec to enable this granular decision making, minimize friction in contributing, and favor community-driven improvements. + +The core spec focuses on high-level modeling of jobs, runs, datasets, and their relation. Each OpenLineage event refers to a run of a job and its input and output datasets. +- A job is a recurring transformation that reads from datasets and writes to datasets. It has a unique name that identifies it across runs. +- A run identifies an individual execution of a job. It might be an incremental or full batch process. It could also be a streaming job. +- A dataset could be a table in a warehouse or a folder in a blob store. It is consumed or written to by jobs. + +**Facets** are pieces of metadata that can be attached to those core entities. Facets have their own schema and capture various aspects of those entities. + +## Facets are individual atomic specs +Like the core model, facets are defined by a `JSONSchema`. They are a self-contained definition of one aspect of a job, a dataset, or a run at the time the event happened. They make the model extensible. The notion of facets is powerful because it makes it easy to add more information to the model - you just define a new facet. There’s a clear compatibility model when introducing a new facet, since fields that are defined at the same time are grouped together. + +For example, there’s a facet to capture the schema of a dataset. There’s a facet to capture the version of a job in source control. There’s a facet to capture the parameters of a run. Facets are optional and may not apply to every instance of an entity. + +## Facets enable specialization of models +The core entities are fairly generic. A dataset might be a table in a warehouse or a topic in a Kafka broker. A job might be a SQL query or a machine learning training job. + +This generic high level model of lineage can be specialized by adding facets for that particular type of entity. At-rest data might be versioned, enabling transactions at the run level. Streaming data might capture the offsets and partitions where a streaming job started reading. Datasets might have a schema like a warehouse table, or not (for example, in the case of a machine learning model). + +By capturing a generic representation of lineage and allowing progressive specialization of those entities, this approach offers a lot of flexibility. + +## Facets allow expressing different point of views +There can be divergent points of view on how to model a certain aspect of metadata. Facets allow these models to cohabitate in a common framework. + +One example of this is capturing the physical plan of a query execution. Each data warehouse might have its own unique way of describing execution plans. It is very valuable to be able to capture both a precise (but maybe too specific) model as well as a generic (but possibly imprecise or lossy) representation. They can be captured as two different facets. This also gives us opportunities to define several competing models and use the resulting information to collaborate on a more unified and generic representation. This emergent modeling is actually extremely useful in an open source setting, and as a way to make incremental progress. + +## Custom facets make the model decentralized +Most importantly, the OpenLineage spec allows custom facets that are defined elsewhere, completely outside of the spec. This allows others to extend the spec as-needed without having to coordinate with anyone or ask any permission from a governing body. They can make their own opinionated definition of an aspect of metadata. All that is required is that they publish a `JSONSchema` that describes their facets, prefixed by a unique namespace. This lowers the barrier to experimentation and encourages incremental progress by making the experimentation of others visible. The facets that become broadly useful can eventually be represented in the core spec. + +# Contribute! +As a community, we’ve done our best to minimize friction when experimenting with or contributing to OpenLineage. We’re looking forward to seeing you join us as we make data lineage transparent across the data ecosystem. diff --git a/blog/extractors/banner.svg b/blog/extractors/banner.svg new file mode 100644 index 0000000000..decaa7a717 --- /dev/null +++ b/blog/extractors/banner.svg @@ -0,0 +1,36 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/extractors/image.svg b/blog/extractors/image.svg new file mode 100644 index 0000000000..5b0cd9ee89 --- /dev/null +++ b/blog/extractors/image.svg @@ -0,0 +1,27 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/extractors/index.mdx b/blog/extractors/index.mdx new file mode 100644 index 0000000000..e85644e81c --- /dev/null +++ b/blog/extractors/index.mdx @@ -0,0 +1,134 @@ +--- +title: Pursuing Lineage from Airflow using Custom Extractors +date: 2022-09-08 +author: Maciej Obuchowski & Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: Built-in support for custom extractors makes OpenLineage a highly adaptable solution for pipelines that use Airflow. +--- +Built-in support for custom extractors makes OpenLineage a highly adaptable solution for pipelines that use Airflow. + +![](./banner.svg#full-width) + + + +### Overview + +Airflow is built around operators, each having a different function and requiring a different approach to lineage. The OpenLineage Airflow integration detects which Airflow operators your DAG is using and extracts lineage data from them using extractors. + +The community has already authored a number of extractors to support Airflow’s Great Expectations, BigQuery, Python, Postgres, SQL and Bash operators (and more – you can find all the extractors [here](https://github.com/OpenLineage/OpenLineage/tree/main/integration/airflow/openlineage/airflow/extractors).) Nevertheless, in the course of pursuing lineage, you may find yourself needing to write custom extractors. + +Some teams use custom extractors to automate repeatable work – using the same code from `PythonOperator` across a project, for example. Another common use case is that a team needs to use an operator for which a pre-built extractor does not yet exist. Airflow has literally hundreds of operators. + +Built-in support for custom extractors makes OpenLineage a flexible, highly adaptable solution for pipelines that use Airflow for orchestration. + +### How it works + +As we explain in the OpenLineage [docs](https://openlineage.io/docs/integrations/airflow/extractor), custom extractors must be derived from the `BaseExtractor` class (import it from `openlineage.airflow.extractors.base`). + +Extractors have methods they can implement: `extract`, `extract_on_complete` and `get_operator_classnames`. Either `extract` or `extract_on_complete` is required. The `get_operator_classnames` method, also required, is for providing a list of operators from which your extractor can get lineage. + +For example: + +``` +@classmethod +def get_operator_classnames(cls) -> List[str]: + return ['PostgresOperator'] +``` + +If the name of the operator matches one of the names on the list, the extractor will be instantiated – using the operator passed to the extractor as a parameter and stored in the `self.operator` property – and both the `extract` and `extract_on_complete` methods will be called. They both return information used by the OpenLineage integration to emit OpenLineage events. The difference is that `extract` is called before the operator's `execute` method to generate a `START` event, while `extract_on_complete` is called afterward to generate a `COMPLETE` event. The latter has access to any additional information that the operator leaves behind following execution. A good example of this is the `SnowflakeOperator`, which sets `query_id`s after execution. + +Both methods return a `TaskMetadata` structure: + +``` +@attr.s +class TaskMetadata: + name: str = attr.ib() # deprecated + inputs: List[Dataset] = attr.ib(factory=list) + outputs: List[Dataset] = attr.ib(factory=list) + run_facets: Dict[str, BaseFacet] = attr.ib(factory=dict) + job_facets: Dict[str, BaseFacet] = attr.ib(factory=dict) +``` + +The inputs and outputs are lists of plain [OpenLineage datasets](https://openlineage.io/docs/client/python). + +The `run_facets` and `job_facets` are dictionaries of optional [`JobFacets`](https://openlineage.io/docs/client/python) and [`RunFacets`](https://openlineage.io/docs/client/python) that accompany a job. For example, you might want to attach a `SqlJobFacet` if your operator is executing SQL. + +Note: in order for a custom extractor to work, it must be registered first, so the OpenLineage integration can import it. You can read about how to use environment variables to do this [here](https://openlineage.io/docs/integrations/airflow/extractor#registering-custom-extractor). + +### Example: the RedshiftDataExtractor + +In the `RedshiftDataExtractor`, the `extract_on_complete` method parses SQL, obtains task `stats` using the `get_facets` method of the `RedshiftDataDatasetsProvider` class, and returns a `TaskMetadata` instance. We can see usage of a SQL statement, and the connection is provided by an actual operator. + +``` +def extract_on_complete(self, task_instance) -> Optional[TaskMetadata]: + log.debug(f"extract_on_complete({task_instance})") + job_facets = {"sql": SqlJobFacet(self.operator.sql)} + + log.debug(f"Sending SQL to parser: {self.operator.sql}") + sql_meta: Optional[SqlMeta] = parse(self.operator.sql, self.default_schema) + log.debug(f"Got meta {sql_meta}") + try: + redshift_job_id = self._get_xcom_redshift_job_id(task_instance) + if redshift_job_id is None: + raise Exception( + "Xcom could not resolve Redshift job id. Job may have failed." + ) + except Exception as e: + log.error(f"Cannot retrieve job details from {e}", exc_info=True) + return TaskMetadata( + name=get_job_name(task=self.operator), + run_facets={}, + job_facets=job_facets, + ) + + client = self.operator.hook.conn + + redshift_details = [ + "database", + "cluster_identifier", + "db_user", + "secret_arn", + "region", + ] + + connection_details = { + detail: getattr(self.operator, detail) for detail in redshift_details + } + + stats = RedshiftDataDatasetsProvider( + client=client, connection_details=connection_details + ).get_facets( + job_id=redshift_job_id, + inputs=sql_meta.in_tables if sql_meta else [], + outputs=sql_meta.out_tables if sql_meta else [], + ) + + return TaskMetadata( + name=get_job_name(task=self.operator), + inputs=[ds.to_openlineage_dataset() for ds in stats.inputs], + outputs=[ds.to_openlineage_dataset() for ds in stats.output], + run_facets=stats.run_facets, + job_facets={"sql": SqlJobFacet(self.operator.sql)}, + ) +``` + +### Common issues + +There are two common issues associated with custom extractors. + +First, when the wrong path is provided to `OPENLINEAGE_EXTRACTORS`, the extractor isn’t imported and OpenLineage events aren’t emitted. The path needs to be exactly the same as the one you are using in your code. Also, make sure that the extractor code is available to import from Airflow’s Python interpreter. + +Second, imports from Airflow can be unnoticeably cyclical. This is due to the fact that OpenLineage code gets instantiated when the Airflow worker itself starts, in contrast to DAG code. OpenLineage extraction can fail as a result. To avoid this issue, make sure that all imports from Airflow are local – in the `extract` or `extract_on_complete` methods. If you need imports for type checking, guard them behind `typing.TYPE_CHECKING`. + +### How to get started + +Check out the existing extractors [here](https://github.com/OpenLineage/OpenLineage/tree/main/integration/airflow/openlineage/airflow/extractors). + +Read the docs about the Airflow integration, including tips on registering and debugging your custom extractor, [here](https://openlineage.io/docs/integrations/airflow/). + +### How to contribute + +We welcome your contributions! One of our existing [integrations](https://github.com/OpenLineage/OpenLineage/tree/main/integration) might be a good place to start. OpenLineage’s growing list of partners includes Airflow, dbt, Dagster and Flink. + +Sounds fun? Check out our [new contributor guide](https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md) to get started. diff --git a/blog/incubation-stage-lfai/banner.svg b/blog/incubation-stage-lfai/banner.svg new file mode 100644 index 0000000000..cef5c526be --- /dev/null +++ b/blog/incubation-stage-lfai/banner.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/incubation-stage-lfai/image.svg b/blog/incubation-stage-lfai/image.svg new file mode 100644 index 0000000000..86807f1399 --- /dev/null +++ b/blog/incubation-stage-lfai/image.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/incubation-stage-lfai/index.mdx b/blog/incubation-stage-lfai/index.mdx new file mode 100644 index 0000000000..19eed3acbe --- /dev/null +++ b/blog/incubation-stage-lfai/index.mdx @@ -0,0 +1,29 @@ +--- +title: OpenLineage Advances to Incubation Stage with the LFAI & Data +date: 2023-01-17 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: OpenLineage has achieved Incubation status with the LFAI & Data. +--- +OpenLineage has achieved Incubation status with the LFAI & Data. + +![](./banner.svg#full-width) + + + +At the December meeting of the LFAI & Data Foundation TAC, members voted to advance OpenLineage to the Incubation stage of their program! This required us to earn a Silver Badge from the [OpenSSF](https://bestpractices.coreinfrastructure.org/en), get 300+ stars on GitHub (we have over 1100), and make an in-depth presentation about the project and our community to the TAC. + +### What It Means + +Now that we’ve cleared this hurdle, we have access to additional services from the foundation, including assistance with creative work, marketing and communication support, and event-planning assistance. Graduation from the program, which will earn us a voting seat on the TAC, is on the horizon. Stay tuned for updates on our progress with the foundation. + +### About the LFAI & Data + +LF AI & Data is an umbrella foundation of the Linux Foundation that supports open source innovation in artificial intelligence (AI) and data. LF AI & Data was created to support open source AI and data, and to create a sustainable open source AI and data ecosystem that makes it easy to create AI and data products and services using open source technologies. They foster collaboration under a neutral environment with an open governance in support of the harmonization and acceleration of open source technical projects. + +For more info about the foundation and other LFAI & Data projects, visit their [website](https://lfaidata.foundation/). + +### What's Next + +The next step for the project is Graduation, which we expect to happen early this summer. Requirements for Graduation include 1000 stars on GitHub and the OpenSSF Gold Badge. Watch this space for updates on our progress. \ No newline at end of file diff --git a/blog/joining-lfai/banner.svg b/blog/joining-lfai/banner.svg new file mode 100644 index 0000000000..1410e89413 --- /dev/null +++ b/blog/joining-lfai/banner.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/joining-lfai/image.svg b/blog/joining-lfai/image.svg new file mode 100644 index 0000000000..76ac743af2 --- /dev/null +++ b/blog/joining-lfai/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/joining-lfai/index.mdx b/blog/joining-lfai/index.mdx new file mode 100644 index 0000000000..25854d4e42 --- /dev/null +++ b/blog/joining-lfai/index.mdx @@ -0,0 +1,22 @@ +--- +title: OpenLineage joins the LF AI & Data Foundation +date: 2021-07-22 +author: Julien Le Dem +image: ./image.svg +banner: ./banner.svg +description: Becoming a LF AI & Data project ensures that OpenLineage can never belong to a company, or even a group of developers; it belongs to us all. +--- +Becoming a LF AI & Data project ensures that OpenLineage can never belong to a company, or even a group of developers; it belongs to us all. + +![](./banner.svg#full-width) + + + +I am pleased to share that the OpenLineage project is joining the [LF AI & Data foundation](https://lfaidata.foundation) as a Sandbox Project! This is an important step towards the development of an open ecosystem for lineage metadata collection. + +The LF AI & Data Foundation provides a vendor-neutral governance structure that can help the project grow broad industry collaboration. Even more importantly, becoming a LF AI & Data project ensures that OpenLineage can never belong to a company, or even a group of developers; it belongs to us all. The license can’t be changed to protect the business interests of a subset of the community. That’s important, because in order to succeed we need a whole lot of software projects - open source and proprietary - to adopt this standard and allow their users to begin collecting lineage metadata. + +In the [full announcement](https://lfaidata.foundation/blog/2021/07/22/openlineage-joins-lf-ai-data-as-new-sandbox-project/), Ibrahim Haddad, Executive Director of LF AI & Data, writes: + +> “We look forward to working with the OpenLineage project to grow the project’s footprint in the ecosystem, expand its community of adopters and contributors, and to foster the creation of collaboration opportunities with our members and other related projects.” + diff --git a/blog/manta-integration/banner.svg b/blog/manta-integration/banner.svg new file mode 100644 index 0000000000..a4ed6cf892 --- /dev/null +++ b/blog/manta-integration/banner.svg @@ -0,0 +1,35 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/manta-integration/image.svg b/blog/manta-integration/image.svg new file mode 100644 index 0000000000..fe95e20435 --- /dev/null +++ b/blog/manta-integration/image.svg @@ -0,0 +1,43 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/manta-integration/index.mdx b/blog/manta-integration/index.mdx new file mode 100644 index 0000000000..f5cf9c14d6 --- /dev/null +++ b/blog/manta-integration/index.mdx @@ -0,0 +1,25 @@ +--- +title: At MANTA, OpenLineage Opens Doors to New Insights +date: 2022-10-31 +author: Ernie Ostic, SVP of Product at MANTA +image: ./image.svg +banner: ./banner.svg +description: Adopting OpenLineage as part of our portfolio allows MANTA to bring detailed run-time lineage to our customers. +--- +Adopting OpenLineage as part of our portfolio allows MANTA to bring detailed run-time lineage to our customers. + +![](./banner.svg#full-width) + + + +Here at [MANTA](https://getmanta.com/?utm_source=partner&utm_medium=referral&utm_campaign=OpenLineage), we are very excited to be working closely with [OpenLineage](https://openlineage.io/) and, more importantly, with the OpenLineage Community. As a leader in lineage analysis, we see first-hand the complexity required to achieve effective lineage, and the benefits of having an accepted standard for the sharing of operational lineage metadata. OpenLineage moves everything in the direction of enhanced interoperability, and helps to ensure that enterprises have maximum flexibility for current and future tool selection. + +Adopting OpenLineage as part of our portfolio allows MANTA to bring detailed run-time lineage to our customers, many of whom are enterprise organizations and need this level of granularity. This is especially important for new technologies such as [Apache Airflow](https://airflow.apache.org/), whose integration with OpenLineage continues to evolve. Apache Airflow, as an example, is increasingly being utilized by our customers as part of their process orchestration portfolio; as such, these companies need lineage coverage for these operations. + +Having a recognized industry standard for lineage capture and reporting is an enabler for enhanced metadata management and governance. OpenLineage helps to ensure increased consistency in pipeline analysis, especially as more and more solutions appear in the Cloud, and in the general marketplace, for the transformation, enrichment, and overall movement of information through new and future dataflows. Vendors like MANTA will continue to offer creative and purposeful solutions that answer key questions and meet the end-to-end requirements of the business. For selected technologies, OpenLineage enables us to do this faster and simpler. + +Eighteen months ago, we started our investigation into OpenLineage. After working with various customers earlier this year, we decided to double down on our investment and get more involved with the OpenLineage Community. Throughout our journey, we’ve found this growing community to be welcoming, helpful, and collaborative. MANTA is pleased to contribute however we can to this important open source project. Are you ready to join? + +For more information about MANTA's data lineage solution, visit [our website](https://getmanta.com/?utm_source=partner&utm_medium=referral&utm_campaign=OpenLineage). + +To learn more about contributing to OpenLineage, check out the project's [new contributor guide](https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md). diff --git a/blog/openlineage-at-northwestern-mutual/banner.svg b/blog/openlineage-at-northwestern-mutual/banner.svg new file mode 100644 index 0000000000..62df33d249 --- /dev/null +++ b/blog/openlineage-at-northwestern-mutual/banner.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-at-northwestern-mutual/image.svg b/blog/openlineage-at-northwestern-mutual/image.svg new file mode 100644 index 0000000000..e6191909fa --- /dev/null +++ b/blog/openlineage-at-northwestern-mutual/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-at-northwestern-mutual/index.mdx b/blog/openlineage-at-northwestern-mutual/index.mdx new file mode 100644 index 0000000000..a7b0fe7a96 --- /dev/null +++ b/blog/openlineage-at-northwestern-mutual/index.mdx @@ -0,0 +1,71 @@ +--- +title: How Northwestern Mutual Simplified Data Observability with OpenLineage & Marquez +date: 2021-10-22 +author: Kevin Mellott +image: ./image.svg +banner: ./banner.svg +description: Northwestern Mutual is building an Enterprise Data Platform. In this guest blog, learn about the experiences and decisions that led them to embrace the OpenLineage and Marquez communities. +--- +Northwestern Mutual is building an Enterprise Data Platform. In this guest blog, learn about the experiences and decisions that led them to embrace the OpenLineage and Marquez communities. + +![](./banner.svg#full-width) + + + +I joined Northwestern Mutual last year to oversee the implementation and delivery of their Enterprise Data Platform (Unified Data Platform). With over 160 years of history, Northwestern Mutual has been serving our clients with insurance and investment products, as well as financial planning, advisory and consultation services. It goes without saying that the company has accumulated a vast amount of data over this time. Our team’s objective is to empower data analysts, data scientists, and data engineers with the platform capabilities they need to derive insights and garner value from many disparate data sources. + +# Ready...Set...Go! + +So, where do you start? The industry has taught us a lot over the past 10+ years - *remember when on-premises Hadoop clusters were all the rage*? When revisiting the approach we took within our Data Platform Engineering teams, I see a lot of alignment to the [Data Engineering Manifesto](https://connectingdots.xyz/blog/posts/2021/05/the-data-engineering-manifesto/). A few principles really jump out: + +### Embrace cloud managed services + +Many of the foundational needs of an Enterprise Data Platform can be accomplished using a cloud-first mindset. While we may not all agree which cloud provider is best, we can all agree that the level of scale and sophistication accomplished around things like storage, compute, and redundancy are going to be MUCH greater when relying on a cloud provider than when rolling your own solution. + +### We are software engineers + +The Data Mesh evolution has reminded the industry that centralized data teams do not scale or empower anybody. With this principle in mind, our platform teams embraced full automation from the beginning and designed for self-service workflows. We do not want to become the bottleneck to insights; rather, we want to enable data owners to manage and share their datasets throughout the company. We want to empower data engineers with transformation and machine learning capabilities, so that they can author pipelines and deliver insights. + +### Aim for simplicity through consistency + +Traditionally, data platforms have gathered and constructed technical metadata based on events of the past. For example, there are many crawlers that will examine various database systems and build a catalog to make those datasets “discoverable.” Logs from various jobs can be parsed in *extremely specific ways* to identify datasets consumed and produced by a given pipeline to infer data lineage. + +We viewed these traditional methods as a massive impediment to activating DataOps, due to differing technology solutions and the historical-based approach of their designs. Our platform aimed to achieve dynamic decisions based on what *is* happening *as it is* happening. + +We also recognize and appreciate the complexity of this portion of the platform and did not find it wise to build from the ground up. Especially with the industry momentum towards real-time data observability, why add another custom solution to the stack? With such an evolving technical landscape, it was important for us to avoid vendor lock to allow us flexibility in future decisions. + +# NM hearts OL + +When we first learned of the OpenLineage specification, we were very intrigued and hopeful. An open specification focused on observing real-time events AND unifying tools and frameworks?!? Fast forward nine months, and we cannot believe how much capability we have developed around data observability in such a brief time. Let me back up a little... + +Marquez is a metadata management framework that implements the OpenLineage specification. It transforms your data runtime events into a searchable catalog of technical metadata. It was a perfect fit to the skills of our Platform Data Engineers - it is written in Java, runs in Kubernetes, and integrates well with our backend services via web-based APIs. + +We were able to quickly deploy this framework into our own environment, which provided us with several immediate wins. + +### Flexible framework + +Since it is aligned with the OpenLineage framework, Marquez can process messages from ANY data producer that is publishing compliant events. The Marquez and OpenLineage communities have been doing an excellent job maturing the [integration library](/integration/), which allows you to tackle this challenge at the infrastructure level. This is the ultimate easy button approach and our own ideal state; configure an environment on behalf of your user base and sit back while it automatically detects and logs the activity within! + +In the cases when an integration either does not exist or you need to address a more custom workflow, you can construct and emit your own OpenLineage event messages. Marquez will still be able to process and store custom OpenLineage events, provided they meet the requirements of the open standard. + +For example, our teams have been able to programmatically construct OpenLineage messages within code that pulls data from various on-premises database servers and publishes it into our Data Platform. Using the OpenLineage specification, we extract the actual table schema from the source system as part of the `Dataset` entity and log the executing SQL query as part of the `Job` entity. This code was simplistic and allowed us to meet our immediate needs around observing data movement and recording those event details. + +### Alignment with enterprise + +Marquez already supported Kubernetes when we got involved, which provided us with many different deployment options. Our first contributions to the project were made to mature the [Helm chart](https://github.com/MarquezProject/marquez/tree/main/chart) and to enhance security around the base images and Kubernetes secrets usage. + +These changes allowed us to fully automate our deployments using GitOps and incorporate internal security measures involving container vulnerability management. + +The flexibility offered by the Marquez deployment architecture and our ability to customize its details allowed us to activate new production use cases in about a month. We were happy with this timeline, given the series of security checkpoints that were validated and the wealth of functionality we had just unlocked. + +### Collaborative working group + +Both the Marquez and OpenLineage communities have been extremely welcoming, and that has been a huge factor in our success at Northwestern Mutual. Our feedback and ideas have been encouraged and heard, which is evidenced by evolving project roadmaps and accepted developer contributions. + +We have learned quite a bit from the community members and feel fortunate to be a part of this group. Monthly community meetings are informative yet have an amazingly informal feel to them. + +# Where are we headed? + +The Unified Data Platform at Northwestern Mutual relies on the OpenLineage standard to formulate technical metadata within our various platform services. Publishing these events into Marquez has provided us with an effortless way to understand our running jobs. We can easily trace a downstream dataset to the job that produced it, as well as examine individual runs of that job or any preceding ones. + +Gaining the ability to observe lineage throughout our platform has been huge, and we are just getting started. Our teams are working to apply standard OpenLineage integrations into our environment and introduce data quality facets into our events. We have also been establishing operational workflows using job run information, to allow our DataOps team to monitor durations and measure against SLAs. diff --git a/blog/openlineage-egeria/banner.svg b/blog/openlineage-egeria/banner.svg new file mode 100644 index 0000000000..4546470290 --- /dev/null +++ b/blog/openlineage-egeria/banner.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-egeria/image.svg b/blog/openlineage-egeria/image.svg new file mode 100644 index 0000000000..3bc58d83b5 --- /dev/null +++ b/blog/openlineage-egeria/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-egeria/index.mdx b/blog/openlineage-egeria/index.mdx new file mode 100644 index 0000000000..68eae5d2a6 --- /dev/null +++ b/blog/openlineage-egeria/index.mdx @@ -0,0 +1,36 @@ +--- +title: OpenLineage Support in Egeria +date: 2022-04-25 +author: Mandy Chessel +image: ./image.svg +banner: ./banner.svg +description: The Egeria project uses OpenLineage to enhance its production of holistic metadata about an organization's operations. +--- +The Egeria project uses OpenLineage to enhance its production of holistic metadata about an organization's operations. + +![](./banner.svg#full-width) + + + +## OpenLineage Support in Egeria + +[Egeria](https://egeria-project.org) is a sister open source project to OpenLineage in the LF AI and Data Foundation. Egeria provides Open Metadata and Governance standard types and integration technology to exchange metadata between different technologies. It stitches together different standards to create a complete landscape of metadata about an organization’s digital operations. + +OpenLineage is very welcome to the Egeria team since it defines a standard for dynamic lineage capture. This means Egeria can capture open lineage events to detect new assets and activity around them, link this new knowledge into the existing metadata and distribute it to the open metadata ecosystem. + +Egeria also executes governance processes for maintaining both metadata and the data sources it describes. Since it is running processes, it also makes sense that Egeria produces open lineage for its processes. + +The diagram below is a big animal picture showing the different features relating to open lineage that Egeria offers. With Egeria’s plug-and-play architecture you can pick and choose which pieces you need. + +![Egeria architecture](./open-lineage-blog.svg) + +The numbers on the diagram refer to the notes below. +1. Egeria can capture open lineage events directly through HTTP or via the proxy backend. +2. OpenLineage metadata is correlated and matched to existing metadata captured through a variety of mechanisms from direct metadata extraction from the hosting data platforms, to updates through dev ops pipelines to metadata discovery analytic tools. +3. Egeria can publish OpenLineage events. These include the OpenLineage events it received (potentially augmented with additional facets), or events generated from its own governance processes. Published OpenLineage events can go to Egeria’s OpenLineage file-based log store for later processing or to any application that supports the OpenLineage API (Marquez, for example -- another project from LF AI and Data). +4. The metadata extracted from OpenLineage events can be distributed to the open metadata ecosystem using standard approaches. This means it can be picked up by connected data science, governance and lineage tools. +5. Governance processes linked to the open metadata ecosystem can use OpenLineage events to validate that their originating processes are operating as frequently and as accurately as expected. + +More information on Egeria’s open lineage support can be found [here](https://egeria-project.org/features/lineage-management/overview/#the-openlineage-standard). + +The Egeria community would like to thank the OpenLineage community for their great support while we created this integration. We look forward to continuing to work together as both our projects mature. diff --git a/blog/openlineage-egeria/open-lineage-blog.svg b/blog/openlineage-egeria/open-lineage-blog.svg new file mode 100644 index 0000000000..db9fa5d105 --- /dev/null +++ b/blog/openlineage-egeria/open-lineage-blog.svg @@ -0,0 +1,4 @@ + + + +
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b/blog/openlineage-microsoft-purview/index.mdx @@ -0,0 +1,124 @@ +--- +title: Microsoft Purview Accelerates Lineage Extraction from Azure Databricks +date: 2022-06-14 +author: Chandru Sugunan, Will Johnson & Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: A new collaboration between Microsoft and OpenLineage is making lineage extraction possible for Azure Databricks and Microsoft Purview users. +--- +A new collaboration between Microsoft and OpenLineage is making lineage extraction possible for Azure Databricks and Microsoft Purview users. + +![](./banner.svg#full-width) + + + +A new collaboration between Microsoft and OpenLineage is making lineage extraction possible for Azure Databricks and Microsoft Purview users. Thanks to a robust OpenLineage Spark integration, users can both extract and visualize lineage from their Databricks notebooks and jobs inside Microsoft Purview. This blog post shares the history and future of this exciting open-source project, describes the solution, and shows you how to get started. + +### Summary + +- [Microsoft Purview](https://azure.microsoft.com/en-us/services/purview/) provides a comprehensive platform to populate native and custom data lineage metadata from on-prem, OSS, SaaS, and multi-cloud data systems. +- The [Azure Databricks to Microsoft Purview Solution Accelerator](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator) takes advantage of the robust Spark integration inside [OpenLineage](https://github.com/OpenLineage/OpenLineage) and translates OpenLineage events into Microsoft Purview native assets supporting: + - Azure Data Lake Gen 2 + - Azure Blob Storage + - Azure SQL + - Azure Synapse SQL Pools +- Customers of Azure Databricks and Microsoft Purview can [try the solution today](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator) by following the [demo instructions](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator/blob/main/deploy-demo.md) or [connector only instructions](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator/blob/main/deploy-base.md). + +### What is Microsoft Purview? + +[Microsoft Purview](https://docs.microsoft.com/en-us/azure/purview/overview) provides an ambient data governance solution that helps you unify and manage your data wherever it exists – on-premises, in the cloud, or on a software-as-a-service (SaaS) platform. With Microsoft Purview, you can: +- create a holistic, up-to-date map of your data landscape with automated data discovery, sensitive data classification, and end-to-end data lineage. +- enable data curators to manage and secure your data estate. +- empower data consumers to find valuable, trustworthy data. + +![High-level overview](./high-level-overview.png) +Figure 1. Microsoft Purview is an ambient data governance platform for an enterprise. + +Microsoft Purview automates data discovery by providing data scanning and classification as a service for assets across your data estate. Microsoft Purview integrates metadata and descriptions of discovered data assets into a holistic map of your data ecosystem. Layered on this map are purpose-built apps that create environments for data discovery, policy management, and insights into your data landscape. + +### Data Lineage in Microsoft Purview + +Organizations need data to conduct business, and they need trustworthy data to perform analysis and make key decisions. Data lineage and provenance provide insights into data pedigree, which relates to operational information, runtime analysis, historical lineage, and ownership information. Users rely on pedigree when taking insights from data. Critical scenarios involving root cause analysis, impact analysis, quality control, compliance, and audit tracing are served by data lineage and provenance. + +[Data Lineage](https://docs.microsoft.com/en-us/azure/purview/catalog-lineage-user-guide) in Microsoft Purview is a core platform capability that populates the Microsoft Purview Data Map with data movement and transformations across systems. With the backing of [Apache Atlas 2.2](https://atlas.apache.org/#/), lineage is captured as it flows in the enterprise and stitched without gaps irrespective of its source. Data lineage in Microsoft Purview enables data analysts and data stewards to conduct root cause analysis, troubleshoot, and perform impact analysis of data moving upstream and downstream in data estates. With a combined platform and interactive lineage visualization tool, data investigations related to quality, trust, and compliance can be self-served in a few clicks rather than requested from a third party. + +Microsoft Purview has native data lineage support for [20+ sources](https://docs.microsoft.com/en-us/azure/purview/catalog-lineage-user-guide#lineage-collection), many of which are integrated at engine runtimes. For example, data lineage is pushed from Azure Data Factory when pipelines are run. This deep integration allows Microsoft Purview to capture operational metadata such as job start/end times, the number of rows impacted, job run status and more. In addition to native support, the [open APIs](https://docs.microsoft.com/en-us/rest/api/purview/catalogdataplane/lineage) can be used to integrate with enterprise systems to support custom lineage. + + + +Figure 2. Native data lineage visualization in Microsoft Purview. + +### OpenLineage + Microsoft + +This integration came about because Microsoft Purview sought a lineage solution for Azure Databricks users, ideally one that would support all Azure data repository types, from Azure Blob Storage to Azure SQL. The team that took on this challenge was the Early Access Engineering (EAE) team, a group of data experts at Microsoft who forge competitive differentiation and value by using groundbreaking technology and features before they become available to the general enterprise landscape. + +#### A History of Contributions to OpenLineage + +The EAE team at Microsoft has a long history of contributions to open source projects in general and to OpenLineage in particular. In December of 2021, Will Johnson contributed a [PR](https://github.com/OpenLineage/OpenLineage/pull/425) to OpenLineage to add support for arbitrary parameters in the OpenLineage URL. This change supported key-based authentication via URL and eased the process of sending metadata from OpenLineage to repositories other than [Marquez](https://github.com/MarquezProject), OpenLineage’s sister project. This in turn supported additional integrations and collaboration and has helped to increase adoption of the OpenLineage standard. + +Over the course of seven months, the Microsoft team contributed eight pull requests to enable: +- better support for the Azure Blob File System (Azure Data Lake Gen 2). +- use of an Azure Function as the lineage endpoint. +- lineage extraction for [Azure Synapse](https://docs.microsoft.com/en-us/azure/databricks/data/data-sources/azure/synapse-analytics) as a data source. +- extraction of Databricks environment properties such as notebook paths and job ids. + +Contributing open source integrations to OpenLineage benefits not only Microsoft Purview but also the data landscape as a whole. Collaborations like this one help increase adoption of the OpenLineage standard across the industry, which gets us closer to the single standard we need for consistently powerful and reliable lineage across the wide diversity of tooling in today’s data pipelines. + +At Microsoft, this kind of work is not unique to the EAE team. Across the company, cross-functional, community-driven teams foster innovation through open source collaboration. + +### Why Contribute to OpenLineage? + +Most enterprise data environments are convoluted, with data systems spread across on-prem, multi-cloud, SaaS, and open-source platforms. The data moves between a variety of storage, processing, analytical, and SaaS data systems. Azure Databricks is one such data system in an enterprise with a lakehouse platform in the cloud that combines data warehouses and data lakes to offer an open and unified platform for data and AI. Microsoft Purview customers have long asked for the ability to populate and govern Azure Databricks assets in the Microsoft Purview DataMap. With OpenLineage, we are bringing runtime Data Lineage capture from Azure Databricks Spark workloads to Microsoft Purview. + +In addition, by contributing to OpenLineage, Microsoft can offer users of OpenLineage on other platforms the ability to represent metadata models of Microsoft data sources accurately in their lineage graphs. For example, users of Spark on any other platform can represent the metadata models of Microsoft data sources more accurately. + +Lastly, OpenLineage benefits from Microsoft’s contributions as they will add hundreds if not thousands of new users to the OpenLineage standard. This will spur more contributions by the OpenLineage community as more users request that new implementations and features be added to the specification. + +### About the Solution + +![Flow of metadata using OpenLineage](./purview-lineage.png) +Figure 3. The flow of metadata from Azure Databricks to Microsoft Purview using OpenLineage. + +1. An Azure administrator deploys an Azure Function (serverless C# application) and an Event Hub (to store OpenLineage events) by running a deployment script. +2. An administrator configures a Databricks cluster as per the [OpenLineage install instructions](https://github.com/OpenLineage/OpenLineage/tree/main/integration/spark/databricks) along with the Azure Function key and OpenLineage host pointing to the Azure Function. +3. The OpenLineage Spark jar extracts the necessary inputs and outputs and emits them to the Azure Function. +4. The Azure Functions transform the OpenLineage payload and push lineage to Microsoft Purview through the Apache Atlas REST APIs. +5. Databricks Lineage is then visible inside Microsoft Purview! + + +## Getting Started with Microsoft Purview +

+Quickly and easily create a Microsoft Purview account to explore the new features. + +Try out the [Azure Databricks to Microsoft Purview Solution Accelerator](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator). + +Learn how to [deploy the solution](https://www.youtube.com/watch?v=pLF0iykhruY&feature=youtu.be). +
+ +### What the Future Holds + +Microsoft plans to continue contributing to OpenLineage to ensure that users can extract lineage from additional Azure data sources such as [Azure Data Explorer (Kusto)](https://docs.microsoft.com/en-us/azure/data-explorer/spark-connector), [Azure Cosmos DB](https://docs.microsoft.com/en-us/azure/cosmos-db/sql/create-sql-api-spark), and [Azure Event Hubs](https://docs.microsoft.com/en-us/azure/databricks/spark/latest/structured-streaming/streaming-event-hubs), and that OpenLineage continues to perform well on Azure Databricks. + +In addition, Microsoft plans to keep up-to-date with advancements made by the OpenLineage community, such as the exciting recent contribution of [column-level lineage](https://github.com/OpenLineage/OpenLineage/pull/698) to the project. + +### Acknowledging the Contributors + +The OpenLineage Spark integration is the product of hard work by teams inside and outside Microsoft. + +Contributors from the Microsoft Early Access Engineering team include: +- Mark Taylor, Principal Technical Specialist ([@marktayl1](https://github.com/Marktayl1)) +- Will Johnson, Global Black Belt - Big Data, Analytics, and ML Specialist ([@wjohnson](https://github.com/wjohnson)) +- Rodrigo Monteiro, Global Black Belt - Big Data, Analytics ([@rodrigomonteiro-gbb](https://github.com/rodrigomonteiro-gbb)) +- Travis Hilbert, Technical Specialist ([@travishilbert](https://github.com/TravisHilbert)) +- Matt Savarino, Sr. Technical Specialist ([@mattsavarino](https://github.com/mattsavarino)) + +Outside Microsoft, contributors to the OpenLineage Spark integration are based at a range of internationally distributed companies and organizations. Additional contributors to the integration include: +- Michael Collado, Staff Software Engineer, Astronomer ([@collado-mike](https://github.com/collado-mike)) +- Oleksandr Dvornik, Senior Java Developer, UBS ([@OleksandrDvornik](https://github.com/OleksandrDvornik)) +- Paweł Leszczyński, Data Engineer, GetInData ([@pawel-big-lebowski](https://github.com/pawel-big-lebowski)) +- Tomasz Nazarewicz, Data Engineer, GetInData ([@tnazarew](https://github.com/tnazarew)) +- Maciej Obuchowski, Software Engineer, GetInData ([@mobuchowski](https://github.com/mobuchowski)) +- Kengo Seki, PMC Member and Committer, Apache Software Foundation ([@sekikn](https://github.com/sekikn)) +- Ziyoiddin Yusupov, Senior Software Engineer, UBS ([@mr-yusupov](https://github.com/mr-yusupov)) + +Try the [Azure Databricks to Microsoft Purview Solution Accelerator](https://github.com/microsoft/Purview-ADB-Lineage-Solution-Accelerator) today! diff --git a/blog/openlineage-microsoft-purview/purview-lineage.png 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+ + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-snowflake/image.svg b/blog/openlineage-snowflake/image.svg new file mode 100644 index 0000000000..55934fb374 --- /dev/null +++ b/blog/openlineage-snowflake/image.svg @@ -0,0 +1,36 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-snowflake/index.mdx b/blog/openlineage-snowflake/index.mdx new file mode 100644 index 0000000000..5bfe492405 --- /dev/null +++ b/blog/openlineage-snowflake/index.mdx @@ -0,0 +1,241 @@ +--- +title: Data Lineage with Snowflake +date: 2022-04-27 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: The OpenLineage Adapter offers Snowflake's enterprise users a powerful tool for analyzing their pipelines. +--- +The OpenLineage Adapter offers Snowflake's enterprise users a powerful tool for analyzing their pipelines. + +![](./banner.svg#full-width) + + + +## Introduction + +We are excited to reveal a new way to gather lineage metadata directly from Snowflake: the OpenLineage Adapter. This integration offers Snowflake’s enterprise users a powerful tool for analyzing and diagnosing issues with their data pipelines. + +This new integration will add new diagnostic capability to one of the world’s largest data platforms. Snowflake’s Data Cloud currently empowers more than 5,900 companies, including 241 of the Fortune 500 as of January 2022, to unite siloed data, securely share data, and execute diverse analytic workloads across their organizations. Legacy platforms struggled to provide a single, secure, and universally accessible platform for organizations to warehouse and analyze their data, but Snowflake’s Data Cloud provides a global ecosystem where customers, providers, and partners can finally break down data silos and derive value from rapidly growing data sets in secure, compliant, and governed ways. + +## Background + +An open source [LF AI & Data Foundation](https://lfaidata.foundation/projects/openlineage) sandbox project, OpenLineage provides an open standard for metadata and lineage collection that instruments jobs as they are running. OpenLineage not only automates the process of generating lineage and metadata about datasets, jobs, and runs in a data flow, but also does this in real time behind the scenes. With OpenLineage’s open standard and extensible backend, users can easily identify the root causes of slow or failing jobs and issues with data quality in their ecosystems without parsing queries. The magic of OpenLineage is its standard API for capturing lineage events. Any number of tools – from schedulers to SQL engines – can send metadata from this endpoint to a compatible tool such as [Marquez](https://github.com/MarquezProject/marquez) for visualization and further analysis of a pipeline. + +Historically, the process of producing lineage and collecting metadata has been laborious and error-prone. Extracting data from query logs via parsing, for example, required one to reimplement database parsing logic, which added complexity and introduced opportunities for user error. In addition, the lineage collected was incomplete. One could learn about the view that was queried but not about the underlying tables in the pipeline, much less about the upstream and downstream dependencies of the datasets. OpenLineage, by contrast, exploits what the database already knows and does to maintain an up-to-date, end-to-end graph of a pipeline – and makes the graph available via an API. + +OpenLineage and Snowflake play nicely because the latter is unusual among cloud data platforms for offering lineage information out of the box in a view ([ACCESS_HISTORY](https://docs.snowflake.com/en/sql-reference/account-usage/access_history.html)). The integration of OpenLineage builds on this foundation to offer automated generation of lineage and metadata. + +The value proposition of Snowflake + OpenLineage lies in the combination of an open standard tool, which supports multiple data systems to provide lineage in a single format, to Snowflake’s existing production of lineage information on an enterprise scale. The integration gives customers the ability to consume enterprise-wide table lineage and process lineage together in a consolidated OpenLineage format. + +## Approach + +The process of integrating OpenLineage benefited from an existing query logging tool already available to Snowflake enterprise customers: the `ACCESS_HISTORY` view. As its name suggests, this feature, designed initially for governance use cases, offers users a detailed view of read operations conducted on Snowflake objects (e.g., tables, views, and columns) on an on-demand basis in response to SQL queries. (Write operations are viewable as a preview feature.) + +As developed primarily by former Snowflake intern Aly Hirani with support from Datakin Senior Engineer Minkyu Park, the OpenLineage integration makes Access History the basis of automated production of lineage and metadata. But rather than produce a view for querying, OpenLineage produces a holistic lineage graph. To create the graph, the integration takes the data used to populate the Access History view and sends it to the OpenLineage backend as a standard OpenLineage event. Events in OpenLineage are JSON objects that employ a consistent naming strategy for database entities and enrich those entities with facets: + +``` +{ + "eventType": "COMPLETE", + "eventTime": "2020-12-28T20:52:00.001+10:00", + "run": { + "runId": "d46e465b-d358-4d32-83d4-df660ff614dd" + }, + "job": { + "namespace": "my-namespace", + "name": "my-job" + }, + "outputs": [{ + "namespace": "my-namespace", + "name": "my-output", + "facets": { + "schema": { + "_producer": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client", + "_schemaURL": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/spec/OpenLineage.json#/definitions/SchemaDatasetFacet", + "fields": [ + { "name": "a", "type": "VARCHAR"}, + { "name": "b", "type": "VARCHAR"} + ] + } + } + }], + "producer": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" +} +``` + +## A DAG-based Solution + +Automating lineage production from the Access History view required a two-DAG solution. Minkyu had initially planned to use one DAG to scan the view and produce the lineage graph, but the timing of the logs used for the view precluded the production of lineage data with a single DAG. The solution Minkyu found was a separate DAG with a schedule for scanning the Access History view on a regular interval. + +``` +def send_ol_events(): + client = OpenLineageClient.from_environment() + + with connect(user=SNOWFLAKE_USER, + password=SNOWFLAKE_PASSWORD, + account=SNOWFLAKE_ACCOUNT, + database='OPENLINEAGE', + schema='PUBLIC') as conn: + with conn.cursor() as cursor: + ol_view = 'OPENLINEAGE_ACCESS_HISTORY' + ol_event_time_tag = 'OL_LATEST_EVENT_TIME' + + var_query = f''' + set current_organization='{SNOWFLAKE_ACCOUNT}'; + ''' + + cursor.execute(var_query) + + ol_query = f''' + SELECT * FROM {ol_view} + WHERE EVENT:eventTime > system$get_tag('{ol_event_time_tag}', '{ol_view}', 'table') + ORDER BY EVENT:eventTime ASC; + ''' + + cursor.execute(ol_query) + ol_events = [json.loads(ol_event[0]) for ol_event in cursor.fetchall()] + + for ol_event in ol_events: + client.emit(ol_event) + + if len(ol_events) > 0: + latest_event_time = ol_events[-1]['eventTime'] + cursor.execute(f''' + ALTER VIEW {ol_view} SET TAG {ol_event_time_tag} = '{latest_event_time}'; + ''') + +default_args = { + 'owner': 'openlineage', + 'depends_on_past': False, + 'start_date': days_ago(1), + 'email_on_failure': False, + 'email_on_retry': False, + 'email': ['demo@openlineage.io'], + 'snowflake_conn_id': 'openlineage_snowflake' +} + +with DAG('etl_openlineage', + schedule_interval='@hourly', + catchup=False, + default_args=default_args, + description='Send OL events every minutes', + tags=["extract"]) as dag: + t1 = PythonOperator(task_id='ol_event', python_callable=send_ol_events) +``` + +## Getting Started with an Example + +This example uses Airflow to run a collection of Snowflake queries for a fictional food delivery service. Lineage data for these queries will be recorded within Snowflake `ACCESS_HISTORY` and, using the OpenLineage Access History View, emitted to an OpenLineage backend. + +This is done using a series of DAGs in `dags/etl` that each use SnowflakeOperator to run queries, along with a DAG in `dags/lineage` that uses PythonOperator to send generated OpenLineage events to the configured backend. + +### Prerequisites + +#### Installing Marquez + +First, checkout the Marquez repository: + +```bash +% git clone https://github.com/MarquezProject/marquez.git +% cd marquez +``` + +Then, run Marquez in detached mode: + +```bash +% docker/up.sh -d +% +``` + +#### Preparing Snowflake + +First, check out the OpenLineage Access History View repository: + +```bash +% git clone https://github.com/Snowflake-Labs/OpenLineage-AccessHistory-Setup.git +% cd OpenLineage-AccessHistory-Setup +``` + +The `OPENLINEAGE` database and `FOOD_DELIVERY` schema in Snowflake need to be created. This can be done using the SnowSQL command-line tool, or by pasting the queries into a new Snowflake Worksheet. This example uses SnowSQL. + +```bash +% snowsql -u -a +SnowSQL> CREATE DATABASE OPENLINEAGE; +SnowSQL> CREATE SCHEMA OPENLINEAGE.FOOD_DELIVERY; +``` + +The view defined in `open_lineage_access_history.sql` also needs to be created. This view represents the entries in `ACCESS_HISTORY` as specially-constructed JSON objects containing RunEvents that can be emitted to an OpenLineage backend. To create it, use SnowSQL to set the current_organization session variable and execute the SQL file. + +``` +SnowSQL> SET current_organization=''; +SnowSQL> USE SCHEMA OPENLINEAGE.PUBLIC; +SnowSQL> !source open_lineage_access_history.sql +``` + +Finally, our lineage extraction DAG relies upon a tag on the view to keep track of which lineage events have been processed. This tag needs to be initialized: + +``` +SnowSQL> CREATE TAG OL_LATEST_EVENT_TIME; +SnowSQL> ALTER VIEW OPENLINEAGE.PUBLIC.OPENLINEAGE_ACCESS_HISTORY SET TAG OL_LATEST_EVENT_TIME = '1970-01-01T00:00:00.000'; +SnowSQL> !quit +% +``` + +### Preparing the Environment + +The following environment variables need to be set in order for the query DAGs to connect to Snowflake, and so that the extraction DAG can send lineage events to your OpenLineage backend: +- SNOWFLAKE_USER +- SNOWFLAKE_PASSWORD +- SNOWFLAKE_ACCOUNT +- OPENLINEAGE_URL +- AIRFLOW_CONN_OPENLINEAGE_SNOWFLAKE + +To do this, copy the `.env-example` file to `.env`, and edit it to provide the appropriate values for your environment. The variables in this file will be set for each service in the Airflow deployment. + +```bash +% cd examples/airflow +% cp .env-example .env +% vi .env +``` + +### Preparing Airflow + +Once the environment is prepared, initialize Airflow with docker-compose: + +```bash +% docker-compose up airflow-init +``` + +This will take several minutes. When it has finished, bring up the Airflow services: + +``` +% docker-compose up +``` + +This will also take several minutes. Eventually, the webserver will be up at [http://localhost:8080](http://localhost:8080). Log in using the default credentials (airflow/airflow) and navigate to the DAGs page. When you see 12 DAGs in the list, you can be confident that Airflow has completed its initialization of the example. + +### Running the Example + +Each of the DAGs is paused by default. Enable each one, skipping the `etl_openlineage` DAG for now. They may not all run successfully on the first try, since they have interdependencies that this example leaves unmanaged. + +![Airflow DAG list](./snowflake-airflow-example.png) + +After each DAG has completed at least one successful run, enable `etl_openlineage`. Wait for it to complete its run. + +### Result + +Navigate to your Marquez deployment and view the resulting lineage graph: + +![Lineage graph](./snowflake-openlineage-example.png) + +## Potential Improvements + +This new integration paves the way for an exciting set of potential future capabilities. These include support for `Object_Dependencies` and the addition of Granular Lineage (column-level lineage). We are interested in feedback from users, which will help the team at Snowflake and the members of the OpenLineage community prioritize future work. + +## Conclusion + +Snowflake’s integration of the OpenLineage standard promises to dramatically improve enterprise users’ ability to diagnose issues with quality and performance in their pipelines. This project is cause for optimism about future collaboration with OpenLineage. The fit between Snowflake’s enterprise product and OpenLineage is already fairly seamless. Further collaboration would likely yield additional features and, by extension, more value for Snowflake’s customers. Also, the fact that OpenLineage is an open standard offers opportunities for fruitful integrations with other partners. Supporters of OpenLineage already include Spark, Airflow, and dbt, and the list is growing. 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zu!$2WmZ9>vqEGnmYI3khq@b1{5h_?52}~iBZ3bZk4xL?^BG)uXXE^_VUNWIw+XfXt zUM*vYhRzLOWNSgiKaS+-<#fj3t=b^9{VQgo*LWi9`Tkx8{9~wVqVqt@HuV1iubq^y literal 0 HcmV?d00001 diff --git a/blog/openlineage-spark/image.svg b/blog/openlineage-spark/image.svg new file mode 100644 index 0000000000..49c8a26c1d --- /dev/null +++ b/blog/openlineage-spark/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/openlineage-spark/index.mdx b/blog/openlineage-spark/index.mdx new file mode 100644 index 0000000000..284b223f47 --- /dev/null +++ b/blog/openlineage-spark/index.mdx @@ -0,0 +1,297 @@ +--- +title: Tracing Data Lineage with OpenLineage and Apache Spark +date: 2021-11-05 +author: Michael Collado +image: ./image.svg +banner: ./banner.svg +description: Spark ushered in a brand new age of data democratization... and left us with a mess of hidden dependencies, stale datasets, and failed jobs. +--- +Spark ushered in a brand new age of data democratization... and left us with a mess of hidden dependencies, stale datasets, and failed jobs. + +![](./banner.svg#full-width) + + + +## The Age of Data Democratization + +In 2015, Apache Spark seemed to be taking over the world. Many of us had spent the prior few years moving our large +datasets out of the Data Warehouse into "Data Lakes"- repositories of structured and unstructured data in +distributed file systems or object stores, like HDFS or S3. This enabled us to build analytic systems that could +handle traditional, table-structured data alongside flexible, unstructured JSON blobs, giving us access to more data +and allowing us to move much faster than we’d previously been able to. + +The problem was that taking the data out of Data Warehouses meant that the people who really needed access to the +data, analysts and statisticians, could no longer use the tools they were comfortable with in order to read that data. +Where previously, SQL and Python were all that was needed to start exploring and analyzing a dataset, now people needed +to write Java or use specialized scripting languages, like Pig, to get at the data. Systems that did support SQL, such +as Hive, were unbearably slow for any but the most basic operations. In many places, the statisticians were dependent on +software engineers to build custom tools for access, meaning the bottleneck had moved from the systems that +needed to store and process the data to the humans who were supposed to tell us what systems to build. + +Then along came Apache Spark, which gave back to analysts the ability to use their beloved Python (and eventually SQL) +tools to process raw data in object stores without the dependency on software engineers. While others were +attracted to its ability to perform multiple operations on data without the I/O overhead of alternatives, like Pig or +Hive, data scientists were thrilled to start piping that data through their NumPy and Pandas scripts. + +## A Colossal Mess + +Of course, the natural consequence of this data democratization is that it becomes difficult to keep track of who is +using the data and for what purpose. Hidden dependencies and Hyrum’s Law suddenly meant that changes to the data schema +would inadvertently break downstream processes or that stale, deprecated datasets were still being consumed, and that +corrupted datasets would leak into unknown processes making recovery difficult or even impossible. + +[![XKCD 1172](./workflow.png)](https://xkcd.com/1172/) + +The goal of OpenLineage is to reduce issues and speed up recovery by exposing those hidden dependencies and informing +both producers and consumers of data about the state of that data and the potential blast radius of changes and software +bugs. Naturally, support for Apache Spark seemed like a good idea and, while the Spark 2.4 branch has been supported for +some time, the recent OpenLineage 0.3 release has explicit support for Spark 3.1. 🎉 + +## Getting Started + +Our approach to integrating with Spark is not super novel nor is it complicated to integrate into your own system. Spark +has had a SparkListener interface since before the 1.x days. If you're a heavy Spark user, it's likely you're already +familiar with it and how it's used in Spark applications. OpenLineage integrates with Spark by implementing that +interface and collecting information about jobs that are executed inside a Spark application. To activate the +listener, add the following properties to your Spark configuration: +``` +spark.jars.packages io.openlineage:openlineage-spark:0.3.+ +spark.extraListeners io.openlineage.spark.agent.OpenLineageSparkListener +``` +This can be added to your cluster’s `spark-defaults.conf` file, in which case it will record lineage for every job executed on the cluster, or added to specific jobs on submission via the `spark-submit` command. Once the listener is activated, it needs to know where to report lineage events, as well as the namespace of your jobs. Add the following additional configuration lines to your `spark-defaults.conf` file or your Spark submission script: +``` +spark.openlineage.host {your.openlineage.host} +spark.openlineage.namespace {your.openlineage.namespace} +``` +## The Demo + +Trying out the Spark integration is super easy if you already have Docker Desktop and git installed. To follow along +with this demo, you’ll also need a Google Cloud account and a Service Account JSON key file for an account that has +access to BigQuery and read/write access to your GCS bucket. I added mine to a file called bq-spark-demo.json. + +Note: If you're on macOS Monterey (macOS 12) you'll have to release port 5000 before beginning by [disabling the AirPlay Receiver](https://developer.apple.com/forums/thread/682332). + +Check out the OpenLineage project into your workspace with: +```bash +git clone https://github.com/OpenLineage/OpenLineage +``` + +Then cd into the integration/spark directory. Run `mkdir -p docker/notebooks/gcs` and copy your service account credentials +file into that directory. Then run: + +```bash +docker-compose up +``` + +This launches a Jupyter notebook with Spark already installed as well as a Marquez API endpoint to report lineage. Once the notebook server is up and running, you should see something like the following text in the logs: +``` +notebook_1 | [I 21:43:39.014 NotebookApp] Jupyter Notebook 6.4.4 is running at: +notebook_1 | [I 21:43:39.014 NotebookApp] http://082cb836f1ec:8888/?token=507af3cf9c22f627f6c5211d6861fe0804d9f7b19a93ca48 +notebook_1 | [I 21:43:39.014 NotebookApp] or http://127.0.0.1:8888/?token=507af3cf9c22f627f6c5211d6861fe0804d9f7b19a93ca48 +notebook_1 | [I 21:43:39.015 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). +``` + +Copy the URL with 127.0.0.1 as the hostname from your own log (the token will be different from mine) and paste it into +your browser window. You should have a blank Jupyter notebook environment ready to go. + +![Jupyter home screen](./jupyter_home.png) + +Once your notebook environment is ready, click on the notebooks directory, then click on the New button to create a new +Python 3 notebook. + +![Jupyter create new notebook](./jupyter_new_notebook.png) + +In the first cell in the window paste the following text. Update the GCP project and bucket names and the +service account credentials file, then run the code: + +```python +from pyspark.sql import SparkSession +import urllib.request + +# download dependencies for BigQuery and GCS +gc_jars = ['https://repo1.maven.org/maven2/com/google/cloud/bigdataoss/gcs-connector/hadoop3-2.1.1/gcs-connector-hadoop3-2.1.1-shaded.jar', + 'https://repo1.maven.org/maven2/com/google/cloud/bigdataoss/bigquery-connector/hadoop3-1.2.0/bigquery-connector-hadoop3-1.2.0-shaded.jar', + 'https://repo1.maven.org/maven2/com/google/cloud/spark/spark-bigquery-with-dependencies_2.12/0.22.2/spark-bigquery-with-dependencies_2.12-0.22.2.jar'] + +files = [urllib.request.urlretrieve(url)[0] for url in gc_jars] + + +# Set these to your own project and bucket +project_id = 'bq-openlineage-spark-demo' +gcs_bucket = 'bq-openlineage-spark-demo-bucket' +credentials_file = '/home/jovyan/notebooks/gcs/bq-spark-demo.json' + +spark = (SparkSession.builder.master('local').appName('openlineage_spark_test') + .config('spark.jars', ",".join(files)) + + # Install and set up the OpenLineage listener + .config('spark.jars.packages', 'io.openlineage:openlineage-spark:0.3.+') + .config('spark.extraListeners', 'io.openlineage.spark.agent.OpenLineageSparkListener') + .config('spark.openlineage.host', 'http://marquez-api:5000') + .config('spark.openlineage.namespace', 'spark_integration') + + # Configure the Google credentials and project id + .config('spark.executorEnv.GCS_PROJECT_ID', project_id) + .config('spark.executorEnv.GOOGLE_APPLICATION_CREDENTIALS', '/home/jovyan/notebooks/gcs/bq-spark-demo.json') + .config('spark.hadoop.google.cloud.auth.service.account.enable', 'true') + .config('spark.hadoop.google.cloud.auth.service.account.json.keyfile', credentials_file) + .config('spark.hadoop.fs.gs.impl', 'com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem') + .config('spark.hadoop.fs.AbstractFileSystem.gs.impl', 'com.google.cloud.hadoop.fs.gcs.GoogleHadoopFS') + .config("spark.hadoop.fs.gs.project.id", project_id) + .getOrCreate()) +``` + +Most of this is boilerplate- we need the BigQuery and GCS libraries installed in the notebook environment, then we need +to set the configuration parameters to tell the libraries what GCP project we want to use and how to authenticate with +Google. The parameters specific to OpenLineage are the four we already covered- `spark.jars.packages`, +`spark.extraListeners`, `spark.openlineage.host`, `spark.openlineage.namespace`. Here, we’ve configured the host to be +the marquez-api container started by Docker. + +Google has a wealth of information available as public datasets in BigQuery. If you’re ever bored one Saturday night, +browse the datasets available- you’ll find census data, crime data, liquor sales, and even a black hole database. For +the demo, I thought I’d browse some of the Covid19 related datasets they have. Specifically, there’s a dataset that +reports the likelihood of people in a given county to wear masks (broken up into five categories: `always`, `frequently`, +`sometimes`, `rarely`, and `never`). There’s also a giant dataset called `covid19_open_data` that contains things like +vaccination rates, current totals of confirmed cases, hospitalizations, deaths, population breakdowns, and policies on +mask-wearing, contact tracing, and vaccination-mandates. Both datasets contain the county FIPS code for US counties, +meaning we can join the two datasets and start exploring. + +Create a new cell in the notebook and paste the following code: + +```python +from pyspark.sql.functions import expr, col + +mask_use = spark.read.format('bigquery') \ + .option('parentProject', project_id) \ + .option('table', 'bigquery-public-data:covid19_nyt.mask_use_by_county') \ + .load() \ + .select(expr("always + frequently").alias("frequent"), + expr("never + rarely").alias("rare"), + "county_fips_code") + +opendata = spark.read.format('bigquery') \ + .option('parentProject', project_id) \ + .option('table', 'bigquery-public-data.covid19_open_data.covid19_open_data') \ + .load() \ + .filter("country_name == 'United States of America'") \ + .filter("date == '2021-10-31'") \ + .select("location_key", + expr('cumulative_deceased/(population/100000)').alias('deaths_per_100k'), + expr('cumulative_persons_fully_vaccinated/(population - population_age_00_09)').alias('vaccination_rate'), + col('subregion2_code').alias('county_fips_code')) +joined = mask_use.join(opendata, 'county_fips_code') + +joined.write.mode('overwrite').parquet(f'gs://{gcs_bucket}/demodata/covid_deaths_and_mask_usage/') +``` + +Again, this is standard Spark DataFrame usage. The particulars are completely irrelevant to the OpenLineage data +collection- we don’t need to call any new APIs or change our code in any way. Here, I’ve filtered +the `covid19_open_data` table to include only U.S. data and to include the data for Halloween 2021. That dataset has a +large number of columns, but for my own purposes, I’m only interested in a few of them. I calculate `deaths_per_100k` +using the existing `cumulative_deceased` and `population` columns and I calculate the `vaccination_rate` using the total +population, subtracting the 0-9 year olds, since they weren’t eligible for vaccination at the time. For +the `mask_use_by_county` data, I don't really care about the difference between `rarely` and `never`, so I combine them +into a single number. I do the same for `frequently` and `always`. I join the few columns I want from the two datasets +and store the combined result in GCS. + +Add one more cell to the notebook and paste the following: + +```python +spark.read.parquet(f'gs://{gcs_bucket}/demodata/covid_deaths_and_mask_usage/').count() +``` + +The notebook will likely spit out a warning and a stacktrace (it should probably be a debug statement), then give you a +total of 3142 records. + +So far, so good. Now what? If this was a data science blog, we might start generating some scatter plots or doing a +linear regression to determine whether frequent mask usage was a predictor of high death rates or vaccination rates. +But since we're really focused on lineage collection, I'll leave the rest of the analysis up to those with the time and +inclination to dig further. Instead, let's switch to exploring the lineage records we just created. + +The `docker-compose.yml` file that ships with the OpenLineage repo includes only the Jupyter notebook and the Marquez API. +For exploring visually, we’ll also want to start up the Marquez web project. Without terminating the existing docker +containers, run the following command in a new terminal: + +```bash +docker run --network spark_default -p 3000:3000 -e MARQUEZ_HOST=marquez-api -e MARQUEZ_PORT=5000 --link marquez-api:marquez-api marquezproject/marquez-web:0.19.1 +``` + +Now open a new browser tab and navigate to `http://localhost:3000`. You should see a screen like the following: + +![Marquez home page](./marquez_home.png) + +Note the spark_integration namespace was found for us and automatically chosen, since there are no other namespaces +available. We can see three jobs listed on the jobs page of the UI. They all start with `openlineage_spark_test`, which +is the `appName` we passed to the SparkSession we were building in the first cell of the notebook. Each query execution +or RDD action is represented as a distinct job and the name of the action is appended to the application name to form +the name of the job. Clicking on the `openlineage_spark_test.execute_insert_into_hadoop_fs_relation_command` node, we +can see the lineage graph for our notebook: + +![Marquez job lineage](./marquez_job_graph.png) + +The graph shows the `openlineage_spark_test.execute_insert_into_hadoop_fs_relation_command` job reads from two input +datasets, `bigquery-public-data.covid19_nyt.mask_use_by_county` +and `bigquery-public-data.covid19_open_data.covid19_open_data`, and writes to a third dataset, +`/demodata/covid_deaths_and_mask_usage`. The namespace is missing from that third dataset- the fully qualified name is +`gs:///demodata/covid_deaths_and_mask_usage`. + +Before clicking on the datasets, though, the bottom bar shows some really interesting data that was collected from the +Spark job. Dragging the bar up expands the view so we can get a better look at that data. + +![Marquez job facets](./marquez_job_facets.png) + +Two [facets](https://openlineage.io/blog/extending-with-facets/) that are always collected from Spark jobs are +the `spark_version` and the `spark.logicalPlan`. The first simply reports what version of Spark was executing, as well +as the version of the `openlineage-spark` library. This is helpful information to collect when trying to debug a job +run. + +The second facet is the serialized optimized `LogicalPlan` Spark reports when the job runs. Spark’s query optimization +can have dramatic effects on the execution time and efficiency of the query job. Tracking how query plans change over +time can significantly aid in debugging slow queries or OutOfMemory errors in production. + +Clicking on the first BigQuery dataset gives us information about the data we read: + +![Marquez dataset latest facet](./marquez_bigquery_dataset_latest.png) + +Here, we can see the schema of the dataset as well as the datasource — namely BigQuery. + +We can get similar information about the dataset written to in GCS: + +![Marquez output dataset latest facet](./marquez_output_dataset_latest.png) + +As in the BigQuery dataset, we can see the output schema and the datasource — here, the `gs://` scheme and the name of +the bucket we wrote to. + +In addition to the schema, we also see a `stats` facet, reporting the number of output records and bytes as -1. A +somewhat recent change to the OpenLineage schema resulted in output facets being recorded in a new field- one that +Marquez is not yet reading from. The old, deprecated facet reports the output stats incorrectly. An upcoming bugfix +should correct the stats view so that we can see the number of rows written as well as the number of output bytes (the +statistics are actually recorded correctly- the API simply needs to start returning the correct values). + +You may have noticed the `VERSIONS` tab on the bottom bar. We can click it, but since the job has only ever run once, +we’ll only see one version. Clicking on the version, we’ll see the same schema and statistics facets, but specific +to the version we clicked. + +![Marquez output dataset version info](./marquez_output_dataset_version.png) + +In production, this dataset would have many versions, as each time the job runs a new version of the dataset is created. +This allows us to track changes to the statistics and schema over time, again aiding in debugging slow jobs (suddenly, +we started writing 50% more records!) or data quality issues (suddenly, we’re only writing half as many records as +normal!) and job failures (somebody changed the output schema and downstream jobs are failing!). + +The final job in the UI is a HashAggregate job- this represents the `count()` method we called at the end to show the +number of records in the dataset. Rather than a `count()`, this could easily be a `toPandas()` call or some other job +that reads and processes that data- perhaps storing output back into GCS or updating a Postgres database or publishing a +new model, etc. Regardless of where the output gets stored, the OpenLineage integration allows you to see the entire +lineage graph, unifying datasets in object stores, relational databases, and more traditional data warehouses. + +[![XKCD 2347](./dependency.png)](https://xkcd.com/2347/) + +The Spark integration is still a work in progress, but users are already getting insights into their graphs of datasets +stored in object stores like S3, GCS, and Azure Blob Storage, as well as BigQuery and relational databases like +Postgres. Now with Spark 3.1 supported, we can gain visibility into more environments, like Databricks, EMR, and +Dataproc clusters. + +Data lineage gives visibility to the (hopefully) high quality, (hopefully) regularly updated datasets that everyone +depends on, maybe without even realizing it. Spark helped usher in a welcome age of data democratization. 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Recognizing how telemetry data is connected across service layers is key to understanding and mitigating complex distributed failures in today’s environments. +OpenTelemetry is the standard that allows collection of telemetry data in a uniform, vendor-agnostic way across services and databases. For example, it enables the understanding of dependencies between microservices, facilitating investigation into how a single failure might impact services several layers removed. +The creation of OpenTelemetry removed the need for every monitoring, tracing analysis and log indexing platform to create unique integrations to collect that information from the environment. + +## Observability in the Data world + +The data world is organized in a slightly different manner. Services strive for high availability and expose a contract to be requested from. Data pipelines consume datasets and produce datasets. They could be executed as batch processes or using streaming engines but their fundamental contract is to consume data from given inputs and produce data to given outputs. The contract is now the schema of the dataset and an expectation of a rate of update. + +In this world observability cares about a few things: +- **Is the data being delivered?** We might be happy with data being delivered at an hourly or daily rate but we want to know if the job responsible for this is failing and won’t be updating it at all. As a consequence all the datasets depending on this will also not be updated. Correlated SLA misses likes this must be identified to avoid many teams investigating the same problem independently. +- **Is the data being delivered on time?** Batch processing for example is relatively forgiving and can still deliver outputs according to a time SLA even when it failed and had to retry or was slower than usual because of disruptions in its environment. However critical data will need to be delivered according to pre-defined SLA. We want to be able to understand where in the data pipeline dependencies, a bottleneck caused a delay and resolve the issue. +- **Is the data correct?** Now the worst thing that can happen is not a data pipeline failing. This case is relatively easy to recover from. Once the issue is fixed and the pipeline restarted, it will typically catch up and get back to normal operation after the delay induced by the failure. The worst case scenario for a data engineer or data scientist, is the pipeline carrying through and producing bad data. This usually propagates to downstream consumers and all over the place. Recovering requires understanding that the data is incorrect (usually using a data quality library like Great Expectations or Deequ), identifying the upstream dataset where the problem originated, identifying the downstream datasets where the problem propagated, and restating all those datasets to the correct result. +- **Auditing what happened:** Another common need whether it’s for compliance or governance reasons is being able to know if specific sensitive datasets are used according to a defined set of rules. This can be used to protect user privacy, comply with financial regulation, or ensure that key metrics are derived from trusted data sources. + +The key common element in all those use cases is understanding dependencies through **data lineage**, just like services care about understanding dependencies through service traces. + +## Differences Between the Data world and the service world + +If the data world has exactly the same needs for observability than the service world, there are key differences between the two that create the need for a different API to instrument data pipelines. + +### Overall dependency structure: + +- **Services** dependencies can vary at the request level. Different requests to the same service may trigger very different downstream requests to other services. Service logic may create very different dependency patterns depending on input, timing and context. Services depend on other services that can be persistent or stateless. +- **Data** pipelines tend to be expressed in terms of a transformation from a defined set of input datasets to one or several output datasets. Their input/output structure tends to be a lot more stable and not vary much from record to record in the dataset. It’s effectively a bigraph: jobs consume datasets and datasets are produced by jobs. + +### Push vs Pull: + + - **Services** send or push requests to downstream services. Whether it’s synchronous or asynchronous, they can add a traceid to their request that will be propagated downstream. An upstream request spawns one or more downstream requests in a tree structure. +- **Data** pipelines pull data from the datasets they consume from. They aggregate and join datasets together. The structure of dependencies is typically a Directed Acyclic Graph at the dataset level instead of a tree at the request level. This means that the granularity of updates does not match one to one in a lot of cases. The frequency of updates can be different from one pipeline to the next and does not neatly align with a trace flowing down the dependencies. + +### Granularity of data updates + +- **Services** treat one request at a time and tend to optimize for latency of the request being processed. +- **Data** pipelines consume entire datasets and tend to prioritize throughput over latency. The result output can be combining many records from various inputs. When a service request spawns multiple requests downstream a data pipeline tends to do the opposite at the record level while producing multiple derived datasets. + +## Parallels between OpenLineage and [OpenTelemetry](https://opentelemetry.io/docs/concepts/what-is-opentelemetry/) + +### An API first + +Like OpenTelemetry is an API to collect traces, logs and metrics, OpenLineage is first an API to collect lineage. It is agnostic to the backend collecting the data and aspires to be integrated in every data processing engine. +Data lineage is the equivalent of traces for services. It keeps track of dependencies between datasets and data pipelines and how they change over time. + +### Broad language support + +Like OpenTelemetry, OpenLineage has broad language support through the definition of its API in the standard JSONSchema representation. It also has dedicated clients to simplify using its semantics in the languages most commonly used for data processing (Java and Python). + +### Backend agnostic + +Like OpenTelemetry, OpenLineage allows the implementation of multiple backends to consume lineage events for a variety of use cases. For example Marquez is an Open Source reference implementation that keeps track of all the changes in your environment and will help you understand what happened if something goes wrong. +Other metadata projects like Egeria, DataHub, Atlas or Amundsen can also benefit from OpenLineage. Egeria in particular is committed to support OpenLineage as a Metadata bus. +Like OpenTelemetry, anybody can consume and leverage OpenLineage events. + +### Integrates with popular frameworks and libraries + +Like OpenTelemetry, OpenLineage aspires to be integrated in every data processing tool in the ecosystem. It also provides integration with popular tools that are not integrated yet. For example today you can cover Apache Spark, BigQuery, Snowflake, Redshift, Apache Airflow and others. + +### OpenLineage specific capabilities + +In addition to those, OpenLineage is extensible to cover various aspects of metadata that are specific to the data world. OpenLineage defines a notion of facet that lets attach well defined pieces of metadata to the OpenLineage entities (Jobs, Runs and Datasets). Facets can be either part of the core spec or be defined as custom facets by third parties. This flexible mechanism lets define independent specs for dataset schema, query profiles or data quality metrics for example. But this is a topic for another post. + + diff --git a/blog/operators-and-extractors-technical-deep-dive/banner.svg b/blog/operators-and-extractors-technical-deep-dive/banner.svg new file mode 100644 index 0000000000..34572da652 --- /dev/null +++ b/blog/operators-and-extractors-technical-deep-dive/banner.svg @@ -0,0 +1,60 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/operators-and-extractors-technical-deep-dive/image.svg b/blog/operators-and-extractors-technical-deep-dive/image.svg new file mode 100644 index 0000000000..080c0a8a5c --- /dev/null +++ b/blog/operators-and-extractors-technical-deep-dive/image.svg @@ -0,0 +1,55 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/operators-and-extractors-technical-deep-dive/index.mdx b/blog/operators-and-extractors-technical-deep-dive/index.mdx new file mode 100644 index 0000000000..fab3e08615 --- /dev/null +++ b/blog/operators-and-extractors-technical-deep-dive/index.mdx @@ -0,0 +1,47 @@ +--- +title: How Operators and Extractors Work Under-the-Hook +date: 2022-09-07 +author: Benji Lampel +image: ./image.svg +banner: ./banner.svg +description: A technical deep-dive on how the Airflow OSS and OpenLineage OSS projects interact. +--- +A technical deep-dive on how the Airflow OSS and OpenLineage OSS projects interact. + +![](./banner.svg#full-width) + + + +## Overview + +Airflow Operators and OpenLineage Extractors have a specific, if quirky, way of working together. Recently, the way they work together has seen a bit of an overhaul, and the new SQL Check Extractors added a new and unique way that the extractors work and interact with operators. In this blog, we'll demystify these relationships. + +Note: This blog post describes the relationships of the operators and extractors only for `Airflow>=2.3` and `OpenLineage>=0.12.0`. + +## Integration + +### The Operator and the Extractor + +Some quick definitions are in order before we continue. + +The Airflow Operator defines a task, which is the unit of work in Airflow. All operators inherit from the `BaseOperator`, and in addition to taking the arguments of the `BaseOperator`, they can take arguments specific to the kind of task they are going to perform, such as a specific `conn_id` to connect to a datasource or a dictionary of checks to perform on that datasource. + +The OpenLineage Extractor is somewhat analogous to the Airflow Operator: it is a unit of work in OpenLineage, which takes the relevant input and output data from an operator, creates OpenLineage data facets, and sends those facets to be displayed in Marquez or Datakin. Each extractor maps to a specific set of operators via the `get_operator_classnames()` class method. The extractors all inherit from a `BaseExtractor`, which defines a few abstract methods, importantly `execute()` and `execute_on_complete()`. + +Briefly, the two other major OpenLineage constructs in this story are the `ExtractorManager`, which is responsible for identifying the correct extractor to use, and the `Listener`, which is the connecting piece between OpenLineage and Airflow. + +### Interplay + +Next, we'll walk through what happens when an Airflow instance with OpenLineage support runs a DAG, and how that operator data makes it to the Marquez or Datakin UI. + +First, a DAG is born. When the DAG is run, the scheduler runs the operators in order by calling their `execute()` method. This is the first time the OpenLineage `Listener` responds. Triggered by the `execute()` event, it calls the `Manager`, which identifies the correct extractor based on the `task_id`. Then the `Extractor`'s `execute()` method is run, potentially returning lineage data in the form of a metadata object. When the operator is done--either succeeded or failed--, the `Listener` calls the `Manager` again, and this time the `Manager` triggers the `Extractor`'s `execute_on_complete()` method, which may also return metadata based on the result of the task. The metadata object is then sent to Marquez or Datakin, where the data is displayed. + +### SQL Check Operators/Extractors + +The `SQLCheckOperators` and `SQLCheckExtractors` work slightly differently than the interplay outlined above. The biggest difference is that the `SQLCheckExtractors` all inherit from a `BaseSqlCheckExtractor`, which in turn *dynamically* inherits from the appropriate extractor at run time. The appropriate extractor is always some existing SQL database extractor. The `BaseSqlCheckExtractor` itself only implements the `extract_on_complete()` method by determining whether the super class’s `extract()` or `extract_on_complete()` method should be run to gather metadata. The `_get_input_facets()` methods are all implemented by the particular check extractors, and are called in the super class’s `extract()` or `extract_on_complete()` method. + +The dynamic inheritance is done by defining the `SQLCheckExtractors` inside the `get_check_extractors()` function that takes a class as a parameter and passes that class to the constructor of the `BaseSqlCheckExtractor`. When a `SQLCheckOperator` is run, and the `Manager` searches for the correct extractor to use, it calls `instantiate_abstract_extractors()` with the given task instance. + +In this function, the task instance is used to find the correct extractor that will be the superclass of the `BaseSqlCheckOperator`. To do this, the function uses a set of hard-coded operator names whose extractors will dynamically inherit from the found superclass. Currently, this list is the set of `SQLCheckOperator`s, which corresponds to a dictionary of extractor keys and `conn_type` values. The given task’s class name is checked against the set of operator names, and if it is in the set, a loop compares the existing extractor’s corresponding `conn_type` from the aforementioned dictionary to the given task instance’s `conn_type` retrieved from Airflow connections. If there’s a match, the `get_check_extractors()` method is called with the matched extractor, instantiating all the operators with the correct superclass. + +The `SQLCheckExtractors` only rely on the `extract_on_complete()` method, as the values needed from the operators, i.e. the results of the query and the success or failures of the checks, are only available after the operator completes. diff --git a/blog/python-client/banner.svg b/blog/python-client/banner.svg new file mode 100644 index 0000000000..642e9e3e63 --- /dev/null +++ b/blog/python-client/banner.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/python-client/image.svg b/blog/python-client/image.svg new file mode 100644 index 0000000000..5c53157889 --- /dev/null +++ b/blog/python-client/image.svg @@ -0,0 +1,41 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blog/python-client/index.mdx b/blog/python-client/index.mdx new file mode 100644 index 0000000000..e5d215c6fb --- /dev/null +++ b/blog/python-client/index.mdx @@ -0,0 +1,133 @@ +--- +title: The Python Client -- the Foundation of OpenLineage Integrations +date: 2022-07-29 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: The Python client enables users to create custom integrations. +--- +The Python client enables users to create custom integrations. + +![](./banner.svg#full-width) + + + +### Introduction + +Thanks to the [OpenLineage](https://github.com/OpenLineage/OpenLineage) community’s active work on [integrations](https://github.com/OpenLineage/OpenLineage/tree/main/integration), the pursuit of lineage is getting more efficient and effective all the time. And our growing list of partners and adapters makes OpenLineage plenty powerful out of the box. At the same time, the nature of the data engineering field means that lineage capture is an ongoing process – simply put, the work of lineage is never done. + +Hence, as lineage capture becomes integral to your pipelines, situations can arise that require new custom integrations. Enter the [Python client](https://github.com/OpenLineage/OpenLineage/tree/main/client/python), one of two built-in clients included in the project (the other being the [Java client](https://github.com/OpenLineage/OpenLineage/tree/main/client/java)). The OpenLineage spec is defined using JSON schema, but we have created these clients so that new integrations do not have to reinvent the wheel. + +OpenLineage’s Python client enables the creation of lineage metadata events with Python code. The core data structures currently offered by the client include the `RunEvent`, `RunState`, `Run`, `Job`, `Dataset`, and `Transport` classes. These either configure or collect data for the emission of lineage events. + +In the history of the project, the client has been useful in helping us avoid unnecessary duplication of code. It is also integral to OpenLineage’s existing integrations, serving as the basis of the Airflow and dbt integrations, for example. It could also act as the foundation of your own custom integration should you need to write one. (Another use case: tests for a new Airflow extractor.) + +For this reason, an existing integration can serve as a useful example of how to use the client to write a new integration (and, hopefully, [contribute it](https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md) back to the project!). What follows is an overview of the Python client and the dbt integration, which uses the Python client. You’ll see how the client receives metadata from dbt to make it available to a consumer of OpenLineage such as Microsoft Purview, Amundsen, Astronomer, Egeria or Marquez. + +### Python Client Data Structures + +The core structures of the client organize metadata about the foundational objects of the OpenLineage spec: runs, jobs and datasets. + +A `dataset` is a class consisting of a `name`, `namespace` and, optionally, `facets` array: + +``` +@attr.s +class Dataset: + namespace: str = attr.ib() + name: str - attr.ib() + Facets: Dict = attr.ib(factory=dict) +``` + +The same goes for a `job`: + +``` +@attr.s +class Job: + namespace: str = attr.ib() + name: str - attr.ib() + Facets: Dict = attr.ib(factory=dict) +``` + +A `RunEvent` sends the time, state, job, run, producer, input and output information needed to construct an OpenLineage job run event: + +``` +@attr.s +class RunEvent: + eventType: RunState = attr.ib(validator=attr.validators.in_(RunState)) + eventTime: str = attr.ib() + run: Run = attr.ib() + job: Job = attr.ib() + producer: str = attr.ib() + inputs: Optional[List[Dataset]] = attr.ib(factory=list) + outputs: Optional[List[Dataset]] = attr.ib(factory=list) +``` +### The OpenLineage-dbt Integration + +At a high level, the [dbt integration](https://github.com/OpenLineage/OpenLineage/tree/main/integration/dbt) uses the Python client to push metadata to the OpenLineage backend. The metadata it makes available comprises the run lifecycle, including any dataset inputs and outputs accessed during a job run. + +In the `dbt-ol` [script](https://github.com/OpenLineage/OpenLineage/blob/main/integration/dbt/scripts/dbt-ol), the integration uses the project’s `ParentRunMetadata` and `DbtArtifactProcessor` classes, both of which can be found in the OpenLineage common integration, to parse metadata from the dbt `manifest` and `run_result` in order to produce OpenLineage events: + +``` +from openlineage.common.provider.dbt import DbtArtifactProcessor, ParentRunMetadata + +#… + +if parent_id: + parent_namespace, parent_job_name, parent_run_id = parent_id.split(‘/’) + parent_run_metadata = ParentRunMetadata( + run_id=parent_run_id, + job_name=parent_job_name, + job_namespace=parent_namespace + ) + +processor = DbtArtifactProcessor( + producer=PRODUCER, + target=target, + job_namespace=job_namespace, + project_dir=project_dir, + profile_name=profile_name, + logger=logger +) +``` + +The integration uses a wrapper for dbt runs because start and complete events are not emitted until execution concludes: + +``` +dbt_run_event = dbt_run_event_start( + job_name=f“dbt-run-{processor.project[‘name’]}”, + job_namespace=job_namespace, + parent_run_metadata=parent_run_metadata +) + +dbt_run_metadata = ParentRunMetadata( + run_id=dbt_run_event.run.runId, + job_name=dbt_run_event.job.name, + job_namespace=dbt_run_event.job.namespace +) + +processor.dbt_run_metadata = dbt_run_metadata +``` + +After executing dbt, the script parses the metadata using the processor and emits a run event: + +``` +events = processor.parse().events() + +client.emit(dbt_run_event_end( + run_id=dbt_run_metadata.run_id, + job_namespace=dbt_run_metadata.job_namespace, + job_name=dbt_run_metadata.job_name, + parent_run_metadata=parent_run_metadata + )) +logger.info(f"Emitted {len(events) + 2} openlineage events") +``` + +### Additional Resources + +Check out the source code here: https://github.com/OpenLineage/OpenLineage/tree/main/client/python. + +Interested in contributing to the project? Read our guide for new contributors: https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md. + +Join us on Slack: https://bit.ly/OLslack. + +Attend a community meeting: https://bit.ly/OLwikitsc. diff --git a/blog/whats-in-a-namespace/banner.svg b/blog/whats-in-a-namespace/banner.svg new file mode 100644 index 0000000000..ffaec3b2a3 --- /dev/null +++ b/blog/whats-in-a-namespace/banner.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/whats-in-a-namespace/blog_with_different_namespaces.png b/blog/whats-in-a-namespace/blog_with_different_namespaces.png new file mode 100644 index 0000000000000000000000000000000000000000..d462697b9baa422b254867779138255dbd35d222 GIT binary patch literal 31013 zcmb@t1yo$k@-I3N2ol`gT|;n(;O=h0-Q6{~1_A_kcXyZI?hZkNyYq%~LcVkEee3_$ zTlcc|EcUM5U0u>$Rnz^O5LsyvSZFM00000hCMqZo0Duw$03dyk?}3y&i7;FM06O1P zKtNVZK!8Bj&f3V-!Vmxu4f&n`Av?8?)Y1OJ+d6@S5RGI;;pYG<3dQY%wEu;e1mtrF z0|~`^OgA#u2P&crNH@@|^+J?N;?N^mi!a>K0(|W7A2PDepF0qak4N0CS4R&Ityvz9 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/dev/null +++ b/blog/whats-in-a-namespace/index.mdx @@ -0,0 +1,288 @@ +--- +title: What's in a Namespace? +date: 2023-01-13 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: Namespaces enable powerful insights into distributed workflows. +--- +Namespaces enable powerful insights into distributed workflows. + +![](./banner.svg#full-width) + + + +### Background + +With all due respect to Shakespeare's [Juliet](https://shakespeare.folger.edu/shakespeares-works/romeo-and-juliet/act-2-scene-2/?search=rose/#line-2.2.41), in the [OpenLineage](https://github.com/OpenLineage/OpenLineage) spec at least, names in general -- and namespaces in particular -- are everything. + +OK, that’s an exaggeration, but not by much. The function of namespaces is to provide unique IDs for everything in the lineage graph so that jobs and datasets can be rendered as nodes. This means namespaces make stitching input and output datasets together as pipelines possible – which is to say they effectively make lineage possible. In the broader context of the spec, namespaces reflect the importance of naming and naming conventions to the way OpenLineage constructs lineage. + +![Namespace Selector](./namespace_selector.png) + +In creating pipelines organized according to data sources (in the case of datasets) or schedulers (in the case of jobs), namespaces enable focused insight into data flows, even when datasets and workflows are distributed across an organization. This focus enabled by namespaces is key to the production of useful lineage. If everything lived in a single namespace, every lineage graph would show everything that happened in an ecosystem – and be too cluttered to be useful. + +### Namespaces in the Spec + +A look at the spec provides additional detail about namespaces. In the spec, namespaces are at the top of the hierarchy, which means that they have priority over datasets, jobs, and the graphs that connect them. Namespaces contain graphs, in fact, along with just about everything else in a datasource or scheduler’s domain. Ultimately, this reflects the spec’s bias towards tracking dataset and job transformations. + +To wit: the same code applied to different input datasets results in different jobs (not different runs of the same job). If those jobs share a scheduler, they will also share a namespace – but not a graph, which makes tracking the transformations much easier. Similarly, if different input datasets share a datasource, they will also share a namespace (but not a graph). + +As you can see, the track switching can get a little complicated, but the namespace abstraction has some clear advantages. + +### Namespaces in the Wild + +Consider the common scenario in which multiple teams in an organization maintain pipelines that access the same datasets. Now, imagine trying to collect and display lineage from the organization’s ecosystem without having a way to distinguish between the different pipelines that use the same datasets. The ambiguous metadata would make any graph so cluttered as to be practically meaningless. + +Suffice it to say, without a strategy for naming at that macro level of the ecosystem, creating a meaningful graph and tracking transformations is much more difficult. Namespaces also ensure that lineage is meaningful irrespective of the various sources of a job’s metadata. A scope above the dataset and run makes heterogeneous, holistic lineage possible in the case of datasets and jobs. + +``` +We define the unique name strategy per resource to ensure it is followed uniformly independently from who is producing metadata and we can connect lineage from various sources. +``` + +In sum, namespaces make operational lineage possible – which is, while maybe not everything, close to it. + +### Consulting the Marquez API + +Thanks to the [Marquez API reference](https://marquezproject.github.io/marquez/openapi.html), we know that a namespaces endpoint is available that we can query for all namespaces. + +If you use curl to do so, here’s what you’ll get after building Marquez from source with seed data (using `./docker/up.sh --build --seed`): + +``` +➜ marquez git:(main) ✗ curl -v http://localhost:5000/api/v1/namespaces | jq +{ + "namespaces": [ + { + "name": "default", + "createdAt": "2022-12-07T15:02:24.135154Z", + "updatedAt": "2022-12-07T15:02:24.135154Z", + "ownerName": "anonymous", + "description": "The default global namespace for dataset, job, and run metadata not belonging to a user-specified namespace.", + "isHidden": false + }, + { + "name": "food_delivery", + "createdAt": "2020-02-22T22:42:42Z", + "updatedAt": "2020-02-22T22:42:42Z", + "ownerName": "anonymous", + "description": null, + "isHidden": false + } + ] +} +``` + +The namespaces endpoint returns all the available namespaces, which is helpful because, as we’ll see, so much of the information available from the API requires a namespace. For this reason alone, you might say the namespace is the “root” of the object model. + +Say you want to retrieve one or more datasets from the API. First, you’ll need a namespace: + +``` +➜ marquez git:(main) ✗ curl -v http://localhost:5000/api/v1/namespaces/food_delivery/datasets/public.drivers | jq +{ + "id": { + "namespace": "food_delivery", + "name": "public.drivers" + }, + "type": "DB_TABLE", + "name": "public.drivers", + "physicalName": "public.drivers", + "createdAt": "2020-02-22T22:42:42Z", + "updatedAt": "2020-02-22T22:42:42Z", + "namespace": "food_delivery", + "sourceName": "default", + "fields": [ + { + "name": "id", + "type": "INTEGER", + "tags": [], + "description": "The unique ID of the driver." + }, … +``` +Say you want to retrieve a job. You’ll need a namespace: + +``` +➜ marquez git:(main) ✗ curl -v http://localhost:5000/api/v1/namespaces/food_delivery/jobs/etl_order_status | jq +{ + "id": { + "namespace": "food_delivery", + "name": "etl_order_status" + }, + "type": "BATCH", + "name": "etl_order_status", + "simpleName": "etl_order_status", + "parentJobName": null, + "createdAt": "2020-02-22T22:42:42Z", + "updatedAt": "2020-02-22T22:44:52Z", + "namespace": "food_delivery", + "inputs": [], + "outputs": [ + { + "namespace": "food_delivery", + "name": "public.order_status" + } + ], … +``` +Runs? You’ll need a namespace for those: + +``` +➜ marquez git:(main) ✗ curl -v http://localhost:5000/api/v1/namespaces/food_delivery/jobs/etl_order_status/runs | jq +{ + "runs": [ + { + "id": "b7098939-87f0-4207-878f-dfd8e8804d8a", + "createdAt": "2020-02-22T22:42:42Z", + "updatedAt": "2020-02-22T22:44:52Z", + "nominalStartTime": null, + "nominalEndTime": null, + "state": "COMPLETED", + "startedAt": "2020-02-22T22:42:42Z", + "endedAt": "2020-02-22T22:44:52Z", + "durationMs": 130000, + "args": {}, + "jobVersion": { + "namespace": "food_delivery", + "name": "etl_order_status", + "version": "44ca508b-43cc-392f-bbd2-9ca77d501afa" + }, + "inputVersions": [], + "outputVersions": [ + { + "namespace": "food_delivery", + "name": "public.order_status", + "version": "0c16298c-cbe2-3547-8429-309917290570" + } + ], + "context": { + "sql": "INSERT INTO order_status (id, transitioned_at, status, order_id, customer_id, restaurant_id, driver_id)\n SELECT id, transitioned_at, status, order_id, customer_id, restaurant_id, driver_id\n FROM tmp_order_status;" + }, + "facets": {} + } + ] +} +``` +As the API reveals, namespaces really are key in the spec: they organize and unlock most of the insights OpenLineage has to offer. + +### Dataset Namespaces + +Having explored the thinking behind namespaces and their role in the spec, we can get into how they organize datasets and jobs. Let’s start with datasets, the simpler of the two cases due to the more straightforward way datasets’ namespaces are constructed. + +In short, a dataset’s namespace is always tied to its datasource. As the spec says, `the namespace for a dataset is the unique name for its datasource.` + +Data sources vary, however, so the specific construction of dataset namespaces also varies across datasource types. (But they tend to map to databases.) + +In the case of Postgres, Mysql, and Trino, for example, we derive the namespace of a dataset from a combination of the scheme, host, and port of the service instance: + +``` +* Namespace: postgres://{host}:{port} of the service instance. + * Scheme = postgres + * Authority = {host}:{port} +* Namespace: mysql://{host}:{port} of the service instance. + * Scheme = mysql + * Authority = {host}:{port} +* Namespace: trino://{host}:{port} of the service instance. + * Scheme = trino + * Authority = {host}:{port} +``` +Redshift requires a different strategy. It’s possible to interact with Redshift via SQL and an API, so a Redshift namespace is composed of a cluster identifier, region name and port – the only common unique ID available to both methods: + +``` +* Namespace: redshift://{cluster_identifier}.{region_name}:{port} of the cluster instance. + * Scheme = redshift + * Authority = {cluster_identifier}:{port} +``` +Snowflake and Amazon’s serverless Athena warehouse service, which do not require a port, are even simpler: + +``` +* Namespace: awsathena://athena.{region_name}.amazonaws.com of the service instance. + * Scheme = awsathena + * Authority = athena.{region_name}.amazonaws.com +* Namespace: snowflake://{account name} + * Scheme = snowflake + * Authority = {account name} +``` +And so on. As you can see, the provenance of dataset namespaces is pretty straightforward: it’s the data source. + +That said, sometimes deriving the data source of a dataset is not a simple operation. Some datasets can be identified two different ways, for example. A Spark dataset can be written using a Hive metastore and table name but read using the physical location of the data. Before we added the [`SymlinksDatasetFacet`](https://github.com/OpenLineage/OpenLineage/blob/main/spec/facets/SymlinksDatasetFacet.json), this naming conflict could break the lineage graph. Symlinks both provide alternative dataset names as a workaround in such cases and contain extra information about the datasets. + +### Job Namespaces + +We’ve seen that for datasets the namespace is determined by the data source. But jobs are a different animal, so their namespaces are also different. How is a job’s namespace derived? + +As in the case of datasets, the unique naming of jobs is essential, and a job’s unique name consists of a namespace and name. Unlike datasets, jobs descend from schedulers, not data sources. Also unlike datasets, jobs are reducible: a job is composed of executions, or runs (as you can see from the “Historial de Ejecuciones” tab – if you were to take the new language switcher for a spin and select Spanish, that is!). + +![Historial de Ejecuciones Tab](./historial_de_ejecuciones.png) + +Consulting [the spec](https://github.com/OpenLineage/OpenLineage/blob/main/spec/Naming.md), we find more detail about the naming of jobs: + +``` +Jobs have a name that is unique to them in their namespace by construction. +The Namespace is the root of the naming hierarchy. The job name is constructed to identify the job within that namespace. +Example: +* Airflow: + * Namespace: the namespace is assigned to the airflow instance. Ex: airflow-staging, airflow-prod + * Job: each task in a DAG is a job. name: {dag name}.{task name} +* Spark: + * Namespace: the namespace is provided as a configuration parameter as in airflow. If there's a parent job, we use the same namespace, otherwise it is provided by configuration. + * Spark app job name: the spark.app.name + * Spark action job name: {spark.app.name}.{node.name} +``` +So, while for datasets it’s all about the datasource, for jobs it’s all about the scheduler. And the `ParentRun` facet makes tracking job namespaces possible. + +``` +{ + "run": { + "runId": "run_uuid" + }, + "job": { + "namespace": "job_namespace", + "name": "job_name" + } +} +``` +For all events, if a parent job exists, the facet’s `namespace` value is used to assign a namespace. Otherwise, one is provided by configuration. + +### What's the Point? + +But why bother with dataset namespaces in the first place? One answer to this question gets to what is, for some users, a primary value proposition of OpenLineage. A common use case for lineage collection involves tracking dataset access and transformation across jobs and teams in an organization – for monitoring the use of PII, for example. Tags are supported by OpenLineage and can be used to meet this need, but, depending on how an organization’s ecosystem is constructed, namespaces can also help with this common governance use case. + +Let’s explore a simple example constructed using the [Python client](https://openlineage.io/docs/client/python/). Imagine that a library’s website has two components, a catalog and a blog, and that both features access the same user and profile tables, both of which contain PII. + +![Website Schematic](./website_schematic.png) + +In the spec, a dataset is unique only within a namespace – not across multiple namespaces – so a number of different graphs are possible depending on how the datasets are produced and accessed across an organization. + +For example, if for some reason the `users` and `profiles` tables shared two *different* data sources, the tables would belong to two different namespaces (let’s call them `catalog_project` and `blog_project`). While not a typical scenario, this would result in two different, uncluttered graphs of the multiple flows making use of the shared datasets: + +![Catalog with Different Namespaces](./catalog_with_different_namespaces.png) + +![Blog with Different Namespaces](./blog_with_different_namespaces.png) + +The reason for the simplicity? The `users` and `profiles` tables belong to *both* the `catalog_project` and `blog_project` namespaces. + +A more typical scenario might involve single versions of the tables being produced by one data source, which would assign them to a single OpenLineage namespace. Ironically, a simpler approach like this results in a more complicated visualization. Notice that the graph remains the same regardless of the namespace selected: + +![Catalog with One Namespace](./catalog_with_one_namespace.png) + +![Blog with One Namespace](./blog_with_one_namespace.png) + +One advantage of this architecture is that it results in graphs making clear that the datasets containing PII are shared by the two jobs. Depending on an organization’s needs, developers might also find it more convenient to be able to see both jobs and their shared datasets in the same graph. + +A third scenario might involve the isolation of PII by the use of a dedicated database and, by extension, a dedicated namespace (e.g., `user_data`). In the resulting visualization, the job views above remain the same, but the shared datasets containing PII are now collected in the `user_data` namespace on the datasets page of the Marquez UI: + +![Datasets in Dedicated Namespace](./pii_namespace.png) + +Namespaces offer organizations a range of insights into how their teams are accessing and transforming sensitive data. + +### How to Learn More + +If you’re new to OpenLineage and want to check out namespaces in action, a good entry point is the [Getting Started guide](https://openlineage.io/docs/getting-started). There you can learn about the core model, collect run-level metadata using [Marquez](https://marquezproject.ai/) as the [HTTP backend](https://github.com/OpenLineage/OpenLineage#scope), and explore lineage in the Marquez UI. + +Helpful resources for learning more about the namespaces include the [spec](https://github.com/OpenLineage/OpenLineage/tree/main/spec), where [Naming.md](https://github.com/OpenLineage/OpenLineage/blob/main/spec/Naming.md) is the Rosetta stone for namespace construction and naming conventions in the project. + +We also welcome contributions to the project. One of the existing [integrations](https://github.com/OpenLineage/OpenLineage/tree/main/integration) might be a good place to start. Our growing list of partners includes Airflow, dbt, Dagster and Flink. + +Sound fun? Check out the [new contributor guide](https://github.com/MarquezProject/marquez/blob/main/CONTRIBUTING.md) to get started. + +### Acknowledgments + +Ross Turk ([@rossturk](https://github.com/rossturk)) and Paweł Leszczyński ([@pawel-big-lebowski](https://github.com/pawel-big-lebowski)) contributed valuable feedback and suggestions. 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"react-dom": "^17.0.2" + "react-dom": "^17.0.2", + "react-feather": "^2.0.9", + "react-markdown": "^8.0.5", + "tailwind-theme-switcher": "^1.0.2", + "tailwindcss": "^2.2.16" }, "devDependencies": { "@docusaurus/module-type-aliases": "2.0.1", diff --git a/plugins/home-blog-plugin.js b/plugins/home-blog-plugin.js new file mode 100644 index 0000000000..851322dd5d --- /dev/null +++ b/plugins/home-blog-plugin.js @@ -0,0 +1,50 @@ +const blogPluginExports = require("@docusaurus/plugin-content-blog"); + +const defaultBlogPlugin = blogPluginExports.default; + +async function blogPluginExtended(...pluginArgs) { + const blogPluginInstance = await defaultBlogPlugin(...pluginArgs); + + return { + // Add all properties of the default blog plugin so existing functionality is preserved + ...blogPluginInstance, + /** + * Override the default `contentLoaded` hook to access blog posts data + */ + contentLoaded: async function (data) { + const blogPosts = data.allContent['docusaurus-plugin-content-blog'].default.blogPosts; + // Get the 6 latest blog posts + const recentPosts = [...blogPosts].splice(0, 6); + + data.actions.addRoute({ + path: "/", + exact: true, + + // The component to use for the "Home" page route + component: "@site/src/pages/home.tsx", + + // These are the props that will be passed to our "Home" page component + modules: { + recentPosts: recentPosts.map((post) => ({ + content: { + __import: true, + // The markdown file for the blog post will be loaded by webpack + path: post.metadata.source, + query: { + truncated: true, + }, + }, + })), + }, + }); + + // Call the default overridden `contentLoaded` implementation + return blogPluginInstance.contentLoaded(data); + }, + }; +} + +module.exports = { + ...blogPluginExports, + default: blogPluginExtended, +}; \ No newline at end of file diff --git a/src/components/item-blog.tsx b/src/components/item-blog.tsx new file mode 100644 index 0000000000..00d04f92c8 --- /dev/null +++ b/src/components/item-blog.tsx @@ -0,0 +1,44 @@ +import React, { useState } from "react" +import { Link } from "react-router-dom"; +import { Calendar } from "react-feather" + +export const ItemBlog = ({ data }) => { + + const [focused, changeFocused] = useState(false); + + const getDate = (date) => new Date(date).toLocaleDateString() // TODO move to moment and move to utils + + return ( +
+
+ changeFocused(true)} onBlur={() => changeFocused(false)} + style={{ textDecoration: 'none' }} + > +
+ {data.assets.image ? + : + + } +
+
+

+ {data.frontMatter.title} +

+
+ + {getDate(data.metadata.date)} by {data.frontMatter.author} +
+

+ {data.frontMatter.description} +

+
+ +
+
+ ) +} + +export default ItemBlog; \ No newline at end of file diff --git a/src/components/item-integration.tsx b/src/components/item-integration.tsx new file mode 100644 index 0000000000..6e69faca56 --- /dev/null +++ b/src/components/item-integration.tsx @@ -0,0 +1,46 @@ +import React from "react" +import { ArrowRight } from "react-feather" +export const ItemIntegration = ({ data, even }) => { + + let datasources = data.datasources.split(',') + + let rowList = datasources.map((datasource, index) => { + return ( + + {index === 0 && ( + +
+

{data.description}

+ + )} + + {index === 0 && ( + + {data.version.split(',').map((item, i) =>

{item}

)} + + )} + +

{datasource}

+ + {index === 0 && ( + + + + )} + + ) + }) + + return rowList +} + +export default ItemIntegration; \ No newline at end of file diff --git a/src/components/ui.tsx b/src/components/ui.tsx new file mode 100644 index 0000000000..f59e5c64c9 --- /dev/null +++ b/src/components/ui.tsx @@ -0,0 +1,94 @@ +import React, { useState } from "react" +import { Link } from "./utils" + +type ButtonProps = { title: string, to?: string, type?: any, label?: string, disabled?: boolean, iconLeft?: JSX.Element, iconRight?: JSX.Element, className?: string }; +const Button: React.FC = props => { + const { title, to, type, label, disabled } = props + + let innerComponents = ( + + {props.iconLeft && ( + {props.iconLeft} + )} + {props.title} + {props.iconRight && ( + {props.iconRight} + )} + + ) + + + if(type) { + const b = type.split(","); + const t = b[1] ? b[1] : "button" + const dis = disabled === undefined ? false: disabled + if (b[0] === "button") { + return + } + if (b[0] === "extbutton") { + console.log(innerComponents) + return ( + + + + ) + } + } + return ( + + {innerComponents} + + ) +} + +const TextInput = ({ label, type = "text", name, onChange, footer }) => { + const [focused, changeFocused] = useState(false) + + let elem = ( + changeFocused(true)} + onBlur={() => changeFocused(false)} + onChange={onChange} + aria-label={name} + /> + ) + + if (type === "textarea") { + elem = ( + "; + support.noCloneChecked = !!div.cloneNode( true ).lastChild.defaultValue; + + // Support: IE <=9 only + // IE <=9 replaces "; + support.option = !!div.lastChild; +} )(); + + +// We have to close these tags to support XHTML (#13200) +var wrapMap = { + + // XHTML parsers do not magically insert elements in the + // same way that tag soup parsers do. So we cannot shorten + // this by omitting or other required elements. + thead: [ 1, "", "
" ], + col: [ 2, "", "
" ], + tr: [ 2, "", "
" ], + td: [ 3, "", "
" ], + + _default: [ 0, "", "" ] +}; + +wrapMap.tbody = wrapMap.tfoot = wrapMap.colgroup = wrapMap.caption = wrapMap.thead; +wrapMap.th = wrapMap.td; + +// Support: IE <=9 only +if ( !support.option ) { + wrapMap.optgroup = wrapMap.option = [ 1, "" ]; +} + + +function getAll( context, tag ) { + + // Support: IE <=9 - 11 only + // Use typeof to avoid zero-argument method invocation on host objects (#15151) + var ret; + + if ( typeof context.getElementsByTagName !== "undefined" ) { + ret = context.getElementsByTagName( tag || "*" ); + + } else if ( typeof context.querySelectorAll !== "undefined" ) { + ret = context.querySelectorAll( tag || "*" ); + + } else { + ret = []; + } + + if ( tag === undefined || tag && nodeName( context, tag ) ) { + return jQuery.merge( [ context ], ret ); + } + + return ret; +} + + +// Mark scripts as having already been evaluated +function setGlobalEval( elems, refElements ) { + var i = 0, + l = elems.length; + + for ( ; i < l; i++ ) { + dataPriv.set( + elems[ i ], + "globalEval", + !refElements || dataPriv.get( refElements[ i ], "globalEval" ) + ); + } +} + + +var rhtml = /<|&#?\w+;/; + +function buildFragment( elems, context, scripts, selection, ignored ) { + var elem, tmp, tag, wrap, attached, j, + fragment = context.createDocumentFragment(), + nodes = [], + i = 0, + l = elems.length; + + for ( ; i < l; i++ ) { + elem = elems[ i ]; + + if ( elem || elem === 0 ) { + + // Add nodes directly + if ( toType( elem ) === "object" ) { + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( nodes, elem.nodeType ? [ elem ] : elem ); + + // Convert non-html into a text node + } else if ( !rhtml.test( elem ) ) { + nodes.push( context.createTextNode( elem ) ); + + // Convert html into DOM nodes + } else { + tmp = tmp || fragment.appendChild( context.createElement( "div" ) ); + + // Deserialize a standard representation + tag = ( rtagName.exec( elem ) || [ "", "" ] )[ 1 ].toLowerCase(); + wrap = wrapMap[ tag ] || wrapMap._default; + tmp.innerHTML = wrap[ 1 ] + jQuery.htmlPrefilter( elem ) + wrap[ 2 ]; + + // Descend through wrappers to the right content + j = wrap[ 0 ]; + while ( j-- ) { + tmp = tmp.lastChild; + } + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( nodes, tmp.childNodes ); + + // Remember the top-level container + tmp = fragment.firstChild; + + // Ensure the created nodes are orphaned (#12392) + tmp.textContent = ""; + } + } + } + + // Remove wrapper from fragment + fragment.textContent = ""; + + i = 0; + while ( ( elem = nodes[ i++ ] ) ) { + + // Skip elements already in the context collection (trac-4087) + if ( selection && jQuery.inArray( elem, selection ) > -1 ) { + if ( ignored ) { + ignored.push( elem ); + } + continue; + } + + attached = isAttached( elem ); + + // Append to fragment + tmp = getAll( fragment.appendChild( elem ), "script" ); + + // Preserve script evaluation history + if ( attached ) { + setGlobalEval( tmp ); + } + + // Capture executables + if ( scripts ) { + j = 0; + while ( ( elem = tmp[ j++ ] ) ) { + if ( rscriptType.test( elem.type || "" ) ) { + scripts.push( elem ); + } + } + } + } + + return fragment; +} + + +var + rkeyEvent = /^key/, + rmouseEvent = /^(?:mouse|pointer|contextmenu|drag|drop)|click/, + rtypenamespace = /^([^.]*)(?:\.(.+)|)/; + +function returnTrue() { + return true; +} + +function returnFalse() { + return false; +} + +// Support: IE <=9 - 11+ +// focus() and blur() are asynchronous, except when they are no-op. +// So expect focus to be synchronous when the element is already active, +// and blur to be synchronous when the element is not already active. +// (focus and blur are always synchronous in other supported browsers, +// this just defines when we can count on it). +function expectSync( elem, type ) { + return ( elem === safeActiveElement() ) === ( type === "focus" ); +} + +// Support: IE <=9 only +// Accessing document.activeElement can throw unexpectedly +// https://bugs.jquery.com/ticket/13393 +function safeActiveElement() { + try { + return document.activeElement; + } catch ( err ) { } +} + +function on( elem, types, selector, data, fn, one ) { + var origFn, type; + + // Types can be a map of types/handlers + if ( typeof types === "object" ) { + + // ( types-Object, selector, data ) + if ( typeof selector !== "string" ) { + + // ( types-Object, data ) + data = data || selector; + selector = undefined; + } + for ( type in types ) { + on( elem, type, selector, data, types[ type ], one ); + } + return elem; + } + + if ( data == null && fn == null ) { + + // ( types, fn ) + fn = selector; + data = selector = undefined; + } else if ( fn == null ) { + if ( typeof selector === "string" ) { + + // ( types, selector, fn ) + fn = data; + data = undefined; + } else { + + // ( types, data, fn ) + fn = data; + data = selector; + selector = undefined; + } + } + if ( fn === false ) { + fn = returnFalse; + } else if ( !fn ) { + return elem; + } + + if ( one === 1 ) { + origFn = fn; + fn = function( event ) { + + // Can use an empty set, since event contains the info + jQuery().off( event ); + return origFn.apply( this, arguments ); + }; + + // Use same guid so caller can remove using origFn + fn.guid = origFn.guid || ( origFn.guid = jQuery.guid++ ); + } + return elem.each( function() { + jQuery.event.add( this, types, fn, data, selector ); + } ); +} + +/* + * Helper functions for managing events -- not part of the public interface. + * Props to Dean Edwards' addEvent library for many of the ideas. + */ +jQuery.event = { + + global: {}, + + add: function( elem, types, handler, data, selector ) { + + var handleObjIn, eventHandle, tmp, + events, t, handleObj, + special, handlers, type, namespaces, origType, + elemData = dataPriv.get( elem ); + + // Only attach events to objects that accept data + if ( !acceptData( elem ) ) { + return; + } + + // Caller can pass in an object of custom data in lieu of the handler + if ( handler.handler ) { + handleObjIn = handler; + handler = handleObjIn.handler; + selector = handleObjIn.selector; + } + + // Ensure that invalid selectors throw exceptions at attach time + // Evaluate against documentElement in case elem is a non-element node (e.g., document) + if ( selector ) { + jQuery.find.matchesSelector( documentElement, selector ); + } + + // Make sure that the handler has a unique ID, used to find/remove it later + if ( !handler.guid ) { + handler.guid = jQuery.guid++; + } + + // Init the element's event structure and main handler, if this is the first + if ( !( events = elemData.events ) ) { + events = elemData.events = Object.create( null ); + } + if ( !( eventHandle = elemData.handle ) ) { + eventHandle = elemData.handle = function( e ) { + + // Discard the second event of a jQuery.event.trigger() and + // when an event is called after a page has unloaded + return typeof jQuery !== "undefined" && jQuery.event.triggered !== e.type ? + jQuery.event.dispatch.apply( elem, arguments ) : undefined; + }; + } + + // Handle multiple events separated by a space + types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; + t = types.length; + while ( t-- ) { + tmp = rtypenamespace.exec( types[ t ] ) || []; + type = origType = tmp[ 1 ]; + namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); + + // There *must* be a type, no attaching namespace-only handlers + if ( !type ) { + continue; + } + + // If event changes its type, use the special event handlers for the changed type + special = jQuery.event.special[ type ] || {}; + + // If selector defined, determine special event api type, otherwise given type + type = ( selector ? special.delegateType : special.bindType ) || type; + + // Update special based on newly reset type + special = jQuery.event.special[ type ] || {}; + + // handleObj is passed to all event handlers + handleObj = jQuery.extend( { + type: type, + origType: origType, + data: data, + handler: handler, + guid: handler.guid, + selector: selector, + needsContext: selector && jQuery.expr.match.needsContext.test( selector ), + namespace: namespaces.join( "." ) + }, handleObjIn ); + + // Init the event handler queue if we're the first + if ( !( handlers = events[ type ] ) ) { + handlers = events[ type ] = []; + handlers.delegateCount = 0; + + // Only use addEventListener if the special events handler returns false + if ( !special.setup || + special.setup.call( elem, data, namespaces, eventHandle ) === false ) { + + if ( elem.addEventListener ) { + elem.addEventListener( type, eventHandle ); + } + } + } + + if ( special.add ) { + special.add.call( elem, handleObj ); + + if ( !handleObj.handler.guid ) { + handleObj.handler.guid = handler.guid; + } + } + + // Add to the element's handler list, delegates in front + if ( selector ) { + handlers.splice( handlers.delegateCount++, 0, handleObj ); + } else { + handlers.push( handleObj ); + } + + // Keep track of which events have ever been used, for event optimization + jQuery.event.global[ type ] = true; + } + + }, + + // Detach an event or set of events from an element + remove: function( elem, types, handler, selector, mappedTypes ) { + + var j, origCount, tmp, + events, t, handleObj, + special, handlers, type, namespaces, origType, + elemData = dataPriv.hasData( elem ) && dataPriv.get( elem ); + + if ( !elemData || !( events = elemData.events ) ) { + return; + } + + // Once for each type.namespace in types; type may be omitted + types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; + t = types.length; + while ( t-- ) { + tmp = rtypenamespace.exec( types[ t ] ) || []; + type = origType = tmp[ 1 ]; + namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); + + // Unbind all events (on this namespace, if provided) for the element + if ( !type ) { + for ( type in events ) { + jQuery.event.remove( elem, type + types[ t ], handler, selector, true ); + } + continue; + } + + special = jQuery.event.special[ type ] || {}; + type = ( selector ? special.delegateType : special.bindType ) || type; + handlers = events[ type ] || []; + tmp = tmp[ 2 ] && + new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ); + + // Remove matching events + origCount = j = handlers.length; + while ( j-- ) { + handleObj = handlers[ j ]; + + if ( ( mappedTypes || origType === handleObj.origType ) && + ( !handler || handler.guid === handleObj.guid ) && + ( !tmp || tmp.test( handleObj.namespace ) ) && + ( !selector || selector === handleObj.selector || + selector === "**" && handleObj.selector ) ) { + handlers.splice( j, 1 ); + + if ( handleObj.selector ) { + handlers.delegateCount--; + } + if ( special.remove ) { + special.remove.call( elem, handleObj ); + } + } + } + + // Remove generic event handler if we removed something and no more handlers exist + // (avoids potential for endless recursion during removal of special event handlers) + if ( origCount && !handlers.length ) { + if ( !special.teardown || + special.teardown.call( elem, namespaces, elemData.handle ) === false ) { + + jQuery.removeEvent( elem, type, elemData.handle ); + } + + delete events[ type ]; + } + } + + // Remove data and the expando if it's no longer used + if ( jQuery.isEmptyObject( events ) ) { + dataPriv.remove( elem, "handle events" ); + } + }, + + dispatch: function( nativeEvent ) { + + var i, j, ret, matched, handleObj, handlerQueue, + args = new Array( arguments.length ), + + // Make a writable jQuery.Event from the native event object + event = jQuery.event.fix( nativeEvent ), + + handlers = ( + dataPriv.get( this, "events" ) || Object.create( null ) + )[ event.type ] || [], + special = jQuery.event.special[ event.type ] || {}; + + // Use the fix-ed jQuery.Event rather than the (read-only) native event + args[ 0 ] = event; + + for ( i = 1; i < arguments.length; i++ ) { + args[ i ] = arguments[ i ]; + } + + event.delegateTarget = this; + + // Call the preDispatch hook for the mapped type, and let it bail if desired + if ( special.preDispatch && special.preDispatch.call( this, event ) === false ) { + return; + } + + // Determine handlers + handlerQueue = jQuery.event.handlers.call( this, event, handlers ); + + // Run delegates first; they may want to stop propagation beneath us + i = 0; + while ( ( matched = handlerQueue[ i++ ] ) && !event.isPropagationStopped() ) { + event.currentTarget = matched.elem; + + j = 0; + while ( ( handleObj = matched.handlers[ j++ ] ) && + !event.isImmediatePropagationStopped() ) { + + // If the event is namespaced, then each handler is only invoked if it is + // specially universal or its namespaces are a superset of the event's. + if ( !event.rnamespace || handleObj.namespace === false || + event.rnamespace.test( handleObj.namespace ) ) { + + event.handleObj = handleObj; + event.data = handleObj.data; + + ret = ( ( jQuery.event.special[ handleObj.origType ] || {} ).handle || + handleObj.handler ).apply( matched.elem, args ); + + if ( ret !== undefined ) { + if ( ( event.result = ret ) === false ) { + event.preventDefault(); + event.stopPropagation(); + } + } + } + } + } + + // Call the postDispatch hook for the mapped type + if ( special.postDispatch ) { + special.postDispatch.call( this, event ); + } + + return event.result; + }, + + handlers: function( event, handlers ) { + var i, handleObj, sel, matchedHandlers, matchedSelectors, + handlerQueue = [], + delegateCount = handlers.delegateCount, + cur = event.target; + + // Find delegate handlers + if ( delegateCount && + + // Support: IE <=9 + // Black-hole SVG instance trees (trac-13180) + cur.nodeType && + + // Support: Firefox <=42 + // Suppress spec-violating clicks indicating a non-primary pointer button (trac-3861) + // https://www.w3.org/TR/DOM-Level-3-Events/#event-type-click + // Support: IE 11 only + // ...but not arrow key "clicks" of radio inputs, which can have `button` -1 (gh-2343) + !( event.type === "click" && event.button >= 1 ) ) { + + for ( ; cur !== this; cur = cur.parentNode || this ) { + + // Don't check non-elements (#13208) + // Don't process clicks on disabled elements (#6911, #8165, #11382, #11764) + if ( cur.nodeType === 1 && !( event.type === "click" && cur.disabled === true ) ) { + matchedHandlers = []; + matchedSelectors = {}; + for ( i = 0; i < delegateCount; i++ ) { + handleObj = handlers[ i ]; + + // Don't conflict with Object.prototype properties (#13203) + sel = handleObj.selector + " "; + + if ( matchedSelectors[ sel ] === undefined ) { + matchedSelectors[ sel ] = handleObj.needsContext ? + jQuery( sel, this ).index( cur ) > -1 : + jQuery.find( sel, this, null, [ cur ] ).length; + } + if ( matchedSelectors[ sel ] ) { + matchedHandlers.push( handleObj ); + } + } + if ( matchedHandlers.length ) { + handlerQueue.push( { elem: cur, handlers: matchedHandlers } ); + } + } + } + } + + // Add the remaining (directly-bound) handlers + cur = this; + if ( delegateCount < handlers.length ) { + handlerQueue.push( { elem: cur, handlers: handlers.slice( delegateCount ) } ); + } + + return handlerQueue; + }, + + addProp: function( name, hook ) { + Object.defineProperty( jQuery.Event.prototype, name, { + enumerable: true, + configurable: true, + + get: isFunction( hook ) ? + function() { + if ( this.originalEvent ) { + return hook( this.originalEvent ); + } + } : + function() { + if ( this.originalEvent ) { + return this.originalEvent[ name ]; + } + }, + + set: function( value ) { + Object.defineProperty( this, name, { + enumerable: true, + configurable: true, + writable: true, + value: value + } ); + } + } ); + }, + + fix: function( originalEvent ) { + return originalEvent[ jQuery.expando ] ? + originalEvent : + new jQuery.Event( originalEvent ); + }, + + special: { + load: { + + // Prevent triggered image.load events from bubbling to window.load + noBubble: true + }, + click: { + + // Utilize native event to ensure correct state for checkable inputs + setup: function( data ) { + + // For mutual compressibility with _default, replace `this` access with a local var. + // `|| data` is dead code meant only to preserve the variable through minification. + var el = this || data; + + // Claim the first handler + if ( rcheckableType.test( el.type ) && + el.click && nodeName( el, "input" ) ) { + + // dataPriv.set( el, "click", ... ) + leverageNative( el, "click", returnTrue ); + } + + // Return false to allow normal processing in the caller + return false; + }, + trigger: function( data ) { + + // For mutual compressibility with _default, replace `this` access with a local var. + // `|| data` is dead code meant only to preserve the variable through minification. + var el = this || data; + + // Force setup before triggering a click + if ( rcheckableType.test( el.type ) && + el.click && nodeName( el, "input" ) ) { + + leverageNative( el, "click" ); + } + + // Return non-false to allow normal event-path propagation + return true; + }, + + // For cross-browser consistency, suppress native .click() on links + // Also prevent it if we're currently inside a leveraged native-event stack + _default: function( event ) { + var target = event.target; + return rcheckableType.test( target.type ) && + target.click && nodeName( target, "input" ) && + dataPriv.get( target, "click" ) || + nodeName( target, "a" ); + } + }, + + beforeunload: { + postDispatch: function( event ) { + + // Support: Firefox 20+ + // Firefox doesn't alert if the returnValue field is not set. + if ( event.result !== undefined && event.originalEvent ) { + event.originalEvent.returnValue = event.result; + } + } + } + } +}; + +// Ensure the presence of an event listener that handles manually-triggered +// synthetic events by interrupting progress until reinvoked in response to +// *native* events that it fires directly, ensuring that state changes have +// already occurred before other listeners are invoked. +function leverageNative( el, type, expectSync ) { + + // Missing expectSync indicates a trigger call, which must force setup through jQuery.event.add + if ( !expectSync ) { + if ( dataPriv.get( el, type ) === undefined ) { + jQuery.event.add( el, type, returnTrue ); + } + return; + } + + // Register the controller as a special universal handler for all event namespaces + dataPriv.set( el, type, false ); + jQuery.event.add( el, type, { + namespace: false, + handler: function( event ) { + var notAsync, result, + saved = dataPriv.get( this, type ); + + if ( ( event.isTrigger & 1 ) && this[ type ] ) { + + // Interrupt processing of the outer synthetic .trigger()ed event + // Saved data should be false in such cases, but might be a leftover capture object + // from an async native handler (gh-4350) + if ( !saved.length ) { + + // Store arguments for use when handling the inner native event + // There will always be at least one argument (an event object), so this array + // will not be confused with a leftover capture object. + saved = slice.call( arguments ); + dataPriv.set( this, type, saved ); + + // Trigger the native event and capture its result + // Support: IE <=9 - 11+ + // focus() and blur() are asynchronous + notAsync = expectSync( this, type ); + this[ type ](); + result = dataPriv.get( this, type ); + if ( saved !== result || notAsync ) { + dataPriv.set( this, type, false ); + } else { + result = {}; + } + if ( saved !== result ) { + + // Cancel the outer synthetic event + event.stopImmediatePropagation(); + event.preventDefault(); + return result.value; + } + + // If this is an inner synthetic event for an event with a bubbling surrogate + // (focus or blur), assume that the surrogate already propagated from triggering the + // native event and prevent that from happening again here. + // This technically gets the ordering wrong w.r.t. to `.trigger()` (in which the + // bubbling surrogate propagates *after* the non-bubbling base), but that seems + // less bad than duplication. + } else if ( ( jQuery.event.special[ type ] || {} ).delegateType ) { + event.stopPropagation(); + } + + // If this is a native event triggered above, everything is now in order + // Fire an inner synthetic event with the original arguments + } else if ( saved.length ) { + + // ...and capture the result + dataPriv.set( this, type, { + value: jQuery.event.trigger( + + // Support: IE <=9 - 11+ + // Extend with the prototype to reset the above stopImmediatePropagation() + jQuery.extend( saved[ 0 ], jQuery.Event.prototype ), + saved.slice( 1 ), + this + ) + } ); + + // Abort handling of the native event + event.stopImmediatePropagation(); + } + } + } ); +} + +jQuery.removeEvent = function( elem, type, handle ) { + + // This "if" is needed for plain objects + if ( elem.removeEventListener ) { + elem.removeEventListener( type, handle ); + } +}; + +jQuery.Event = function( src, props ) { + + // Allow instantiation without the 'new' keyword + if ( !( this instanceof jQuery.Event ) ) { + return new jQuery.Event( src, props ); + } + + // Event object + if ( src && src.type ) { + this.originalEvent = src; + this.type = src.type; + + // Events bubbling up the document may have been marked as prevented + // by a handler lower down the tree; reflect the correct value. + this.isDefaultPrevented = src.defaultPrevented || + src.defaultPrevented === undefined && + + // Support: Android <=2.3 only + src.returnValue === false ? + returnTrue : + returnFalse; + + // Create target properties + // Support: Safari <=6 - 7 only + // Target should not be a text node (#504, #13143) + this.target = ( src.target && src.target.nodeType === 3 ) ? + src.target.parentNode : + src.target; + + this.currentTarget = src.currentTarget; + this.relatedTarget = src.relatedTarget; + + // Event type + } else { + this.type = src; + } + + // Put explicitly provided properties onto the event object + if ( props ) { + jQuery.extend( this, props ); + } + + // Create a timestamp if incoming event doesn't have one + this.timeStamp = src && src.timeStamp || Date.now(); + + // Mark it as fixed + this[ jQuery.expando ] = true; +}; + +// jQuery.Event is based on DOM3 Events as specified by the ECMAScript Language Binding +// https://www.w3.org/TR/2003/WD-DOM-Level-3-Events-20030331/ecma-script-binding.html +jQuery.Event.prototype = { + constructor: jQuery.Event, + isDefaultPrevented: returnFalse, + isPropagationStopped: returnFalse, + isImmediatePropagationStopped: returnFalse, + isSimulated: false, + + preventDefault: function() { + var e = this.originalEvent; + + this.isDefaultPrevented = returnTrue; + + if ( e && !this.isSimulated ) { + e.preventDefault(); + } + }, + stopPropagation: function() { + var e = this.originalEvent; + + this.isPropagationStopped = returnTrue; + + if ( e && !this.isSimulated ) { + e.stopPropagation(); + } + }, + stopImmediatePropagation: function() { + var e = this.originalEvent; + + this.isImmediatePropagationStopped = returnTrue; + + if ( e && !this.isSimulated ) { + e.stopImmediatePropagation(); + } + + this.stopPropagation(); + } +}; + +// Includes all common event props including KeyEvent and MouseEvent specific props +jQuery.each( { + altKey: true, + bubbles: true, + cancelable: true, + changedTouches: true, + ctrlKey: true, + detail: true, + eventPhase: true, + metaKey: true, + pageX: true, + pageY: true, + shiftKey: true, + view: true, + "char": true, + code: true, + charCode: true, + key: true, + keyCode: true, + button: true, + buttons: true, + clientX: true, + clientY: true, + offsetX: true, + offsetY: true, + pointerId: true, + pointerType: true, + screenX: true, + screenY: true, + targetTouches: true, + toElement: true, + touches: true, + + which: function( event ) { + var button = event.button; + + // Add which for key events + if ( event.which == null && rkeyEvent.test( event.type ) ) { + return event.charCode != null ? event.charCode : event.keyCode; + } + + // Add which for click: 1 === left; 2 === middle; 3 === right + if ( !event.which && button !== undefined && rmouseEvent.test( event.type ) ) { + if ( button & 1 ) { + return 1; + } + + if ( button & 2 ) { + return 3; + } + + if ( button & 4 ) { + return 2; + } + + return 0; + } + + return event.which; + } +}, jQuery.event.addProp ); + +jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateType ) { + jQuery.event.special[ type ] = { + + // Utilize native event if possible so blur/focus sequence is correct + setup: function() { + + // Claim the first handler + // dataPriv.set( this, "focus", ... ) + // dataPriv.set( this, "blur", ... ) + leverageNative( this, type, expectSync ); + + // Return false to allow normal processing in the caller + return false; + }, + trigger: function() { + + // Force setup before trigger + leverageNative( this, type ); + + // Return non-false to allow normal event-path propagation + return true; + }, + + delegateType: delegateType + }; +} ); + +// Create mouseenter/leave events using mouseover/out and event-time checks +// so that event delegation works in jQuery. +// Do the same for pointerenter/pointerleave and pointerover/pointerout +// +// Support: Safari 7 only +// Safari sends mouseenter too often; see: +// https://bugs.chromium.org/p/chromium/issues/detail?id=470258 +// for the description of the bug (it existed in older Chrome versions as well). +jQuery.each( { + mouseenter: "mouseover", + mouseleave: "mouseout", + pointerenter: "pointerover", + pointerleave: "pointerout" +}, function( orig, fix ) { + jQuery.event.special[ orig ] = { + delegateType: fix, + bindType: fix, + + handle: function( event ) { + var ret, + target = this, + related = event.relatedTarget, + handleObj = event.handleObj; + + // For mouseenter/leave call the handler if related is outside the target. + // NB: No relatedTarget if the mouse left/entered the browser window + if ( !related || ( related !== target && !jQuery.contains( target, related ) ) ) { + event.type = handleObj.origType; + ret = handleObj.handler.apply( this, arguments ); + event.type = fix; + } + return ret; + } + }; +} ); + +jQuery.fn.extend( { + + on: function( types, selector, data, fn ) { + return on( this, types, selector, data, fn ); + }, + one: function( types, selector, data, fn ) { + return on( this, types, selector, data, fn, 1 ); + }, + off: function( types, selector, fn ) { + var handleObj, type; + if ( types && types.preventDefault && types.handleObj ) { + + // ( event ) dispatched jQuery.Event + handleObj = types.handleObj; + jQuery( types.delegateTarget ).off( + handleObj.namespace ? + handleObj.origType + "." + handleObj.namespace : + handleObj.origType, + handleObj.selector, + handleObj.handler + ); + return this; + } + if ( typeof types === "object" ) { + + // ( types-object [, selector] ) + for ( type in types ) { + this.off( type, selector, types[ type ] ); + } + return this; + } + if ( selector === false || typeof selector === "function" ) { + + // ( types [, fn] ) + fn = selector; + selector = undefined; + } + if ( fn === false ) { + fn = returnFalse; + } + return this.each( function() { + jQuery.event.remove( this, types, fn, selector ); + } ); + } +} ); + + +var + + // Support: IE <=10 - 11, Edge 12 - 13 only + // In IE/Edge using regex groups here causes severe slowdowns. + // See https://connect.microsoft.com/IE/feedback/details/1736512/ + rnoInnerhtml = /\s*$/g; + +// Prefer a tbody over its parent table for containing new rows +function manipulationTarget( elem, content ) { + if ( nodeName( elem, "table" ) && + nodeName( content.nodeType !== 11 ? content : content.firstChild, "tr" ) ) { + + return jQuery( elem ).children( "tbody" )[ 0 ] || elem; + } + + return elem; +} + +// Replace/restore the type attribute of script elements for safe DOM manipulation +function disableScript( elem ) { + elem.type = ( elem.getAttribute( "type" ) !== null ) + "/" + elem.type; + return elem; +} +function restoreScript( elem ) { + if ( ( elem.type || "" ).slice( 0, 5 ) === "true/" ) { + elem.type = elem.type.slice( 5 ); + } else { + elem.removeAttribute( "type" ); + } + + return elem; +} + +function cloneCopyEvent( src, dest ) { + var i, l, type, pdataOld, udataOld, udataCur, events; + + if ( dest.nodeType !== 1 ) { + return; + } + + // 1. Copy private data: events, handlers, etc. + if ( dataPriv.hasData( src ) ) { + pdataOld = dataPriv.get( src ); + events = pdataOld.events; + + if ( events ) { + dataPriv.remove( dest, "handle events" ); + + for ( type in events ) { + for ( i = 0, l = events[ type ].length; i < l; i++ ) { + jQuery.event.add( dest, type, events[ type ][ i ] ); + } + } + } + } + + // 2. Copy user data + if ( dataUser.hasData( src ) ) { + udataOld = dataUser.access( src ); + udataCur = jQuery.extend( {}, udataOld ); + + dataUser.set( dest, udataCur ); + } +} + +// Fix IE bugs, see support tests +function fixInput( src, dest ) { + var nodeName = dest.nodeName.toLowerCase(); + + // Fails to persist the checked state of a cloned checkbox or radio button. + if ( nodeName === "input" && rcheckableType.test( src.type ) ) { + dest.checked = src.checked; + + // Fails to return the selected option to the default selected state when cloning options + } else if ( nodeName === "input" || nodeName === "textarea" ) { + dest.defaultValue = src.defaultValue; + } +} + +function domManip( collection, args, callback, ignored ) { + + // Flatten any nested arrays + args = flat( args ); + + var fragment, first, scripts, hasScripts, node, doc, + i = 0, + l = collection.length, + iNoClone = l - 1, + value = args[ 0 ], + valueIsFunction = isFunction( value ); + + // We can't cloneNode fragments that contain checked, in WebKit + if ( valueIsFunction || + ( l > 1 && typeof value === "string" && + !support.checkClone && rchecked.test( value ) ) ) { + return collection.each( function( index ) { + var self = collection.eq( index ); + if ( valueIsFunction ) { + args[ 0 ] = value.call( this, index, self.html() ); + } + domManip( self, args, callback, ignored ); + } ); + } + + if ( l ) { + fragment = buildFragment( args, collection[ 0 ].ownerDocument, false, collection, ignored ); + first = fragment.firstChild; + + if ( fragment.childNodes.length === 1 ) { + fragment = first; + } + + // Require either new content or an interest in ignored elements to invoke the callback + if ( first || ignored ) { + scripts = jQuery.map( getAll( fragment, "script" ), disableScript ); + hasScripts = scripts.length; + + // Use the original fragment for the last item + // instead of the first because it can end up + // being emptied incorrectly in certain situations (#8070). + for ( ; i < l; i++ ) { + node = fragment; + + if ( i !== iNoClone ) { + node = jQuery.clone( node, true, true ); + + // Keep references to cloned scripts for later restoration + if ( hasScripts ) { + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( scripts, getAll( node, "script" ) ); + } + } + + callback.call( collection[ i ], node, i ); + } + + if ( hasScripts ) { + doc = scripts[ scripts.length - 1 ].ownerDocument; + + // Reenable scripts + jQuery.map( scripts, restoreScript ); + + // Evaluate executable scripts on first document insertion + for ( i = 0; i < hasScripts; i++ ) { + node = scripts[ i ]; + if ( rscriptType.test( node.type || "" ) && + !dataPriv.access( node, "globalEval" ) && + jQuery.contains( doc, node ) ) { + + if ( node.src && ( node.type || "" ).toLowerCase() !== "module" ) { + + // Optional AJAX dependency, but won't run scripts if not present + if ( jQuery._evalUrl && !node.noModule ) { + jQuery._evalUrl( node.src, { + nonce: node.nonce || node.getAttribute( "nonce" ) + }, doc ); + } + } else { + DOMEval( node.textContent.replace( rcleanScript, "" ), node, doc ); + } + } + } + } + } + } + + return collection; +} + +function remove( elem, selector, keepData ) { + var node, + nodes = selector ? jQuery.filter( selector, elem ) : elem, + i = 0; + + for ( ; ( node = nodes[ i ] ) != null; i++ ) { + if ( !keepData && node.nodeType === 1 ) { + jQuery.cleanData( getAll( node ) ); + } + + if ( node.parentNode ) { + if ( keepData && isAttached( node ) ) { + setGlobalEval( getAll( node, "script" ) ); + } + node.parentNode.removeChild( node ); + } + } + + return elem; +} + +jQuery.extend( { + htmlPrefilter: function( html ) { + return html; + }, + + clone: function( elem, dataAndEvents, deepDataAndEvents ) { + var i, l, srcElements, destElements, + clone = elem.cloneNode( true ), + inPage = isAttached( elem ); + + // Fix IE cloning issues + if ( !support.noCloneChecked && ( elem.nodeType === 1 || elem.nodeType === 11 ) && + !jQuery.isXMLDoc( elem ) ) { + + // We eschew Sizzle here for performance reasons: https://jsperf.com/getall-vs-sizzle/2 + destElements = getAll( clone ); + srcElements = getAll( elem ); + + for ( i = 0, l = srcElements.length; i < l; i++ ) { + fixInput( srcElements[ i ], destElements[ i ] ); + } + } + + // Copy the events from the original to the clone + if ( dataAndEvents ) { + if ( deepDataAndEvents ) { + srcElements = srcElements || getAll( elem ); + destElements = destElements || getAll( clone ); + + for ( i = 0, l = srcElements.length; i < l; i++ ) { + cloneCopyEvent( srcElements[ i ], destElements[ i ] ); + } + } else { + cloneCopyEvent( elem, clone ); + } + } + + // Preserve script evaluation history + destElements = getAll( clone, "script" ); + if ( destElements.length > 0 ) { + setGlobalEval( destElements, !inPage && getAll( elem, "script" ) ); + } + + // Return the cloned set + return clone; + }, + + cleanData: function( elems ) { + var data, elem, type, + special = jQuery.event.special, + i = 0; + + for ( ; ( elem = elems[ i ] ) !== undefined; i++ ) { + if ( acceptData( elem ) ) { + if ( ( data = elem[ dataPriv.expando ] ) ) { + if ( data.events ) { + for ( type in data.events ) { + if ( special[ type ] ) { + jQuery.event.remove( elem, type ); + + // This is a shortcut to avoid jQuery.event.remove's overhead + } else { + jQuery.removeEvent( elem, type, data.handle ); + } + } + } + + // Support: Chrome <=35 - 45+ + // Assign undefined instead of using delete, see Data#remove + elem[ dataPriv.expando ] = undefined; + } + if ( elem[ dataUser.expando ] ) { + + // Support: Chrome <=35 - 45+ + // Assign undefined instead of using delete, see Data#remove + elem[ dataUser.expando ] = undefined; + } + } + } + } +} ); + +jQuery.fn.extend( { + detach: function( selector ) { + return remove( this, selector, true ); + }, + + remove: function( selector ) { + return remove( this, selector ); + }, + + text: function( value ) { + return access( this, function( value ) { + return value === undefined ? + jQuery.text( this ) : + this.empty().each( function() { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + this.textContent = value; + } + } ); + }, null, value, arguments.length ); + }, + + append: function() { + return domManip( this, arguments, function( elem ) { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + var target = manipulationTarget( this, elem ); + target.appendChild( elem ); + } + } ); + }, + + prepend: function() { + return domManip( this, arguments, function( elem ) { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + var target = manipulationTarget( this, elem ); + target.insertBefore( elem, target.firstChild ); + } + } ); + }, + + before: function() { + return domManip( this, arguments, function( elem ) { + if ( this.parentNode ) { + this.parentNode.insertBefore( elem, this ); + } + } ); + }, + + after: function() { + return domManip( this, arguments, function( elem ) { + if ( this.parentNode ) { + this.parentNode.insertBefore( elem, this.nextSibling ); + } + } ); + }, + + empty: function() { + var elem, + i = 0; + + for ( ; ( elem = this[ i ] ) != null; i++ ) { + if ( elem.nodeType === 1 ) { + + // Prevent memory leaks + jQuery.cleanData( getAll( elem, false ) ); + + // Remove any remaining nodes + elem.textContent = ""; + } + } + + return this; + }, + + clone: function( dataAndEvents, deepDataAndEvents ) { + dataAndEvents = dataAndEvents == null ? false : dataAndEvents; + deepDataAndEvents = deepDataAndEvents == null ? dataAndEvents : deepDataAndEvents; + + return this.map( function() { + return jQuery.clone( this, dataAndEvents, deepDataAndEvents ); + } ); + }, + + html: function( value ) { + return access( this, function( value ) { + var elem = this[ 0 ] || {}, + i = 0, + l = this.length; + + if ( value === undefined && elem.nodeType === 1 ) { + return elem.innerHTML; + } + + // See if we can take a shortcut and just use innerHTML + if ( typeof value === "string" && !rnoInnerhtml.test( value ) && + !wrapMap[ ( rtagName.exec( value ) || [ "", "" ] )[ 1 ].toLowerCase() ] ) { + + value = jQuery.htmlPrefilter( value ); + + try { + for ( ; i < l; i++ ) { + elem = this[ i ] || {}; + + // Remove element nodes and prevent memory leaks + if ( elem.nodeType === 1 ) { + jQuery.cleanData( getAll( elem, false ) ); + elem.innerHTML = value; + } + } + + elem = 0; + + // If using innerHTML throws an exception, use the fallback method + } catch ( e ) {} + } + + if ( elem ) { + this.empty().append( value ); + } + }, null, value, arguments.length ); + }, + + replaceWith: function() { + var ignored = []; + + // Make the changes, replacing each non-ignored context element with the new content + return domManip( this, arguments, function( elem ) { + var parent = this.parentNode; + + if ( jQuery.inArray( this, ignored ) < 0 ) { + jQuery.cleanData( getAll( this ) ); + if ( parent ) { + parent.replaceChild( elem, this ); + } + } + + // Force callback invocation + }, ignored ); + } +} ); + +jQuery.each( { + appendTo: "append", + prependTo: "prepend", + insertBefore: "before", + insertAfter: "after", + replaceAll: "replaceWith" +}, function( name, original ) { + jQuery.fn[ name ] = function( selector ) { + var elems, + ret = [], + insert = jQuery( selector ), + last = insert.length - 1, + i = 0; + + for ( ; i <= last; i++ ) { + elems = i === last ? this : this.clone( true ); + jQuery( insert[ i ] )[ original ]( elems ); + + // Support: Android <=4.0 only, PhantomJS 1 only + // .get() because push.apply(_, arraylike) throws on ancient WebKit + push.apply( ret, elems.get() ); + } + + return this.pushStack( ret ); + }; +} ); +var rnumnonpx = new RegExp( "^(" + pnum + ")(?!px)[a-z%]+$", "i" ); + +var getStyles = function( elem ) { + + // Support: IE <=11 only, Firefox <=30 (#15098, #14150) + // IE throws on elements created in popups + // FF meanwhile throws on frame elements through "defaultView.getComputedStyle" + var view = elem.ownerDocument.defaultView; + + if ( !view || !view.opener ) { + view = window; + } + + return view.getComputedStyle( elem ); + }; + +var swap = function( elem, options, callback ) { + var ret, name, + old = {}; + + // Remember the old values, and insert the new ones + for ( name in options ) { + old[ name ] = elem.style[ name ]; + elem.style[ name ] = options[ name ]; + } + + ret = callback.call( elem ); + + // Revert the old values + for ( name in options ) { + elem.style[ name ] = old[ name ]; + } + + return ret; +}; + + +var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); + + + +( function() { + + // Executing both pixelPosition & boxSizingReliable tests require only one layout + // so they're executed at the same time to save the second computation. + function computeStyleTests() { + + // This is a singleton, we need to execute it only once + if ( !div ) { + return; + } + + container.style.cssText = "position:absolute;left:-11111px;width:60px;" + + "margin-top:1px;padding:0;border:0"; + div.style.cssText = + "position:relative;display:block;box-sizing:border-box;overflow:scroll;" + + "margin:auto;border:1px;padding:1px;" + + "width:60%;top:1%"; + documentElement.appendChild( container ).appendChild( div ); + + var divStyle = window.getComputedStyle( div ); + pixelPositionVal = divStyle.top !== "1%"; + + // Support: Android 4.0 - 4.3 only, Firefox <=3 - 44 + reliableMarginLeftVal = roundPixelMeasures( divStyle.marginLeft ) === 12; + + // Support: Android 4.0 - 4.3 only, Safari <=9.1 - 10.1, iOS <=7.0 - 9.3 + // Some styles come back with percentage values, even though they shouldn't + div.style.right = "60%"; + pixelBoxStylesVal = roundPixelMeasures( divStyle.right ) === 36; + + // Support: IE 9 - 11 only + // Detect misreporting of content dimensions for box-sizing:border-box elements + boxSizingReliableVal = roundPixelMeasures( divStyle.width ) === 36; + + // Support: IE 9 only + // Detect overflow:scroll screwiness (gh-3699) + // Support: Chrome <=64 + // Don't get tricked when zoom affects offsetWidth (gh-4029) + div.style.position = "absolute"; + scrollboxSizeVal = roundPixelMeasures( div.offsetWidth / 3 ) === 12; + + documentElement.removeChild( container ); + + // Nullify the div so it wouldn't be stored in the memory and + // it will also be a sign that checks already performed + div = null; + } + + function roundPixelMeasures( measure ) { + return Math.round( parseFloat( measure ) ); + } + + var pixelPositionVal, boxSizingReliableVal, scrollboxSizeVal, pixelBoxStylesVal, + reliableTrDimensionsVal, reliableMarginLeftVal, + container = document.createElement( "div" ), + div = document.createElement( "div" ); + + // Finish early in limited (non-browser) environments + if ( !div.style ) { + return; + } + + // Support: IE <=9 - 11 only + // Style of cloned element affects source element cloned (#8908) + div.style.backgroundClip = "content-box"; + div.cloneNode( true ).style.backgroundClip = ""; + support.clearCloneStyle = div.style.backgroundClip === "content-box"; + + jQuery.extend( support, { + boxSizingReliable: function() { + computeStyleTests(); + return boxSizingReliableVal; + }, + pixelBoxStyles: function() { + computeStyleTests(); + return pixelBoxStylesVal; + }, + pixelPosition: function() { + computeStyleTests(); + return pixelPositionVal; + }, + reliableMarginLeft: function() { + computeStyleTests(); + return reliableMarginLeftVal; + }, + scrollboxSize: function() { + computeStyleTests(); + return scrollboxSizeVal; + }, + + // Support: IE 9 - 11+, Edge 15 - 18+ + // IE/Edge misreport `getComputedStyle` of table rows with width/height + // set in CSS while `offset*` properties report correct values. + // Behavior in IE 9 is more subtle than in newer versions & it passes + // some versions of this test; make sure not to make it pass there! + reliableTrDimensions: function() { + var table, tr, trChild, trStyle; + if ( reliableTrDimensionsVal == null ) { + table = document.createElement( "table" ); + tr = document.createElement( "tr" ); + trChild = document.createElement( "div" ); + + table.style.cssText = "position:absolute;left:-11111px"; + tr.style.height = "1px"; + trChild.style.height = "9px"; + + documentElement + .appendChild( table ) + .appendChild( tr ) + .appendChild( trChild ); + + trStyle = window.getComputedStyle( tr ); + reliableTrDimensionsVal = parseInt( trStyle.height ) > 3; + + documentElement.removeChild( table ); + } + return reliableTrDimensionsVal; + } + } ); +} )(); + + +function curCSS( elem, name, computed ) { + var width, minWidth, maxWidth, ret, + + // Support: Firefox 51+ + // Retrieving style before computed somehow + // fixes an issue with getting wrong values + // on detached elements + style = elem.style; + + computed = computed || getStyles( elem ); + + // getPropertyValue is needed for: + // .css('filter') (IE 9 only, #12537) + // .css('--customProperty) (#3144) + if ( computed ) { + ret = computed.getPropertyValue( name ) || computed[ name ]; + + if ( ret === "" && !isAttached( elem ) ) { + ret = jQuery.style( elem, name ); + } + + // A tribute to the "awesome hack by Dean Edwards" + // Android Browser returns percentage for some values, + // but width seems to be reliably pixels. + // This is against the CSSOM draft spec: + // https://drafts.csswg.org/cssom/#resolved-values + if ( !support.pixelBoxStyles() && rnumnonpx.test( ret ) && rboxStyle.test( name ) ) { + + // Remember the original values + width = style.width; + minWidth = style.minWidth; + maxWidth = style.maxWidth; + + // Put in the new values to get a computed value out + style.minWidth = style.maxWidth = style.width = ret; + ret = computed.width; + + // Revert the changed values + style.width = width; + style.minWidth = minWidth; + style.maxWidth = maxWidth; + } + } + + return ret !== undefined ? + + // Support: IE <=9 - 11 only + // IE returns zIndex value as an integer. + ret + "" : + ret; +} + + +function addGetHookIf( conditionFn, hookFn ) { + + // Define the hook, we'll check on the first run if it's really needed. + return { + get: function() { + if ( conditionFn() ) { + + // Hook not needed (or it's not possible to use it due + // to missing dependency), remove it. + delete this.get; + return; + } + + // Hook needed; redefine it so that the support test is not executed again. + return ( this.get = hookFn ).apply( this, arguments ); + } + }; +} + + +var cssPrefixes = [ "Webkit", "Moz", "ms" ], + emptyStyle = document.createElement( "div" ).style, + vendorProps = {}; + +// Return a vendor-prefixed property or undefined +function vendorPropName( name ) { + + // Check for vendor prefixed names + var capName = name[ 0 ].toUpperCase() + name.slice( 1 ), + i = cssPrefixes.length; + + while ( i-- ) { + name = cssPrefixes[ i ] + capName; + if ( name in emptyStyle ) { + return name; + } + } +} + +// Return a potentially-mapped jQuery.cssProps or vendor prefixed property +function finalPropName( name ) { + var final = jQuery.cssProps[ name ] || vendorProps[ name ]; + + if ( final ) { + return final; + } + if ( name in emptyStyle ) { + return name; + } + return vendorProps[ name ] = vendorPropName( name ) || name; +} + + +var + + // Swappable if display is none or starts with table + // except "table", "table-cell", or "table-caption" + // See here for display values: https://developer.mozilla.org/en-US/docs/CSS/display + rdisplayswap = /^(none|table(?!-c[ea]).+)/, + rcustomProp = /^--/, + cssShow = { position: "absolute", visibility: "hidden", display: "block" }, + cssNormalTransform = { + letterSpacing: "0", + fontWeight: "400" + }; + +function setPositiveNumber( _elem, value, subtract ) { + + // Any relative (+/-) values have already been + // normalized at this point + var matches = rcssNum.exec( value ); + return matches ? + + // Guard against undefined "subtract", e.g., when used as in cssHooks + Math.max( 0, matches[ 2 ] - ( subtract || 0 ) ) + ( matches[ 3 ] || "px" ) : + value; +} + +function boxModelAdjustment( elem, dimension, box, isBorderBox, styles, computedVal ) { + var i = dimension === "width" ? 1 : 0, + extra = 0, + delta = 0; + + // Adjustment may not be necessary + if ( box === ( isBorderBox ? "border" : "content" ) ) { + return 0; + } + + for ( ; i < 4; i += 2 ) { + + // Both box models exclude margin + if ( box === "margin" ) { + delta += jQuery.css( elem, box + cssExpand[ i ], true, styles ); + } + + // If we get here with a content-box, we're seeking "padding" or "border" or "margin" + if ( !isBorderBox ) { + + // Add padding + delta += jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); + + // For "border" or "margin", add border + if ( box !== "padding" ) { + delta += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + + // But still keep track of it otherwise + } else { + extra += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + } + + // If we get here with a border-box (content + padding + border), we're seeking "content" or + // "padding" or "margin" + } else { + + // For "content", subtract padding + if ( box === "content" ) { + delta -= jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); + } + + // For "content" or "padding", subtract border + if ( box !== "margin" ) { + delta -= jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + } + } + } + + // Account for positive content-box scroll gutter when requested by providing computedVal + if ( !isBorderBox && computedVal >= 0 ) { + + // offsetWidth/offsetHeight is a rounded sum of content, padding, scroll gutter, and border + // Assuming integer scroll gutter, subtract the rest and round down + delta += Math.max( 0, Math.ceil( + elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - + computedVal - + delta - + extra - + 0.5 + + // If offsetWidth/offsetHeight is unknown, then we can't determine content-box scroll gutter + // Use an explicit zero to avoid NaN (gh-3964) + ) ) || 0; + } + + return delta; +} + +function getWidthOrHeight( elem, dimension, extra ) { + + // Start with computed style + var styles = getStyles( elem ), + + // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-4322). + // Fake content-box until we know it's needed to know the true value. + boxSizingNeeded = !support.boxSizingReliable() || extra, + isBorderBox = boxSizingNeeded && + jQuery.css( elem, "boxSizing", false, styles ) === "border-box", + valueIsBorderBox = isBorderBox, + + val = curCSS( elem, dimension, styles ), + offsetProp = "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ); + + // Support: Firefox <=54 + // Return a confounding non-pixel value or feign ignorance, as appropriate. + if ( rnumnonpx.test( val ) ) { + if ( !extra ) { + return val; + } + val = "auto"; + } + + + // Support: IE 9 - 11 only + // Use offsetWidth/offsetHeight for when box sizing is unreliable. + // In those cases, the computed value can be trusted to be border-box. + if ( ( !support.boxSizingReliable() && isBorderBox || + + // Support: IE 10 - 11+, Edge 15 - 18+ + // IE/Edge misreport `getComputedStyle` of table rows with width/height + // set in CSS while `offset*` properties report correct values. + // Interestingly, in some cases IE 9 doesn't suffer from this issue. + !support.reliableTrDimensions() && nodeName( elem, "tr" ) || + + // Fall back to offsetWidth/offsetHeight when value is "auto" + // This happens for inline elements with no explicit setting (gh-3571) + val === "auto" || + + // Support: Android <=4.1 - 4.3 only + // Also use offsetWidth/offsetHeight for misreported inline dimensions (gh-3602) + !parseFloat( val ) && jQuery.css( elem, "display", false, styles ) === "inline" ) && + + // Make sure the element is visible & connected + elem.getClientRects().length ) { + + isBorderBox = jQuery.css( elem, "boxSizing", false, styles ) === "border-box"; + + // Where available, offsetWidth/offsetHeight approximate border box dimensions. + // Where not available (e.g., SVG), assume unreliable box-sizing and interpret the + // retrieved value as a content box dimension. + valueIsBorderBox = offsetProp in elem; + if ( valueIsBorderBox ) { + val = elem[ offsetProp ]; + } + } + + // Normalize "" and auto + val = parseFloat( val ) || 0; + + // Adjust for the element's box model + return ( val + + boxModelAdjustment( + elem, + dimension, + extra || ( isBorderBox ? "border" : "content" ), + valueIsBorderBox, + styles, + + // Provide the current computed size to request scroll gutter calculation (gh-3589) + val + ) + ) + "px"; +} + +jQuery.extend( { + + // Add in style property hooks for overriding the default + // behavior of getting and setting a style property + cssHooks: { + opacity: { + get: function( elem, computed ) { + if ( computed ) { + + // We should always get a number back from opacity + var ret = curCSS( elem, "opacity" ); + return ret === "" ? "1" : ret; + } + } + } + }, + + // Don't automatically add "px" to these possibly-unitless properties + cssNumber: { + "animationIterationCount": true, + "columnCount": true, + "fillOpacity": true, + "flexGrow": true, + "flexShrink": true, + "fontWeight": true, + "gridArea": true, + "gridColumn": true, + "gridColumnEnd": true, + "gridColumnStart": true, + "gridRow": true, + "gridRowEnd": true, + "gridRowStart": true, + "lineHeight": true, + "opacity": true, + "order": true, + "orphans": true, + "widows": true, + "zIndex": true, + "zoom": true + }, + + // Add in properties whose names you wish to fix before + // setting or getting the value + cssProps: {}, + + // Get and set the style property on a DOM Node + style: function( elem, name, value, extra ) { + + // Don't set styles on text and comment nodes + if ( !elem || elem.nodeType === 3 || elem.nodeType === 8 || !elem.style ) { + return; + } + + // Make sure that we're working with the right name + var ret, type, hooks, + origName = camelCase( name ), + isCustomProp = rcustomProp.test( name ), + style = elem.style; + + // Make sure that we're working with the right name. We don't + // want to query the value if it is a CSS custom property + // since they are user-defined. + if ( !isCustomProp ) { + name = finalPropName( origName ); + } + + // Gets hook for the prefixed version, then unprefixed version + hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; + + // Check if we're setting a value + if ( value !== undefined ) { + type = typeof value; + + // Convert "+=" or "-=" to relative numbers (#7345) + if ( type === "string" && ( ret = rcssNum.exec( value ) ) && ret[ 1 ] ) { + value = adjustCSS( elem, name, ret ); + + // Fixes bug #9237 + type = "number"; + } + + // Make sure that null and NaN values aren't set (#7116) + if ( value == null || value !== value ) { + return; + } + + // If a number was passed in, add the unit (except for certain CSS properties) + // The isCustomProp check can be removed in jQuery 4.0 when we only auto-append + // "px" to a few hardcoded values. + if ( type === "number" && !isCustomProp ) { + value += ret && ret[ 3 ] || ( jQuery.cssNumber[ origName ] ? "" : "px" ); + } + + // background-* props affect original clone's values + if ( !support.clearCloneStyle && value === "" && name.indexOf( "background" ) === 0 ) { + style[ name ] = "inherit"; + } + + // If a hook was provided, use that value, otherwise just set the specified value + if ( !hooks || !( "set" in hooks ) || + ( value = hooks.set( elem, value, extra ) ) !== undefined ) { + + if ( isCustomProp ) { + style.setProperty( name, value ); + } else { + style[ name ] = value; + } + } + + } else { + + // If a hook was provided get the non-computed value from there + if ( hooks && "get" in hooks && + ( ret = hooks.get( elem, false, extra ) ) !== undefined ) { + + return ret; + } + + // Otherwise just get the value from the style object + return style[ name ]; + } + }, + + css: function( elem, name, extra, styles ) { + var val, num, hooks, + origName = camelCase( name ), + isCustomProp = rcustomProp.test( name ); + + // Make sure that we're working with the right name. We don't + // want to modify the value if it is a CSS custom property + // since they are user-defined. + if ( !isCustomProp ) { + name = finalPropName( origName ); + } + + // Try prefixed name followed by the unprefixed name + hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; + + // If a hook was provided get the computed value from there + if ( hooks && "get" in hooks ) { + val = hooks.get( elem, true, extra ); + } + + // Otherwise, if a way to get the computed value exists, use that + if ( val === undefined ) { + val = curCSS( elem, name, styles ); + } + + // Convert "normal" to computed value + if ( val === "normal" && name in cssNormalTransform ) { + val = cssNormalTransform[ name ]; + } + + // Make numeric if forced or a qualifier was provided and val looks numeric + if ( extra === "" || extra ) { + num = parseFloat( val ); + return extra === true || isFinite( num ) ? num || 0 : val; + } + + return val; + } +} ); + +jQuery.each( [ "height", "width" ], function( _i, dimension ) { + jQuery.cssHooks[ dimension ] = { + get: function( elem, computed, extra ) { + if ( computed ) { + + // Certain elements can have dimension info if we invisibly show them + // but it must have a current display style that would benefit + return rdisplayswap.test( jQuery.css( elem, "display" ) ) && + + // Support: Safari 8+ + // Table columns in Safari have non-zero offsetWidth & zero + // getBoundingClientRect().width unless display is changed. + // Support: IE <=11 only + // Running getBoundingClientRect on a disconnected node + // in IE throws an error. + ( !elem.getClientRects().length || !elem.getBoundingClientRect().width ) ? + swap( elem, cssShow, function() { + return getWidthOrHeight( elem, dimension, extra ); + } ) : + getWidthOrHeight( elem, dimension, extra ); + } + }, + + set: function( elem, value, extra ) { + var matches, + styles = getStyles( elem ), + + // Only read styles.position if the test has a chance to fail + // to avoid forcing a reflow. + scrollboxSizeBuggy = !support.scrollboxSize() && + styles.position === "absolute", + + // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-3991) + boxSizingNeeded = scrollboxSizeBuggy || extra, + isBorderBox = boxSizingNeeded && + jQuery.css( elem, "boxSizing", false, styles ) === "border-box", + subtract = extra ? + boxModelAdjustment( + elem, + dimension, + extra, + isBorderBox, + styles + ) : + 0; + + // Account for unreliable border-box dimensions by comparing offset* to computed and + // faking a content-box to get border and padding (gh-3699) + if ( isBorderBox && scrollboxSizeBuggy ) { + subtract -= Math.ceil( + elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - + parseFloat( styles[ dimension ] ) - + boxModelAdjustment( elem, dimension, "border", false, styles ) - + 0.5 + ); + } + + // Convert to pixels if value adjustment is needed + if ( subtract && ( matches = rcssNum.exec( value ) ) && + ( matches[ 3 ] || "px" ) !== "px" ) { + + elem.style[ dimension ] = value; + value = jQuery.css( elem, dimension ); + } + + return setPositiveNumber( elem, value, subtract ); + } + }; +} ); + +jQuery.cssHooks.marginLeft = addGetHookIf( support.reliableMarginLeft, + function( elem, computed ) { + if ( computed ) { + return ( parseFloat( curCSS( elem, "marginLeft" ) ) || + elem.getBoundingClientRect().left - + swap( elem, { marginLeft: 0 }, function() { + return elem.getBoundingClientRect().left; + } ) + ) + "px"; + } + } +); + +// These hooks are used by animate to expand properties +jQuery.each( { + margin: "", + padding: "", + border: "Width" +}, function( prefix, suffix ) { + jQuery.cssHooks[ prefix + suffix ] = { + expand: function( value ) { + var i = 0, + expanded = {}, + + // Assumes a single number if not a string + parts = typeof value === "string" ? value.split( " " ) : [ value ]; + + for ( ; i < 4; i++ ) { + expanded[ prefix + cssExpand[ i ] + suffix ] = + parts[ i ] || parts[ i - 2 ] || parts[ 0 ]; + } + + return expanded; + } + }; + + if ( prefix !== "margin" ) { + jQuery.cssHooks[ prefix + suffix ].set = setPositiveNumber; + } +} ); + +jQuery.fn.extend( { + css: function( name, value ) { + return access( this, function( elem, name, value ) { + var styles, len, + map = {}, + i = 0; + + if ( Array.isArray( name ) ) { + styles = getStyles( elem ); + len = name.length; + + for ( ; i < len; i++ ) { + map[ name[ i ] ] = jQuery.css( elem, name[ i ], false, styles ); + } + + return map; + } + + return value !== undefined ? + jQuery.style( elem, name, value ) : + jQuery.css( elem, name ); + }, name, value, arguments.length > 1 ); + } +} ); + + +function Tween( elem, options, prop, end, easing ) { + return new Tween.prototype.init( elem, options, prop, end, easing ); +} +jQuery.Tween = Tween; + +Tween.prototype = { + constructor: Tween, + init: function( elem, options, prop, end, easing, unit ) { + this.elem = elem; + this.prop = prop; + this.easing = easing || jQuery.easing._default; + this.options = options; + this.start = this.now = this.cur(); + this.end = end; + this.unit = unit || ( jQuery.cssNumber[ prop ] ? "" : "px" ); + }, + cur: function() { + var hooks = Tween.propHooks[ this.prop ]; + + return hooks && hooks.get ? + hooks.get( this ) : + Tween.propHooks._default.get( this ); + }, + run: function( percent ) { + var eased, + hooks = Tween.propHooks[ this.prop ]; + + if ( this.options.duration ) { + this.pos = eased = jQuery.easing[ this.easing ]( + percent, this.options.duration * percent, 0, 1, this.options.duration + ); + } else { + this.pos = eased = percent; + } + this.now = ( this.end - this.start ) * eased + this.start; + + if ( this.options.step ) { + this.options.step.call( this.elem, this.now, this ); + } + + if ( hooks && hooks.set ) { + hooks.set( this ); + } else { + Tween.propHooks._default.set( this ); + } + return this; + } +}; + +Tween.prototype.init.prototype = Tween.prototype; + +Tween.propHooks = { + _default: { + get: function( tween ) { + var result; + + // Use a property on the element directly when it is not a DOM element, + // or when there is no matching style property that exists. + if ( tween.elem.nodeType !== 1 || + tween.elem[ tween.prop ] != null && tween.elem.style[ tween.prop ] == null ) { + return tween.elem[ tween.prop ]; + } + + // Passing an empty string as a 3rd parameter to .css will automatically + // attempt a parseFloat and fallback to a string if the parse fails. + // Simple values such as "10px" are parsed to Float; + // complex values such as "rotate(1rad)" are returned as-is. + result = jQuery.css( tween.elem, tween.prop, "" ); + + // Empty strings, null, undefined and "auto" are converted to 0. + return !result || result === "auto" ? 0 : result; + }, + set: function( tween ) { + + // Use step hook for back compat. + // Use cssHook if its there. + // Use .style if available and use plain properties where available. + if ( jQuery.fx.step[ tween.prop ] ) { + jQuery.fx.step[ tween.prop ]( tween ); + } else if ( tween.elem.nodeType === 1 && ( + jQuery.cssHooks[ tween.prop ] || + tween.elem.style[ finalPropName( tween.prop ) ] != null ) ) { + jQuery.style( tween.elem, tween.prop, tween.now + tween.unit ); + } else { + tween.elem[ tween.prop ] = tween.now; + } + } + } +}; + +// Support: IE <=9 only +// Panic based approach to setting things on disconnected nodes +Tween.propHooks.scrollTop = Tween.propHooks.scrollLeft = { + set: function( tween ) { + if ( tween.elem.nodeType && tween.elem.parentNode ) { + tween.elem[ tween.prop ] = tween.now; + } + } +}; + +jQuery.easing = { + linear: function( p ) { + return p; + }, + swing: function( p ) { + return 0.5 - Math.cos( p * Math.PI ) / 2; + }, + _default: "swing" +}; + +jQuery.fx = Tween.prototype.init; + +// Back compat <1.8 extension point +jQuery.fx.step = {}; + + + + +var + fxNow, inProgress, + rfxtypes = /^(?:toggle|show|hide)$/, + rrun = /queueHooks$/; + +function schedule() { + if ( inProgress ) { + if ( document.hidden === false && window.requestAnimationFrame ) { + window.requestAnimationFrame( schedule ); + } else { + window.setTimeout( schedule, jQuery.fx.interval ); + } + + jQuery.fx.tick(); + } +} + +// Animations created synchronously will run synchronously +function createFxNow() { + window.setTimeout( function() { + fxNow = undefined; + } ); + return ( fxNow = Date.now() ); +} + +// Generate parameters to create a standard animation +function genFx( type, includeWidth ) { + var which, + i = 0, + attrs = { height: type }; + + // If we include width, step value is 1 to do all cssExpand values, + // otherwise step value is 2 to skip over Left and Right + includeWidth = includeWidth ? 1 : 0; + for ( ; i < 4; i += 2 - includeWidth ) { + which = cssExpand[ i ]; + attrs[ "margin" + which ] = attrs[ "padding" + which ] = type; + } + + if ( includeWidth ) { + attrs.opacity = attrs.width = type; + } + + return attrs; +} + +function createTween( value, prop, animation ) { + var tween, + collection = ( Animation.tweeners[ prop ] || [] ).concat( Animation.tweeners[ "*" ] ), + index = 0, + length = collection.length; + for ( ; index < length; index++ ) { + if ( ( tween = collection[ index ].call( animation, prop, value ) ) ) { + + // We're done with this property + return tween; + } + } +} + +function defaultPrefilter( elem, props, opts ) { + var prop, value, toggle, hooks, oldfire, propTween, restoreDisplay, display, + isBox = "width" in props || "height" in props, + anim = this, + orig = {}, + style = elem.style, + hidden = elem.nodeType && isHiddenWithinTree( elem ), + dataShow = dataPriv.get( elem, "fxshow" ); + + // Queue-skipping animations hijack the fx hooks + if ( !opts.queue ) { + hooks = jQuery._queueHooks( elem, "fx" ); + if ( hooks.unqueued == null ) { + hooks.unqueued = 0; + oldfire = hooks.empty.fire; + hooks.empty.fire = function() { + if ( !hooks.unqueued ) { + oldfire(); + } + }; + } + hooks.unqueued++; + + anim.always( function() { + + // Ensure the complete handler is called before this completes + anim.always( function() { + hooks.unqueued--; + if ( !jQuery.queue( elem, "fx" ).length ) { + hooks.empty.fire(); + } + } ); + } ); + } + + // Detect show/hide animations + for ( prop in props ) { + value = props[ prop ]; + if ( rfxtypes.test( value ) ) { + delete props[ prop ]; + toggle = toggle || value === "toggle"; + if ( value === ( hidden ? "hide" : "show" ) ) { + + // Pretend to be hidden if this is a "show" and + // there is still data from a stopped show/hide + if ( value === "show" && dataShow && dataShow[ prop ] !== undefined ) { + hidden = true; + + // Ignore all other no-op show/hide data + } else { + continue; + } + } + orig[ prop ] = dataShow && dataShow[ prop ] || jQuery.style( elem, prop ); + } + } + + // Bail out if this is a no-op like .hide().hide() + propTween = !jQuery.isEmptyObject( props ); + if ( !propTween && jQuery.isEmptyObject( orig ) ) { + return; + } + + // Restrict "overflow" and "display" styles during box animations + if ( isBox && elem.nodeType === 1 ) { + + // Support: IE <=9 - 11, Edge 12 - 15 + // Record all 3 overflow attributes because IE does not infer the shorthand + // from identically-valued overflowX and overflowY and Edge just mirrors + // the overflowX value there. + opts.overflow = [ style.overflow, style.overflowX, style.overflowY ]; + + // Identify a display type, preferring old show/hide data over the CSS cascade + restoreDisplay = dataShow && dataShow.display; + if ( restoreDisplay == null ) { + restoreDisplay = dataPriv.get( elem, "display" ); + } + display = jQuery.css( elem, "display" ); + if ( display === "none" ) { + if ( restoreDisplay ) { + display = restoreDisplay; + } else { + + // Get nonempty value(s) by temporarily forcing visibility + showHide( [ elem ], true ); + restoreDisplay = elem.style.display || restoreDisplay; + display = jQuery.css( elem, "display" ); + showHide( [ elem ] ); + } + } + + // Animate inline elements as inline-block + if ( display === "inline" || display === "inline-block" && restoreDisplay != null ) { + if ( jQuery.css( elem, "float" ) === "none" ) { + + // Restore the original display value at the end of pure show/hide animations + if ( !propTween ) { + anim.done( function() { + style.display = restoreDisplay; + } ); + if ( restoreDisplay == null ) { + display = style.display; + restoreDisplay = display === "none" ? "" : display; + } + } + style.display = "inline-block"; + } + } + } + + if ( opts.overflow ) { + style.overflow = "hidden"; + anim.always( function() { + style.overflow = opts.overflow[ 0 ]; + style.overflowX = opts.overflow[ 1 ]; + style.overflowY = opts.overflow[ 2 ]; + } ); + } + + // Implement show/hide animations + propTween = false; + for ( prop in orig ) { + + // General show/hide setup for this element animation + if ( !propTween ) { + if ( dataShow ) { + if ( "hidden" in dataShow ) { + hidden = dataShow.hidden; + } + } else { + dataShow = dataPriv.access( elem, "fxshow", { display: restoreDisplay } ); + } + + // Store hidden/visible for toggle so `.stop().toggle()` "reverses" + if ( toggle ) { + dataShow.hidden = !hidden; + } + + // Show elements before animating them + if ( hidden ) { + showHide( [ elem ], true ); + } + + /* eslint-disable no-loop-func */ + + anim.done( function() { + + /* eslint-enable no-loop-func */ + + // The final step of a "hide" animation is actually hiding the element + if ( !hidden ) { + showHide( [ elem ] ); + } + dataPriv.remove( elem, "fxshow" ); + for ( prop in orig ) { + jQuery.style( elem, prop, orig[ prop ] ); + } + } ); + } + + // Per-property setup + propTween = createTween( hidden ? dataShow[ prop ] : 0, prop, anim ); + if ( !( prop in dataShow ) ) { + dataShow[ prop ] = propTween.start; + if ( hidden ) { + propTween.end = propTween.start; + propTween.start = 0; + } + } + } +} + +function propFilter( props, specialEasing ) { + var index, name, easing, value, hooks; + + // camelCase, specialEasing and expand cssHook pass + for ( index in props ) { + name = camelCase( index ); + easing = specialEasing[ name ]; + value = props[ index ]; + if ( Array.isArray( value ) ) { + easing = value[ 1 ]; + value = props[ index ] = value[ 0 ]; + } + + if ( index !== name ) { + props[ name ] = value; + delete props[ index ]; + } + + hooks = jQuery.cssHooks[ name ]; + if ( hooks && "expand" in hooks ) { + value = hooks.expand( value ); + delete props[ name ]; + + // Not quite $.extend, this won't overwrite existing keys. + // Reusing 'index' because we have the correct "name" + for ( index in value ) { + if ( !( index in props ) ) { + props[ index ] = value[ index ]; + specialEasing[ index ] = easing; + } + } + } else { + specialEasing[ name ] = easing; + } + } +} + +function Animation( elem, properties, options ) { + var result, + stopped, + index = 0, + length = Animation.prefilters.length, + deferred = jQuery.Deferred().always( function() { + + // Don't match elem in the :animated selector + delete tick.elem; + } ), + tick = function() { + if ( stopped ) { + return false; + } + var currentTime = fxNow || createFxNow(), + remaining = Math.max( 0, animation.startTime + animation.duration - currentTime ), + + // Support: Android 2.3 only + // Archaic crash bug won't allow us to use `1 - ( 0.5 || 0 )` (#12497) + temp = remaining / animation.duration || 0, + percent = 1 - temp, + index = 0, + length = animation.tweens.length; + + for ( ; index < length; index++ ) { + animation.tweens[ index ].run( percent ); + } + + deferred.notifyWith( elem, [ animation, percent, remaining ] ); + + // If there's more to do, yield + if ( percent < 1 && length ) { + return remaining; + } + + // If this was an empty animation, synthesize a final progress notification + if ( !length ) { + deferred.notifyWith( elem, [ animation, 1, 0 ] ); + } + + // Resolve the animation and report its conclusion + deferred.resolveWith( elem, [ animation ] ); + return false; + }, + animation = deferred.promise( { + elem: elem, + props: jQuery.extend( {}, properties ), + opts: jQuery.extend( true, { + specialEasing: {}, + easing: jQuery.easing._default + }, options ), + originalProperties: properties, + originalOptions: options, + startTime: fxNow || createFxNow(), + duration: options.duration, + tweens: [], + createTween: function( prop, end ) { + var tween = jQuery.Tween( elem, animation.opts, prop, end, + animation.opts.specialEasing[ prop ] || animation.opts.easing ); + animation.tweens.push( tween ); + return tween; + }, + stop: function( gotoEnd ) { + var index = 0, + + // If we are going to the end, we want to run all the tweens + // otherwise we skip this part + length = gotoEnd ? animation.tweens.length : 0; + if ( stopped ) { + return this; + } + stopped = true; + for ( ; index < length; index++ ) { + animation.tweens[ index ].run( 1 ); + } + + // Resolve when we played the last frame; otherwise, reject + if ( gotoEnd ) { + deferred.notifyWith( elem, [ animation, 1, 0 ] ); + deferred.resolveWith( elem, [ animation, gotoEnd ] ); + } else { + deferred.rejectWith( elem, [ animation, gotoEnd ] ); + } + return this; + } + } ), + props = animation.props; + + propFilter( props, animation.opts.specialEasing ); + + for ( ; index < length; index++ ) { + result = Animation.prefilters[ index ].call( animation, elem, props, animation.opts ); + if ( result ) { + if ( isFunction( result.stop ) ) { + jQuery._queueHooks( animation.elem, animation.opts.queue ).stop = + result.stop.bind( result ); + } + return result; + } + } + + jQuery.map( props, createTween, animation ); + + if ( isFunction( animation.opts.start ) ) { + animation.opts.start.call( elem, animation ); + } + + // Attach callbacks from options + animation + .progress( animation.opts.progress ) + .done( animation.opts.done, animation.opts.complete ) + .fail( animation.opts.fail ) + .always( animation.opts.always ); + + jQuery.fx.timer( + jQuery.extend( tick, { + elem: elem, + anim: animation, + queue: animation.opts.queue + } ) + ); + + return animation; +} + +jQuery.Animation = jQuery.extend( Animation, { + + tweeners: { + "*": [ function( prop, value ) { + var tween = this.createTween( prop, value ); + adjustCSS( tween.elem, prop, rcssNum.exec( value ), tween ); + return tween; + } ] + }, + + tweener: function( props, callback ) { + if ( isFunction( props ) ) { + callback = props; + props = [ "*" ]; + } else { + props = props.match( rnothtmlwhite ); + } + + var prop, + index = 0, + length = props.length; + + for ( ; index < length; index++ ) { + prop = props[ index ]; + Animation.tweeners[ prop ] = Animation.tweeners[ prop ] || []; + Animation.tweeners[ prop ].unshift( callback ); + } + }, + + prefilters: [ defaultPrefilter ], + + prefilter: function( callback, prepend ) { + if ( prepend ) { + Animation.prefilters.unshift( callback ); + } else { + Animation.prefilters.push( callback ); + } + } +} ); + +jQuery.speed = function( speed, easing, fn ) { + var opt = speed && typeof speed === "object" ? jQuery.extend( {}, speed ) : { + complete: fn || !fn && easing || + isFunction( speed ) && speed, + duration: speed, + easing: fn && easing || easing && !isFunction( easing ) && easing + }; + + // Go to the end state if fx are off + if ( jQuery.fx.off ) { + opt.duration = 0; + + } else { + if ( typeof opt.duration !== "number" ) { + if ( opt.duration in jQuery.fx.speeds ) { + opt.duration = jQuery.fx.speeds[ opt.duration ]; + + } else { + opt.duration = jQuery.fx.speeds._default; + } + } + } + + // Normalize opt.queue - true/undefined/null -> "fx" + if ( opt.queue == null || opt.queue === true ) { + opt.queue = "fx"; + } + + // Queueing + opt.old = opt.complete; + + opt.complete = function() { + if ( isFunction( opt.old ) ) { + opt.old.call( this ); + } + + if ( opt.queue ) { + jQuery.dequeue( this, opt.queue ); + } + }; + + return opt; +}; + +jQuery.fn.extend( { + fadeTo: function( speed, to, easing, callback ) { + + // Show any hidden elements after setting opacity to 0 + return this.filter( isHiddenWithinTree ).css( "opacity", 0 ).show() + + // Animate to the value specified + .end().animate( { opacity: to }, speed, easing, callback ); + }, + animate: function( prop, speed, easing, callback ) { + var empty = jQuery.isEmptyObject( prop ), + optall = jQuery.speed( speed, easing, callback ), + doAnimation = function() { + + // Operate on a copy of prop so per-property easing won't be lost + var anim = Animation( this, jQuery.extend( {}, prop ), optall ); + + // Empty animations, or finishing resolves immediately + if ( empty || dataPriv.get( this, "finish" ) ) { + anim.stop( true ); + } + }; + doAnimation.finish = doAnimation; + + return empty || optall.queue === false ? + this.each( doAnimation ) : + this.queue( optall.queue, doAnimation ); + }, + stop: function( type, clearQueue, gotoEnd ) { + var stopQueue = function( hooks ) { + var stop = hooks.stop; + delete hooks.stop; + stop( gotoEnd ); + }; + + if ( typeof type !== "string" ) { + gotoEnd = clearQueue; + clearQueue = type; + type = undefined; + } + if ( clearQueue ) { + this.queue( type || "fx", [] ); + } + + return this.each( function() { + var dequeue = true, + index = type != null && type + "queueHooks", + timers = jQuery.timers, + data = dataPriv.get( this ); + + if ( index ) { + if ( data[ index ] && data[ index ].stop ) { + stopQueue( data[ index ] ); + } + } else { + for ( index in data ) { + if ( data[ index ] && data[ index ].stop && rrun.test( index ) ) { + stopQueue( data[ index ] ); + } + } + } + + for ( index = timers.length; index--; ) { + if ( timers[ index ].elem === this && + ( type == null || timers[ index ].queue === type ) ) { + + timers[ index ].anim.stop( gotoEnd ); + dequeue = false; + timers.splice( index, 1 ); + } + } + + // Start the next in the queue if the last step wasn't forced. + // Timers currently will call their complete callbacks, which + // will dequeue but only if they were gotoEnd. + if ( dequeue || !gotoEnd ) { + jQuery.dequeue( this, type ); + } + } ); + }, + finish: function( type ) { + if ( type !== false ) { + type = type || "fx"; + } + return this.each( function() { + var index, + data = dataPriv.get( this ), + queue = data[ type + "queue" ], + hooks = data[ type + "queueHooks" ], + timers = jQuery.timers, + length = queue ? queue.length : 0; + + // Enable finishing flag on private data + data.finish = true; + + // Empty the queue first + jQuery.queue( this, type, [] ); + + if ( hooks && hooks.stop ) { + hooks.stop.call( this, true ); + } + + // Look for any active animations, and finish them + for ( index = timers.length; index--; ) { + if ( timers[ index ].elem === this && timers[ index ].queue === type ) { + timers[ index ].anim.stop( true ); + timers.splice( index, 1 ); + } + } + + // Look for any animations in the old queue and finish them + for ( index = 0; index < length; index++ ) { + if ( queue[ index ] && queue[ index ].finish ) { + queue[ index ].finish.call( this ); + } + } + + // Turn off finishing flag + delete data.finish; + } ); + } +} ); + +jQuery.each( [ "toggle", "show", "hide" ], function( _i, name ) { + var cssFn = jQuery.fn[ name ]; + jQuery.fn[ name ] = function( speed, easing, callback ) { + return speed == null || typeof speed === "boolean" ? + cssFn.apply( this, arguments ) : + this.animate( genFx( name, true ), speed, easing, callback ); + }; +} ); + +// Generate shortcuts for custom animations +jQuery.each( { + slideDown: genFx( "show" ), + slideUp: genFx( "hide" ), + slideToggle: genFx( "toggle" ), + fadeIn: { opacity: "show" }, + fadeOut: { opacity: "hide" }, + fadeToggle: { opacity: "toggle" } +}, function( name, props ) { + jQuery.fn[ name ] = function( speed, easing, callback ) { + return this.animate( props, speed, easing, callback ); + }; +} ); + +jQuery.timers = []; +jQuery.fx.tick = function() { + var timer, + i = 0, + timers = jQuery.timers; + + fxNow = Date.now(); + + for ( ; i < timers.length; i++ ) { + timer = timers[ i ]; + + // Run the timer and safely remove it when done (allowing for external removal) + if ( !timer() && timers[ i ] === timer ) { + timers.splice( i--, 1 ); + } + } + + if ( !timers.length ) { + jQuery.fx.stop(); + } + fxNow = undefined; +}; + +jQuery.fx.timer = function( timer ) { + jQuery.timers.push( timer ); + jQuery.fx.start(); +}; + +jQuery.fx.interval = 13; +jQuery.fx.start = function() { + if ( inProgress ) { + return; + } + + inProgress = true; + schedule(); +}; + +jQuery.fx.stop = function() { + inProgress = null; +}; + +jQuery.fx.speeds = { + slow: 600, + fast: 200, + + // Default speed + _default: 400 +}; + + +// Based off of the plugin by Clint Helfers, with permission. +// https://web.archive.org/web/20100324014747/http://blindsignals.com/index.php/2009/07/jquery-delay/ +jQuery.fn.delay = function( time, type ) { + time = jQuery.fx ? jQuery.fx.speeds[ time ] || time : time; + type = type || "fx"; + + return this.queue( type, function( next, hooks ) { + var timeout = window.setTimeout( next, time ); + hooks.stop = function() { + window.clearTimeout( timeout ); + }; + } ); +}; + + +( function() { + var input = document.createElement( "input" ), + select = document.createElement( "select" ), + opt = select.appendChild( document.createElement( "option" ) ); + + input.type = "checkbox"; + + // Support: Android <=4.3 only + // Default value for a checkbox should be "on" + support.checkOn = input.value !== ""; + + // Support: IE <=11 only + // Must access selectedIndex to make default options select + support.optSelected = opt.selected; + + // Support: IE <=11 only + // An input loses its value after becoming a radio + input = document.createElement( "input" ); + input.value = "t"; + input.type = "radio"; + support.radioValue = input.value === "t"; +} )(); + + +var boolHook, + attrHandle = jQuery.expr.attrHandle; + +jQuery.fn.extend( { + attr: function( name, value ) { + return access( this, jQuery.attr, name, value, arguments.length > 1 ); + }, + + removeAttr: function( name ) { + return this.each( function() { + jQuery.removeAttr( this, name ); + } ); + } +} ); + +jQuery.extend( { + attr: function( elem, name, value ) { + var ret, hooks, + nType = elem.nodeType; + + // Don't get/set attributes on text, comment and attribute nodes + if ( nType === 3 || nType === 8 || nType === 2 ) { + return; + } + + // Fallback to prop when attributes are not supported + if ( typeof elem.getAttribute === "undefined" ) { + return jQuery.prop( elem, name, value ); + } + + // Attribute hooks are determined by the lowercase version + // Grab necessary hook if one is defined + if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { + hooks = jQuery.attrHooks[ name.toLowerCase() ] || + ( jQuery.expr.match.bool.test( name ) ? boolHook : undefined ); + } + + if ( value !== undefined ) { + if ( value === null ) { + jQuery.removeAttr( elem, name ); + return; + } + + if ( hooks && "set" in hooks && + ( ret = hooks.set( elem, value, name ) ) !== undefined ) { + return ret; + } + + elem.setAttribute( name, value + "" ); + return value; + } + + if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { + return ret; + } + + ret = jQuery.find.attr( elem, name ); + + // Non-existent attributes return null, we normalize to undefined + return ret == null ? undefined : ret; + }, + + attrHooks: { + type: { + set: function( elem, value ) { + if ( !support.radioValue && value === "radio" && + nodeName( elem, "input" ) ) { + var val = elem.value; + elem.setAttribute( "type", value ); + if ( val ) { + elem.value = val; + } + return value; + } + } + } + }, + + removeAttr: function( elem, value ) { + var name, + i = 0, + + // Attribute names can contain non-HTML whitespace characters + // https://html.spec.whatwg.org/multipage/syntax.html#attributes-2 + attrNames = value && value.match( rnothtmlwhite ); + + if ( attrNames && elem.nodeType === 1 ) { + while ( ( name = attrNames[ i++ ] ) ) { + elem.removeAttribute( name ); + } + } + } +} ); + +// Hooks for boolean attributes +boolHook = { + set: function( elem, value, name ) { + if ( value === false ) { + + // Remove boolean attributes when set to false + jQuery.removeAttr( elem, name ); + } else { + elem.setAttribute( name, name ); + } + return name; + } +}; + +jQuery.each( jQuery.expr.match.bool.source.match( /\w+/g ), function( _i, name ) { + var getter = attrHandle[ name ] || jQuery.find.attr; + + attrHandle[ name ] = function( elem, name, isXML ) { + var ret, handle, + lowercaseName = name.toLowerCase(); + + if ( !isXML ) { + + // Avoid an infinite loop by temporarily removing this function from the getter + handle = attrHandle[ lowercaseName ]; + attrHandle[ lowercaseName ] = ret; + ret = getter( elem, name, isXML ) != null ? + lowercaseName : + null; + attrHandle[ lowercaseName ] = handle; + } + return ret; + }; +} ); + + + + +var rfocusable = /^(?:input|select|textarea|button)$/i, + rclickable = /^(?:a|area)$/i; + +jQuery.fn.extend( { + prop: function( name, value ) { + return access( this, jQuery.prop, name, value, arguments.length > 1 ); + }, + + removeProp: function( name ) { + return this.each( function() { + delete this[ jQuery.propFix[ name ] || name ]; + } ); + } +} ); + +jQuery.extend( { + prop: function( elem, name, value ) { + var ret, hooks, + nType = elem.nodeType; + + // Don't get/set properties on text, comment and attribute nodes + if ( nType === 3 || nType === 8 || nType === 2 ) { + return; + } + + if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { + + // Fix name and attach hooks + name = jQuery.propFix[ name ] || name; + hooks = jQuery.propHooks[ name ]; + } + + if ( value !== undefined ) { + if ( hooks && "set" in hooks && + ( ret = hooks.set( elem, value, name ) ) !== undefined ) { + return ret; + } + + return ( elem[ name ] = value ); + } + + if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { + return ret; + } + + return elem[ name ]; + }, + + propHooks: { + tabIndex: { + get: function( elem ) { + + // Support: IE <=9 - 11 only + // elem.tabIndex doesn't always return the + // correct value when it hasn't been explicitly set + // https://web.archive.org/web/20141116233347/http://fluidproject.org/blog/2008/01/09/getting-setting-and-removing-tabindex-values-with-javascript/ + // Use proper attribute retrieval(#12072) + var tabindex = jQuery.find.attr( elem, "tabindex" ); + + if ( tabindex ) { + return parseInt( tabindex, 10 ); + } + + if ( + rfocusable.test( elem.nodeName ) || + rclickable.test( elem.nodeName ) && + elem.href + ) { + return 0; + } + + return -1; + } + } + }, + + propFix: { + "for": "htmlFor", + "class": "className" + } +} ); + +// Support: IE <=11 only +// Accessing the selectedIndex property +// forces the browser to respect setting selected +// on the option +// The getter ensures a default option is selected +// when in an optgroup +// eslint rule "no-unused-expressions" is disabled for this code +// since it considers such accessions noop +if ( !support.optSelected ) { + jQuery.propHooks.selected = { + get: function( elem ) { + + /* eslint no-unused-expressions: "off" */ + + var parent = elem.parentNode; + if ( parent && parent.parentNode ) { + parent.parentNode.selectedIndex; + } + return null; + }, + set: function( elem ) { + + /* eslint no-unused-expressions: "off" */ + + var parent = elem.parentNode; + if ( parent ) { + parent.selectedIndex; + + if ( parent.parentNode ) { + parent.parentNode.selectedIndex; + } + } + } + }; +} + +jQuery.each( [ + "tabIndex", + "readOnly", + "maxLength", + "cellSpacing", + "cellPadding", + "rowSpan", + "colSpan", + "useMap", + "frameBorder", + "contentEditable" +], function() { + jQuery.propFix[ this.toLowerCase() ] = this; +} ); + + + + + // Strip and collapse whitespace according to HTML spec + // https://infra.spec.whatwg.org/#strip-and-collapse-ascii-whitespace + function stripAndCollapse( value ) { + var tokens = value.match( rnothtmlwhite ) || []; + return tokens.join( " " ); + } + + +function getClass( elem ) { + return elem.getAttribute && elem.getAttribute( "class" ) || ""; +} + +function classesToArray( value ) { + if ( Array.isArray( value ) ) { + return value; + } + if ( typeof value === "string" ) { + return value.match( rnothtmlwhite ) || []; + } + return []; +} + +jQuery.fn.extend( { + addClass: function( value ) { + var classes, elem, cur, curValue, clazz, j, finalValue, + i = 0; + + if ( isFunction( value ) ) { + return this.each( function( j ) { + jQuery( this ).addClass( value.call( this, j, getClass( this ) ) ); + } ); + } + + classes = classesToArray( value ); + + if ( classes.length ) { + while ( ( elem = this[ i++ ] ) ) { + curValue = getClass( elem ); + cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); + + if ( cur ) { + j = 0; + while ( ( clazz = classes[ j++ ] ) ) { + if ( cur.indexOf( " " + clazz + " " ) < 0 ) { + cur += clazz + " "; + } + } + + // Only assign if different to avoid unneeded rendering. + finalValue = stripAndCollapse( cur ); + if ( curValue !== finalValue ) { + elem.setAttribute( "class", finalValue ); + } + } + } + } + + return this; + }, + + removeClass: function( value ) { + var classes, elem, cur, curValue, clazz, j, finalValue, + i = 0; + + if ( isFunction( value ) ) { + return this.each( function( j ) { + jQuery( this ).removeClass( value.call( this, j, getClass( this ) ) ); + } ); + } + + if ( !arguments.length ) { + return this.attr( "class", "" ); + } + + classes = classesToArray( value ); + + if ( classes.length ) { + while ( ( elem = this[ i++ ] ) ) { + curValue = getClass( elem ); + + // This expression is here for better compressibility (see addClass) + cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); + + if ( cur ) { + j = 0; + while ( ( clazz = classes[ j++ ] ) ) { + + // Remove *all* instances + while ( cur.indexOf( " " + clazz + " " ) > -1 ) { + cur = cur.replace( " " + clazz + " ", " " ); + } + } + + // Only assign if different to avoid unneeded rendering. + finalValue = stripAndCollapse( cur ); + if ( curValue !== finalValue ) { + elem.setAttribute( "class", finalValue ); + } + } + } + } + + return this; + }, + + toggleClass: function( value, stateVal ) { + var type = typeof value, + isValidValue = type === "string" || Array.isArray( value ); + + if ( typeof stateVal === "boolean" && isValidValue ) { + return stateVal ? this.addClass( value ) : this.removeClass( value ); + } + + if ( isFunction( value ) ) { + return this.each( function( i ) { + jQuery( this ).toggleClass( + value.call( this, i, getClass( this ), stateVal ), + stateVal + ); + } ); + } + + return this.each( function() { + var className, i, self, classNames; + + if ( isValidValue ) { + + // Toggle individual class names + i = 0; + self = jQuery( this ); + classNames = classesToArray( value ); + + while ( ( className = classNames[ i++ ] ) ) { + + // Check each className given, space separated list + if ( self.hasClass( className ) ) { + self.removeClass( className ); + } else { + self.addClass( className ); + } + } + + // Toggle whole class name + } else if ( value === undefined || type === "boolean" ) { + className = getClass( this ); + if ( className ) { + + // Store className if set + dataPriv.set( this, "__className__", className ); + } + + // If the element has a class name or if we're passed `false`, + // then remove the whole classname (if there was one, the above saved it). + // Otherwise bring back whatever was previously saved (if anything), + // falling back to the empty string if nothing was stored. + if ( this.setAttribute ) { + this.setAttribute( "class", + className || value === false ? + "" : + dataPriv.get( this, "__className__" ) || "" + ); + } + } + } ); + }, + + hasClass: function( selector ) { + var className, elem, + i = 0; + + className = " " + selector + " "; + while ( ( elem = this[ i++ ] ) ) { + if ( elem.nodeType === 1 && + ( " " + stripAndCollapse( getClass( elem ) ) + " " ).indexOf( className ) > -1 ) { + return true; + } + } + + return false; + } +} ); + + + + +var rreturn = /\r/g; + +jQuery.fn.extend( { + val: function( value ) { + var hooks, ret, valueIsFunction, + elem = this[ 0 ]; + + if ( !arguments.length ) { + if ( elem ) { + hooks = jQuery.valHooks[ elem.type ] || + jQuery.valHooks[ elem.nodeName.toLowerCase() ]; + + if ( hooks && + "get" in hooks && + ( ret = hooks.get( elem, "value" ) ) !== undefined + ) { + return ret; + } + + ret = elem.value; + + // Handle most common string cases + if ( typeof ret === "string" ) { + return ret.replace( rreturn, "" ); + } + + // Handle cases where value is null/undef or number + return ret == null ? "" : ret; + } + + return; + } + + valueIsFunction = isFunction( value ); + + return this.each( function( i ) { + var val; + + if ( this.nodeType !== 1 ) { + return; + } + + if ( valueIsFunction ) { + val = value.call( this, i, jQuery( this ).val() ); + } else { + val = value; + } + + // Treat null/undefined as ""; convert numbers to string + if ( val == null ) { + val = ""; + + } else if ( typeof val === "number" ) { + val += ""; + + } else if ( Array.isArray( val ) ) { + val = jQuery.map( val, function( value ) { + return value == null ? "" : value + ""; + } ); + } + + hooks = jQuery.valHooks[ this.type ] || jQuery.valHooks[ this.nodeName.toLowerCase() ]; + + // If set returns undefined, fall back to normal setting + if ( !hooks || !( "set" in hooks ) || hooks.set( this, val, "value" ) === undefined ) { + this.value = val; + } + } ); + } +} ); + +jQuery.extend( { + valHooks: { + option: { + get: function( elem ) { + + var val = jQuery.find.attr( elem, "value" ); + return val != null ? + val : + + // Support: IE <=10 - 11 only + // option.text throws exceptions (#14686, #14858) + // Strip and collapse whitespace + // https://html.spec.whatwg.org/#strip-and-collapse-whitespace + stripAndCollapse( jQuery.text( elem ) ); + } + }, + select: { + get: function( elem ) { + var value, option, i, + options = elem.options, + index = elem.selectedIndex, + one = elem.type === "select-one", + values = one ? null : [], + max = one ? index + 1 : options.length; + + if ( index < 0 ) { + i = max; + + } else { + i = one ? index : 0; + } + + // Loop through all the selected options + for ( ; i < max; i++ ) { + option = options[ i ]; + + // Support: IE <=9 only + // IE8-9 doesn't update selected after form reset (#2551) + if ( ( option.selected || i === index ) && + + // Don't return options that are disabled or in a disabled optgroup + !option.disabled && + ( !option.parentNode.disabled || + !nodeName( option.parentNode, "optgroup" ) ) ) { + + // Get the specific value for the option + value = jQuery( option ).val(); + + // We don't need an array for one selects + if ( one ) { + return value; + } + + // Multi-Selects return an array + values.push( value ); + } + } + + return values; + }, + + set: function( elem, value ) { + var optionSet, option, + options = elem.options, + values = jQuery.makeArray( value ), + i = options.length; + + while ( i-- ) { + option = options[ i ]; + + /* eslint-disable no-cond-assign */ + + if ( option.selected = + jQuery.inArray( jQuery.valHooks.option.get( option ), values ) > -1 + ) { + optionSet = true; + } + + /* eslint-enable no-cond-assign */ + } + + // Force browsers to behave consistently when non-matching value is set + if ( !optionSet ) { + elem.selectedIndex = -1; + } + return values; + } + } + } +} ); + +// Radios and checkboxes getter/setter +jQuery.each( [ "radio", "checkbox" ], function() { + jQuery.valHooks[ this ] = { + set: function( elem, value ) { + if ( Array.isArray( value ) ) { + return ( elem.checked = jQuery.inArray( jQuery( elem ).val(), value ) > -1 ); + } + } + }; + if ( !support.checkOn ) { + jQuery.valHooks[ this ].get = function( elem ) { + return elem.getAttribute( "value" ) === null ? "on" : elem.value; + }; + } +} ); + + + + +// Return jQuery for attributes-only inclusion + + +support.focusin = "onfocusin" in window; + + +var rfocusMorph = /^(?:focusinfocus|focusoutblur)$/, + stopPropagationCallback = function( e ) { + e.stopPropagation(); + }; + +jQuery.extend( jQuery.event, { + + trigger: function( event, data, elem, onlyHandlers ) { + + var i, cur, tmp, bubbleType, ontype, handle, special, lastElement, + eventPath = [ elem || document ], + type = hasOwn.call( event, "type" ) ? event.type : event, + namespaces = hasOwn.call( event, "namespace" ) ? event.namespace.split( "." ) : []; + + cur = lastElement = tmp = elem = elem || document; + + // Don't do events on text and comment nodes + if ( elem.nodeType === 3 || elem.nodeType === 8 ) { + return; + } + + // focus/blur morphs to focusin/out; ensure we're not firing them right now + if ( rfocusMorph.test( type + jQuery.event.triggered ) ) { + return; + } + + if ( type.indexOf( "." ) > -1 ) { + + // Namespaced trigger; create a regexp to match event type in handle() + namespaces = type.split( "." ); + type = namespaces.shift(); + namespaces.sort(); + } + ontype = type.indexOf( ":" ) < 0 && "on" + type; + + // Caller can pass in a jQuery.Event object, Object, or just an event type string + event = event[ jQuery.expando ] ? + event : + new jQuery.Event( type, typeof event === "object" && event ); + + // Trigger bitmask: & 1 for native handlers; & 2 for jQuery (always true) + event.isTrigger = onlyHandlers ? 2 : 3; + event.namespace = namespaces.join( "." ); + event.rnamespace = event.namespace ? + new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ) : + null; + + // Clean up the event in case it is being reused + event.result = undefined; + if ( !event.target ) { + event.target = elem; + } + + // Clone any incoming data and prepend the event, creating the handler arg list + data = data == null ? + [ event ] : + jQuery.makeArray( data, [ event ] ); + + // Allow special events to draw outside the lines + special = jQuery.event.special[ type ] || {}; + if ( !onlyHandlers && special.trigger && special.trigger.apply( elem, data ) === false ) { + return; + } + + // Determine event propagation path in advance, per W3C events spec (#9951) + // Bubble up to document, then to window; watch for a global ownerDocument var (#9724) + if ( !onlyHandlers && !special.noBubble && !isWindow( elem ) ) { + + bubbleType = special.delegateType || type; + if ( !rfocusMorph.test( bubbleType + type ) ) { + cur = cur.parentNode; + } + for ( ; cur; cur = cur.parentNode ) { + eventPath.push( cur ); + tmp = cur; + } + + // Only add window if we got to document (e.g., not plain obj or detached DOM) + if ( tmp === ( elem.ownerDocument || document ) ) { + eventPath.push( tmp.defaultView || tmp.parentWindow || window ); + } + } + + // Fire handlers on the event path + i = 0; + while ( ( cur = eventPath[ i++ ] ) && !event.isPropagationStopped() ) { + lastElement = cur; + event.type = i > 1 ? + bubbleType : + special.bindType || type; + + // jQuery handler + handle = ( + dataPriv.get( cur, "events" ) || Object.create( null ) + )[ event.type ] && + dataPriv.get( cur, "handle" ); + if ( handle ) { + handle.apply( cur, data ); + } + + // Native handler + handle = ontype && cur[ ontype ]; + if ( handle && handle.apply && acceptData( cur ) ) { + event.result = handle.apply( cur, data ); + if ( event.result === false ) { + event.preventDefault(); + } + } + } + event.type = type; + + // If nobody prevented the default action, do it now + if ( !onlyHandlers && !event.isDefaultPrevented() ) { + + if ( ( !special._default || + special._default.apply( eventPath.pop(), data ) === false ) && + acceptData( elem ) ) { + + // Call a native DOM method on the target with the same name as the event. + // Don't do default actions on window, that's where global variables be (#6170) + if ( ontype && isFunction( elem[ type ] ) && !isWindow( elem ) ) { + + // Don't re-trigger an onFOO event when we call its FOO() method + tmp = elem[ ontype ]; + + if ( tmp ) { + elem[ ontype ] = null; + } + + // Prevent re-triggering of the same event, since we already bubbled it above + jQuery.event.triggered = type; + + if ( event.isPropagationStopped() ) { + lastElement.addEventListener( type, stopPropagationCallback ); + } + + elem[ type ](); + + if ( event.isPropagationStopped() ) { + lastElement.removeEventListener( type, stopPropagationCallback ); + } + + jQuery.event.triggered = undefined; + + if ( tmp ) { + elem[ ontype ] = tmp; + } + } + } + } + + return event.result; + }, + + // Piggyback on a donor event to simulate a different one + // Used only for `focus(in | out)` events + simulate: function( type, elem, event ) { + var e = jQuery.extend( + new jQuery.Event(), + event, + { + type: type, + isSimulated: true + } + ); + + jQuery.event.trigger( e, null, elem ); + } + +} ); + +jQuery.fn.extend( { + + trigger: function( type, data ) { + return this.each( function() { + jQuery.event.trigger( type, data, this ); + } ); + }, + triggerHandler: function( type, data ) { + var elem = this[ 0 ]; + if ( elem ) { + return jQuery.event.trigger( type, data, elem, true ); + } + } +} ); + + +// Support: Firefox <=44 +// Firefox doesn't have focus(in | out) events +// Related ticket - https://bugzilla.mozilla.org/show_bug.cgi?id=687787 +// +// Support: Chrome <=48 - 49, Safari <=9.0 - 9.1 +// focus(in | out) events fire after focus & blur events, +// which is spec violation - http://www.w3.org/TR/DOM-Level-3-Events/#events-focusevent-event-order +// Related ticket - https://bugs.chromium.org/p/chromium/issues/detail?id=449857 +if ( !support.focusin ) { + jQuery.each( { focus: "focusin", blur: "focusout" }, function( orig, fix ) { + + // Attach a single capturing handler on the document while someone wants focusin/focusout + var handler = function( event ) { + jQuery.event.simulate( fix, event.target, jQuery.event.fix( event ) ); + }; + + jQuery.event.special[ fix ] = { + setup: function() { + + // Handle: regular nodes (via `this.ownerDocument`), window + // (via `this.document`) & document (via `this`). + var doc = this.ownerDocument || this.document || this, + attaches = dataPriv.access( doc, fix ); + + if ( !attaches ) { + doc.addEventListener( orig, handler, true ); + } + dataPriv.access( doc, fix, ( attaches || 0 ) + 1 ); + }, + teardown: function() { + var doc = this.ownerDocument || this.document || this, + attaches = dataPriv.access( doc, fix ) - 1; + + if ( !attaches ) { + doc.removeEventListener( orig, handler, true ); + dataPriv.remove( doc, fix ); + + } else { + dataPriv.access( doc, fix, attaches ); + } + } + }; + } ); +} +var location = window.location; + +var nonce = { guid: Date.now() }; + +var rquery = ( /\?/ ); + + + +// Cross-browser xml parsing +jQuery.parseXML = function( data ) { + var xml; + if ( !data || typeof data !== "string" ) { + return null; + } + + // Support: IE 9 - 11 only + // IE throws on parseFromString with invalid input. + try { + xml = ( new window.DOMParser() ).parseFromString( data, "text/xml" ); + } catch ( e ) { + xml = undefined; + } + + if ( !xml || xml.getElementsByTagName( "parsererror" ).length ) { + jQuery.error( "Invalid XML: " + data ); + } + return xml; +}; + + +var + rbracket = /\[\]$/, + rCRLF = /\r?\n/g, + rsubmitterTypes = /^(?:submit|button|image|reset|file)$/i, + rsubmittable = /^(?:input|select|textarea|keygen)/i; + +function buildParams( prefix, obj, traditional, add ) { + var name; + + if ( Array.isArray( obj ) ) { + + // Serialize array item. + jQuery.each( obj, function( i, v ) { + if ( traditional || rbracket.test( prefix ) ) { + + // Treat each array item as a scalar. + add( prefix, v ); + + } else { + + // Item is non-scalar (array or object), encode its numeric index. + buildParams( + prefix + "[" + ( typeof v === "object" && v != null ? i : "" ) + "]", + v, + traditional, + add + ); + } + } ); + + } else if ( !traditional && toType( obj ) === "object" ) { + + // Serialize object item. + for ( name in obj ) { + buildParams( prefix + "[" + name + "]", obj[ name ], traditional, add ); + } + + } else { + + // Serialize scalar item. + add( prefix, obj ); + } +} + +// Serialize an array of form elements or a set of +// key/values into a query string +jQuery.param = function( a, traditional ) { + var prefix, + s = [], + add = function( key, valueOrFunction ) { + + // If value is a function, invoke it and use its return value + var value = isFunction( valueOrFunction ) ? + valueOrFunction() : + valueOrFunction; + + s[ s.length ] = encodeURIComponent( key ) + "=" + + encodeURIComponent( value == null ? "" : value ); + }; + + if ( a == null ) { + return ""; + } + + // If an array was passed in, assume that it is an array of form elements. + if ( Array.isArray( a ) || ( a.jquery && !jQuery.isPlainObject( a ) ) ) { + + // Serialize the form elements + jQuery.each( a, function() { + add( this.name, this.value ); + } ); + + } else { + + // If traditional, encode the "old" way (the way 1.3.2 or older + // did it), otherwise encode params recursively. + for ( prefix in a ) { + buildParams( prefix, a[ prefix ], traditional, add ); + } + } + + // Return the resulting serialization + return s.join( "&" ); +}; + +jQuery.fn.extend( { + serialize: function() { + return jQuery.param( this.serializeArray() ); + }, + serializeArray: function() { + return this.map( function() { + + // Can add propHook for "elements" to filter or add form elements + var elements = jQuery.prop( this, "elements" ); + return elements ? jQuery.makeArray( elements ) : this; + } ) + .filter( function() { + var type = this.type; + + // Use .is( ":disabled" ) so that fieldset[disabled] works + return this.name && !jQuery( this ).is( ":disabled" ) && + rsubmittable.test( this.nodeName ) && !rsubmitterTypes.test( type ) && + ( this.checked || !rcheckableType.test( type ) ); + } ) + .map( function( _i, elem ) { + var val = jQuery( this ).val(); + + if ( val == null ) { + return null; + } + + if ( Array.isArray( val ) ) { + return jQuery.map( val, function( val ) { + return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; + } ); + } + + return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; + } ).get(); + } +} ); + + +var + r20 = /%20/g, + rhash = /#.*$/, + rantiCache = /([?&])_=[^&]*/, + rheaders = /^(.*?):[ \t]*([^\r\n]*)$/mg, + + // #7653, #8125, #8152: local protocol detection + rlocalProtocol = /^(?:about|app|app-storage|.+-extension|file|res|widget):$/, + rnoContent = /^(?:GET|HEAD)$/, + rprotocol = /^\/\//, + + /* Prefilters + * 1) They are useful to introduce custom dataTypes (see ajax/jsonp.js for an example) + * 2) These are called: + * - BEFORE asking for a transport + * - AFTER param serialization (s.data is a string if s.processData is true) + * 3) key is the dataType + * 4) the catchall symbol "*" can be used + * 5) execution will start with transport dataType and THEN continue down to "*" if needed + */ + prefilters = {}, + + /* Transports bindings + * 1) key is the dataType + * 2) the catchall symbol "*" can be used + * 3) selection will start with transport dataType and THEN go to "*" if needed + */ + transports = {}, + + // Avoid comment-prolog char sequence (#10098); must appease lint and evade compression + allTypes = "*/".concat( "*" ), + + // Anchor tag for parsing the document origin + originAnchor = document.createElement( "a" ); + originAnchor.href = location.href; + +// Base "constructor" for jQuery.ajaxPrefilter and jQuery.ajaxTransport +function addToPrefiltersOrTransports( structure ) { + + // dataTypeExpression is optional and defaults to "*" + return function( dataTypeExpression, func ) { + + if ( typeof dataTypeExpression !== "string" ) { + func = dataTypeExpression; + dataTypeExpression = "*"; + } + + var dataType, + i = 0, + dataTypes = dataTypeExpression.toLowerCase().match( rnothtmlwhite ) || []; + + if ( isFunction( func ) ) { + + // For each dataType in the dataTypeExpression + while ( ( dataType = dataTypes[ i++ ] ) ) { + + // Prepend if requested + if ( dataType[ 0 ] === "+" ) { + dataType = dataType.slice( 1 ) || "*"; + ( structure[ dataType ] = structure[ dataType ] || [] ).unshift( func ); + + // Otherwise append + } else { + ( structure[ dataType ] = structure[ dataType ] || [] ).push( func ); + } + } + } + }; +} + +// Base inspection function for prefilters and transports +function inspectPrefiltersOrTransports( structure, options, originalOptions, jqXHR ) { + + var inspected = {}, + seekingTransport = ( structure === transports ); + + function inspect( dataType ) { + var selected; + inspected[ dataType ] = true; + jQuery.each( structure[ dataType ] || [], function( _, prefilterOrFactory ) { + var dataTypeOrTransport = prefilterOrFactory( options, originalOptions, jqXHR ); + if ( typeof dataTypeOrTransport === "string" && + !seekingTransport && !inspected[ dataTypeOrTransport ] ) { + + options.dataTypes.unshift( dataTypeOrTransport ); + inspect( dataTypeOrTransport ); + return false; + } else if ( seekingTransport ) { + return !( selected = dataTypeOrTransport ); + } + } ); + return selected; + } + + return inspect( options.dataTypes[ 0 ] ) || !inspected[ "*" ] && inspect( "*" ); +} + +// A special extend for ajax options +// that takes "flat" options (not to be deep extended) +// Fixes #9887 +function ajaxExtend( target, src ) { + var key, deep, + flatOptions = jQuery.ajaxSettings.flatOptions || {}; + + for ( key in src ) { + if ( src[ key ] !== undefined ) { + ( flatOptions[ key ] ? target : ( deep || ( deep = {} ) ) )[ key ] = src[ key ]; + } + } + if ( deep ) { + jQuery.extend( true, target, deep ); + } + + return target; +} + +/* Handles responses to an ajax request: + * - finds the right dataType (mediates between content-type and expected dataType) + * - returns the corresponding response + */ +function ajaxHandleResponses( s, jqXHR, responses ) { + + var ct, type, finalDataType, firstDataType, + contents = s.contents, + dataTypes = s.dataTypes; + + // Remove auto dataType and get content-type in the process + while ( dataTypes[ 0 ] === "*" ) { + dataTypes.shift(); + if ( ct === undefined ) { + ct = s.mimeType || jqXHR.getResponseHeader( "Content-Type" ); + } + } + + // Check if we're dealing with a known content-type + if ( ct ) { + for ( type in contents ) { + if ( contents[ type ] && contents[ type ].test( ct ) ) { + dataTypes.unshift( type ); + break; + } + } + } + + // Check to see if we have a response for the expected dataType + if ( dataTypes[ 0 ] in responses ) { + finalDataType = dataTypes[ 0 ]; + } else { + + // Try convertible dataTypes + for ( type in responses ) { + if ( !dataTypes[ 0 ] || s.converters[ type + " " + dataTypes[ 0 ] ] ) { + finalDataType = type; + break; + } + if ( !firstDataType ) { + firstDataType = type; + } + } + + // Or just use first one + finalDataType = finalDataType || firstDataType; + } + + // If we found a dataType + // We add the dataType to the list if needed + // and return the corresponding response + if ( finalDataType ) { + if ( finalDataType !== dataTypes[ 0 ] ) { + dataTypes.unshift( finalDataType ); + } + return responses[ finalDataType ]; + } +} + +/* Chain conversions given the request and the original response + * Also sets the responseXXX fields on the jqXHR instance + */ +function ajaxConvert( s, response, jqXHR, isSuccess ) { + var conv2, current, conv, tmp, prev, + converters = {}, + + // Work with a copy of dataTypes in case we need to modify it for conversion + dataTypes = s.dataTypes.slice(); + + // Create converters map with lowercased keys + if ( dataTypes[ 1 ] ) { + for ( conv in s.converters ) { + converters[ conv.toLowerCase() ] = s.converters[ conv ]; + } + } + + current = dataTypes.shift(); + + // Convert to each sequential dataType + while ( current ) { + + if ( s.responseFields[ current ] ) { + jqXHR[ s.responseFields[ current ] ] = response; + } + + // Apply the dataFilter if provided + if ( !prev && isSuccess && s.dataFilter ) { + response = s.dataFilter( response, s.dataType ); + } + + prev = current; + current = dataTypes.shift(); + + if ( current ) { + + // There's only work to do if current dataType is non-auto + if ( current === "*" ) { + + current = prev; + + // Convert response if prev dataType is non-auto and differs from current + } else if ( prev !== "*" && prev !== current ) { + + // Seek a direct converter + conv = converters[ prev + " " + current ] || converters[ "* " + current ]; + + // If none found, seek a pair + if ( !conv ) { + for ( conv2 in converters ) { + + // If conv2 outputs current + tmp = conv2.split( " " ); + if ( tmp[ 1 ] === current ) { + + // If prev can be converted to accepted input + conv = converters[ prev + " " + tmp[ 0 ] ] || + converters[ "* " + tmp[ 0 ] ]; + if ( conv ) { + + // Condense equivalence converters + if ( conv === true ) { + conv = converters[ conv2 ]; + + // Otherwise, insert the intermediate dataType + } else if ( converters[ conv2 ] !== true ) { + current = tmp[ 0 ]; + dataTypes.unshift( tmp[ 1 ] ); + } + break; + } + } + } + } + + // Apply converter (if not an equivalence) + if ( conv !== true ) { + + // Unless errors are allowed to bubble, catch and return them + if ( conv && s.throws ) { + response = conv( response ); + } else { + try { + response = conv( response ); + } catch ( e ) { + return { + state: "parsererror", + error: conv ? e : "No conversion from " + prev + " to " + current + }; + } + } + } + } + } + } + + return { state: "success", data: response }; +} + +jQuery.extend( { + + // Counter for holding the number of active queries + active: 0, + + // Last-Modified header cache for next request + lastModified: {}, + etag: {}, + + ajaxSettings: { + url: location.href, + type: "GET", + isLocal: rlocalProtocol.test( location.protocol ), + global: true, + processData: true, + async: true, + contentType: "application/x-www-form-urlencoded; charset=UTF-8", + + /* + timeout: 0, + data: null, + dataType: null, + username: null, + password: null, + cache: null, + throws: false, + traditional: false, + headers: {}, + */ + + accepts: { + "*": allTypes, + text: "text/plain", + html: "text/html", + xml: "application/xml, text/xml", + json: "application/json, text/javascript" + }, + + contents: { + xml: /\bxml\b/, + html: /\bhtml/, + json: /\bjson\b/ + }, + + responseFields: { + xml: "responseXML", + text: "responseText", + json: "responseJSON" + }, + + // Data converters + // Keys separate source (or catchall "*") and destination types with a single space + converters: { + + // Convert anything to text + "* text": String, + + // Text to html (true = no transformation) + "text html": true, + + // Evaluate text as a json expression + "text json": JSON.parse, + + // Parse text as xml + "text xml": jQuery.parseXML + }, + + // For options that shouldn't be deep extended: + // you can add your own custom options here if + // and when you create one that shouldn't be + // deep extended (see ajaxExtend) + flatOptions: { + url: true, + context: true + } + }, + + // Creates a full fledged settings object into target + // with both ajaxSettings and settings fields. + // If target is omitted, writes into ajaxSettings. + ajaxSetup: function( target, settings ) { + return settings ? + + // Building a settings object + ajaxExtend( ajaxExtend( target, jQuery.ajaxSettings ), settings ) : + + // Extending ajaxSettings + ajaxExtend( jQuery.ajaxSettings, target ); + }, + + ajaxPrefilter: addToPrefiltersOrTransports( prefilters ), + ajaxTransport: addToPrefiltersOrTransports( transports ), + + // Main method + ajax: function( url, options ) { + + // If url is an object, simulate pre-1.5 signature + if ( typeof url === "object" ) { + options = url; + url = undefined; + } + + // Force options to be an object + options = options || {}; + + var transport, + + // URL without anti-cache param + cacheURL, + + // Response headers + responseHeadersString, + responseHeaders, + + // timeout handle + timeoutTimer, + + // Url cleanup var + urlAnchor, + + // Request state (becomes false upon send and true upon completion) + completed, + + // To know if global events are to be dispatched + fireGlobals, + + // Loop variable + i, + + // uncached part of the url + uncached, + + // Create the final options object + s = jQuery.ajaxSetup( {}, options ), + + // Callbacks context + callbackContext = s.context || s, + + // Context for global events is callbackContext if it is a DOM node or jQuery collection + globalEventContext = s.context && + ( callbackContext.nodeType || callbackContext.jquery ) ? + jQuery( callbackContext ) : + jQuery.event, + + // Deferreds + deferred = jQuery.Deferred(), + completeDeferred = jQuery.Callbacks( "once memory" ), + + // Status-dependent callbacks + statusCode = s.statusCode || {}, + + // Headers (they are sent all at once) + requestHeaders = {}, + requestHeadersNames = {}, + + // Default abort message + strAbort = "canceled", + + // Fake xhr + jqXHR = { + readyState: 0, + + // Builds headers hashtable if needed + getResponseHeader: function( key ) { + var match; + if ( completed ) { + if ( !responseHeaders ) { + responseHeaders = {}; + while ( ( match = rheaders.exec( responseHeadersString ) ) ) { + responseHeaders[ match[ 1 ].toLowerCase() + " " ] = + ( responseHeaders[ match[ 1 ].toLowerCase() + " " ] || [] ) + .concat( match[ 2 ] ); + } + } + match = responseHeaders[ key.toLowerCase() + " " ]; + } + return match == null ? null : match.join( ", " ); + }, + + // Raw string + getAllResponseHeaders: function() { + return completed ? responseHeadersString : null; + }, + + // Caches the header + setRequestHeader: function( name, value ) { + if ( completed == null ) { + name = requestHeadersNames[ name.toLowerCase() ] = + requestHeadersNames[ name.toLowerCase() ] || name; + requestHeaders[ name ] = value; + } + return this; + }, + + // Overrides response content-type header + overrideMimeType: function( type ) { + if ( completed == null ) { + s.mimeType = type; + } + return this; + }, + + // Status-dependent callbacks + statusCode: function( map ) { + var code; + if ( map ) { + if ( completed ) { + + // Execute the appropriate callbacks + jqXHR.always( map[ jqXHR.status ] ); + } else { + + // Lazy-add the new callbacks in a way that preserves old ones + for ( code in map ) { + statusCode[ code ] = [ statusCode[ code ], map[ code ] ]; + } + } + } + return this; + }, + + // Cancel the request + abort: function( statusText ) { + var finalText = statusText || strAbort; + if ( transport ) { + transport.abort( finalText ); + } + done( 0, finalText ); + return this; + } + }; + + // Attach deferreds + deferred.promise( jqXHR ); + + // Add protocol if not provided (prefilters might expect it) + // Handle falsy url in the settings object (#10093: consistency with old signature) + // We also use the url parameter if available + s.url = ( ( url || s.url || location.href ) + "" ) + .replace( rprotocol, location.protocol + "//" ); + + // Alias method option to type as per ticket #12004 + s.type = options.method || options.type || s.method || s.type; + + // Extract dataTypes list + s.dataTypes = ( s.dataType || "*" ).toLowerCase().match( rnothtmlwhite ) || [ "" ]; + + // A cross-domain request is in order when the origin doesn't match the current origin. + if ( s.crossDomain == null ) { + urlAnchor = document.createElement( "a" ); + + // Support: IE <=8 - 11, Edge 12 - 15 + // IE throws exception on accessing the href property if url is malformed, + // e.g. http://example.com:80x/ + try { + urlAnchor.href = s.url; + + // Support: IE <=8 - 11 only + // Anchor's host property isn't correctly set when s.url is relative + urlAnchor.href = urlAnchor.href; + s.crossDomain = originAnchor.protocol + "//" + originAnchor.host !== + urlAnchor.protocol + "//" + urlAnchor.host; + } catch ( e ) { + + // If there is an error parsing the URL, assume it is crossDomain, + // it can be rejected by the transport if it is invalid + s.crossDomain = true; + } + } + + // Convert data if not already a string + if ( s.data && s.processData && typeof s.data !== "string" ) { + s.data = jQuery.param( s.data, s.traditional ); + } + + // Apply prefilters + inspectPrefiltersOrTransports( prefilters, s, options, jqXHR ); + + // If request was aborted inside a prefilter, stop there + if ( completed ) { + return jqXHR; + } + + // We can fire global events as of now if asked to + // Don't fire events if jQuery.event is undefined in an AMD-usage scenario (#15118) + fireGlobals = jQuery.event && s.global; + + // Watch for a new set of requests + if ( fireGlobals && jQuery.active++ === 0 ) { + jQuery.event.trigger( "ajaxStart" ); + } + + // Uppercase the type + s.type = s.type.toUpperCase(); + + // Determine if request has content + s.hasContent = !rnoContent.test( s.type ); + + // Save the URL in case we're toying with the If-Modified-Since + // and/or If-None-Match header later on + // Remove hash to simplify url manipulation + cacheURL = s.url.replace( rhash, "" ); + + // More options handling for requests with no content + if ( !s.hasContent ) { + + // Remember the hash so we can put it back + uncached = s.url.slice( cacheURL.length ); + + // If data is available and should be processed, append data to url + if ( s.data && ( s.processData || typeof s.data === "string" ) ) { + cacheURL += ( rquery.test( cacheURL ) ? "&" : "?" ) + s.data; + + // #9682: remove data so that it's not used in an eventual retry + delete s.data; + } + + // Add or update anti-cache param if needed + if ( s.cache === false ) { + cacheURL = cacheURL.replace( rantiCache, "$1" ); + uncached = ( rquery.test( cacheURL ) ? "&" : "?" ) + "_=" + ( nonce.guid++ ) + + uncached; + } + + // Put hash and anti-cache on the URL that will be requested (gh-1732) + s.url = cacheURL + uncached; + + // Change '%20' to '+' if this is encoded form body content (gh-2658) + } else if ( s.data && s.processData && + ( s.contentType || "" ).indexOf( "application/x-www-form-urlencoded" ) === 0 ) { + s.data = s.data.replace( r20, "+" ); + } + + // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. + if ( s.ifModified ) { + if ( jQuery.lastModified[ cacheURL ] ) { + jqXHR.setRequestHeader( "If-Modified-Since", jQuery.lastModified[ cacheURL ] ); + } + if ( jQuery.etag[ cacheURL ] ) { + jqXHR.setRequestHeader( "If-None-Match", jQuery.etag[ cacheURL ] ); + } + } + + // Set the correct header, if data is being sent + if ( s.data && s.hasContent && s.contentType !== false || options.contentType ) { + jqXHR.setRequestHeader( "Content-Type", s.contentType ); + } + + // Set the Accepts header for the server, depending on the dataType + jqXHR.setRequestHeader( + "Accept", + s.dataTypes[ 0 ] && s.accepts[ s.dataTypes[ 0 ] ] ? + s.accepts[ s.dataTypes[ 0 ] ] + + ( s.dataTypes[ 0 ] !== "*" ? ", " + allTypes + "; q=0.01" : "" ) : + s.accepts[ "*" ] + ); + + // Check for headers option + for ( i in s.headers ) { + jqXHR.setRequestHeader( i, s.headers[ i ] ); + } + + // Allow custom headers/mimetypes and early abort + if ( s.beforeSend && + ( s.beforeSend.call( callbackContext, jqXHR, s ) === false || completed ) ) { + + // Abort if not done already and return + return jqXHR.abort(); + } + + // Aborting is no longer a cancellation + strAbort = "abort"; + + // Install callbacks on deferreds + completeDeferred.add( s.complete ); + jqXHR.done( s.success ); + jqXHR.fail( s.error ); + + // Get transport + transport = inspectPrefiltersOrTransports( transports, s, options, jqXHR ); + + // If no transport, we auto-abort + if ( !transport ) { + done( -1, "No Transport" ); + } else { + jqXHR.readyState = 1; + + // Send global event + if ( fireGlobals ) { + globalEventContext.trigger( "ajaxSend", [ jqXHR, s ] ); + } + + // If request was aborted inside ajaxSend, stop there + if ( completed ) { + return jqXHR; + } + + // Timeout + if ( s.async && s.timeout > 0 ) { + timeoutTimer = window.setTimeout( function() { + jqXHR.abort( "timeout" ); + }, s.timeout ); + } + + try { + completed = false; + transport.send( requestHeaders, done ); + } catch ( e ) { + + // Rethrow post-completion exceptions + if ( completed ) { + throw e; + } + + // Propagate others as results + done( -1, e ); + } + } + + // Callback for when everything is done + function done( status, nativeStatusText, responses, headers ) { + var isSuccess, success, error, response, modified, + statusText = nativeStatusText; + + // Ignore repeat invocations + if ( completed ) { + return; + } + + completed = true; + + // Clear timeout if it exists + if ( timeoutTimer ) { + window.clearTimeout( timeoutTimer ); + } + + // Dereference transport for early garbage collection + // (no matter how long the jqXHR object will be used) + transport = undefined; + + // Cache response headers + responseHeadersString = headers || ""; + + // Set readyState + jqXHR.readyState = status > 0 ? 4 : 0; + + // Determine if successful + isSuccess = status >= 200 && status < 300 || status === 304; + + // Get response data + if ( responses ) { + response = ajaxHandleResponses( s, jqXHR, responses ); + } + + // Use a noop converter for missing script + if ( !isSuccess && jQuery.inArray( "script", s.dataTypes ) > -1 ) { + s.converters[ "text script" ] = function() {}; + } + + // Convert no matter what (that way responseXXX fields are always set) + response = ajaxConvert( s, response, jqXHR, isSuccess ); + + // If successful, handle type chaining + if ( isSuccess ) { + + // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. + if ( s.ifModified ) { + modified = jqXHR.getResponseHeader( "Last-Modified" ); + if ( modified ) { + jQuery.lastModified[ cacheURL ] = modified; + } + modified = jqXHR.getResponseHeader( "etag" ); + if ( modified ) { + jQuery.etag[ cacheURL ] = modified; + } + } + + // if no content + if ( status === 204 || s.type === "HEAD" ) { + statusText = "nocontent"; + + // if not modified + } else if ( status === 304 ) { + statusText = "notmodified"; + + // If we have data, let's convert it + } else { + statusText = response.state; + success = response.data; + error = response.error; + isSuccess = !error; + } + } else { + + // Extract error from statusText and normalize for non-aborts + error = statusText; + if ( status || !statusText ) { + statusText = "error"; + if ( status < 0 ) { + status = 0; + } + } + } + + // Set data for the fake xhr object + jqXHR.status = status; + jqXHR.statusText = ( nativeStatusText || statusText ) + ""; + + // Success/Error + if ( isSuccess ) { + deferred.resolveWith( callbackContext, [ success, statusText, jqXHR ] ); + } else { + deferred.rejectWith( callbackContext, [ jqXHR, statusText, error ] ); + } + + // Status-dependent callbacks + jqXHR.statusCode( statusCode ); + statusCode = undefined; + + if ( fireGlobals ) { + globalEventContext.trigger( isSuccess ? "ajaxSuccess" : "ajaxError", + [ jqXHR, s, isSuccess ? success : error ] ); + } + + // Complete + completeDeferred.fireWith( callbackContext, [ jqXHR, statusText ] ); + + if ( fireGlobals ) { + globalEventContext.trigger( "ajaxComplete", [ jqXHR, s ] ); + + // Handle the global AJAX counter + if ( !( --jQuery.active ) ) { + jQuery.event.trigger( "ajaxStop" ); + } + } + } + + return jqXHR; + }, + + getJSON: function( url, data, callback ) { + return jQuery.get( url, data, callback, "json" ); + }, + + getScript: function( url, callback ) { + return jQuery.get( url, undefined, callback, "script" ); + } +} ); + +jQuery.each( [ "get", "post" ], function( _i, method ) { + jQuery[ method ] = function( url, data, callback, type ) { + + // Shift arguments if data argument was omitted + if ( isFunction( data ) ) { + type = type || callback; + callback = data; + data = undefined; + } + + // The url can be an options object (which then must have .url) + return jQuery.ajax( jQuery.extend( { + url: url, + type: method, + dataType: type, + data: data, + success: callback + }, jQuery.isPlainObject( url ) && url ) ); + }; +} ); + +jQuery.ajaxPrefilter( function( s ) { + var i; + for ( i in s.headers ) { + if ( i.toLowerCase() === "content-type" ) { + s.contentType = s.headers[ i ] || ""; + } + } +} ); + + +jQuery._evalUrl = function( url, options, doc ) { + return jQuery.ajax( { + url: url, + + // Make this explicit, since user can override this through ajaxSetup (#11264) + type: "GET", + dataType: "script", + cache: true, + async: false, + global: false, + + // Only evaluate the response if it is successful (gh-4126) + // dataFilter is not invoked for failure responses, so using it instead + // of the default converter is kludgy but it works. + converters: { + "text script": function() {} + }, + dataFilter: function( response ) { + jQuery.globalEval( response, options, doc ); + } + } ); +}; + + +jQuery.fn.extend( { + wrapAll: function( html ) { + var wrap; + + if ( this[ 0 ] ) { + if ( isFunction( html ) ) { + html = html.call( this[ 0 ] ); + } + + // The elements to wrap the target around + wrap = jQuery( html, this[ 0 ].ownerDocument ).eq( 0 ).clone( true ); + + if ( this[ 0 ].parentNode ) { + wrap.insertBefore( this[ 0 ] ); + } + + wrap.map( function() { + var elem = this; + + while ( elem.firstElementChild ) { + elem = elem.firstElementChild; + } + + return elem; + } ).append( this ); + } + + return this; + }, + + wrapInner: function( html ) { + if ( isFunction( html ) ) { + return this.each( function( i ) { + jQuery( this ).wrapInner( html.call( this, i ) ); + } ); + } + + return this.each( function() { + var self = jQuery( this ), + contents = self.contents(); + + if ( contents.length ) { + contents.wrapAll( html ); + + } else { + self.append( html ); + } + } ); + }, + + wrap: function( html ) { + var htmlIsFunction = isFunction( html ); + + return this.each( function( i ) { + jQuery( this ).wrapAll( htmlIsFunction ? html.call( this, i ) : html ); + } ); + }, + + unwrap: function( selector ) { + this.parent( selector ).not( "body" ).each( function() { + jQuery( this ).replaceWith( this.childNodes ); + } ); + return this; + } +} ); + + +jQuery.expr.pseudos.hidden = function( elem ) { + return !jQuery.expr.pseudos.visible( elem ); +}; +jQuery.expr.pseudos.visible = function( elem ) { + return !!( elem.offsetWidth || elem.offsetHeight || elem.getClientRects().length ); +}; + + + + +jQuery.ajaxSettings.xhr = function() { + try { + return new window.XMLHttpRequest(); + } catch ( e ) {} +}; + +var xhrSuccessStatus = { + + // File protocol always yields status code 0, assume 200 + 0: 200, + + // Support: IE <=9 only + // #1450: sometimes IE returns 1223 when it should be 204 + 1223: 204 + }, + xhrSupported = jQuery.ajaxSettings.xhr(); + +support.cors = !!xhrSupported && ( "withCredentials" in xhrSupported ); +support.ajax = xhrSupported = !!xhrSupported; + +jQuery.ajaxTransport( function( options ) { + var callback, errorCallback; + + // Cross domain only allowed if supported through XMLHttpRequest + if ( support.cors || xhrSupported && !options.crossDomain ) { + return { + send: function( headers, complete ) { + var i, + xhr = options.xhr(); + + xhr.open( + options.type, + options.url, + options.async, + options.username, + options.password + ); + + // Apply custom fields if provided + if ( options.xhrFields ) { + for ( i in options.xhrFields ) { + xhr[ i ] = options.xhrFields[ i ]; + } + } + + // Override mime type if needed + if ( options.mimeType && xhr.overrideMimeType ) { + xhr.overrideMimeType( options.mimeType ); + } + + // X-Requested-With header + // For cross-domain requests, seeing as conditions for a preflight are + // akin to a jigsaw puzzle, we simply never set it to be sure. + // (it can always be set on a per-request basis or even using ajaxSetup) + // For same-domain requests, won't change header if already provided. + if ( !options.crossDomain && !headers[ "X-Requested-With" ] ) { + headers[ "X-Requested-With" ] = "XMLHttpRequest"; + } + + // Set headers + for ( i in headers ) { + xhr.setRequestHeader( i, headers[ i ] ); + } + + // Callback + callback = function( type ) { + return function() { + if ( callback ) { + callback = errorCallback = xhr.onload = + xhr.onerror = xhr.onabort = xhr.ontimeout = + xhr.onreadystatechange = null; + + if ( type === "abort" ) { + xhr.abort(); + } else if ( type === "error" ) { + + // Support: IE <=9 only + // On a manual native abort, IE9 throws + // errors on any property access that is not readyState + if ( typeof xhr.status !== "number" ) { + complete( 0, "error" ); + } else { + complete( + + // File: protocol always yields status 0; see #8605, #14207 + xhr.status, + xhr.statusText + ); + } + } else { + complete( + xhrSuccessStatus[ xhr.status ] || xhr.status, + xhr.statusText, + + // Support: IE <=9 only + // IE9 has no XHR2 but throws on binary (trac-11426) + // For XHR2 non-text, let the caller handle it (gh-2498) + ( xhr.responseType || "text" ) !== "text" || + typeof xhr.responseText !== "string" ? + { binary: xhr.response } : + { text: xhr.responseText }, + xhr.getAllResponseHeaders() + ); + } + } + }; + }; + + // Listen to events + xhr.onload = callback(); + errorCallback = xhr.onerror = xhr.ontimeout = callback( "error" ); + + // Support: IE 9 only + // Use onreadystatechange to replace onabort + // to handle uncaught aborts + if ( xhr.onabort !== undefined ) { + xhr.onabort = errorCallback; + } else { + xhr.onreadystatechange = function() { + + // Check readyState before timeout as it changes + if ( xhr.readyState === 4 ) { + + // Allow onerror to be called first, + // but that will not handle a native abort + // Also, save errorCallback to a variable + // as xhr.onerror cannot be accessed + window.setTimeout( function() { + if ( callback ) { + errorCallback(); + } + } ); + } + }; + } + + // Create the abort callback + callback = callback( "abort" ); + + try { + + // Do send the request (this may raise an exception) + xhr.send( options.hasContent && options.data || null ); + } catch ( e ) { + + // #14683: Only rethrow if this hasn't been notified as an error yet + if ( callback ) { + throw e; + } + } + }, + + abort: function() { + if ( callback ) { + callback(); + } + } + }; + } +} ); + + + + +// Prevent auto-execution of scripts when no explicit dataType was provided (See gh-2432) +jQuery.ajaxPrefilter( function( s ) { + if ( s.crossDomain ) { + s.contents.script = false; + } +} ); + +// Install script dataType +jQuery.ajaxSetup( { + accepts: { + script: "text/javascript, application/javascript, " + + "application/ecmascript, application/x-ecmascript" + }, + contents: { + script: /\b(?:java|ecma)script\b/ + }, + converters: { + "text script": function( text ) { + jQuery.globalEval( text ); + return text; + } + } +} ); + +// Handle cache's special case and crossDomain +jQuery.ajaxPrefilter( "script", function( s ) { + if ( s.cache === undefined ) { + s.cache = false; + } + if ( s.crossDomain ) { + s.type = "GET"; + } +} ); + +// Bind script tag hack transport +jQuery.ajaxTransport( "script", function( s ) { + + // This transport only deals with cross domain or forced-by-attrs requests + if ( s.crossDomain || s.scriptAttrs ) { + var script, callback; + return { + send: function( _, complete ) { + script = jQuery( "\r\n"; + +// inject VBScript +document.write(IEBinaryToArray_ByteStr_Script); + +global.JSZipUtils._getBinaryFromXHR = function (xhr) { + var binary = xhr.responseBody; + var byteMapping = {}; + for ( var i = 0; i < 256; i++ ) { + for ( var j = 0; j < 256; j++ ) { + byteMapping[ String.fromCharCode( i + (j << 8) ) ] = + String.fromCharCode(i) + String.fromCharCode(j); + } + } + var rawBytes = IEBinaryToArray_ByteStr(binary); + var lastChr = IEBinaryToArray_ByteStr_Last(binary); + return rawBytes.replace(/[\s\S]/g, function( match ) { + return byteMapping[match]; + }) + lastChr; +}; + +// enforcing Stuk's coding style +// vim: set shiftwidth=4 softtabstop=4: + +},{}]},{},[1]) +; diff --git a/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils-ie.min.js b/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils-ie.min.js new file mode 100644 index 0000000000..93d8bc8ef2 --- /dev/null +++ b/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils-ie.min.js @@ -0,0 +1,10 @@ +/*! + +JSZipUtils - A collection of cross-browser utilities to go along with JSZip. + + +(c) 2014 Stuart Knightley, David Duponchel +Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip-utils/master/LICENSE.markdown. + +*/ +!function a(b,c,d){function e(g,h){if(!c[g]){if(!b[g]){var i="function"==typeof require&&require;if(!h&&i)return i(g,!0);if(f)return f(g,!0);throw new Error("Cannot find module '"+g+"'")}var j=c[g]={exports:{}};b[g][0].call(j.exports,function(a){var c=b[g][1][a];return e(c?c:a)},j,j.exports,a,b,c,d)}return c[g].exports}for(var f="function"==typeof require&&require,g=0;g\r\n";document.write(b),a.JSZipUtils._getBinaryFromXHR=function(a){for(var b=a.responseBody,c={},d=0;256>d;d++)for(var e=0;256>e;e++)c[String.fromCharCode(d+(e<<8))]=String.fromCharCode(d)+String.fromCharCode(e);var f=IEBinaryToArray_ByteStr(b),g=IEBinaryToArray_ByteStr_Last(b);return f.replace(/[\s\S]/g,function(a){return c[a]})+g}},{}]},{},[1]); diff --git a/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils.js b/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils.js new file mode 100644 index 0000000000..775895ec92 --- /dev/null +++ b/static/apidocs/javadoc/jquery/jszip-utils/dist/jszip-utils.js @@ -0,0 +1,118 @@ +/*! + +JSZipUtils - A collection of cross-browser utilities to go along with JSZip. + + +(c) 2014 Stuart Knightley, David Duponchel +Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip-utils/master/LICENSE.markdown. + +*/ +!function(e){"object"==typeof exports?module.exports=e():"function"==typeof define&&define.amd?define(e):"undefined"!=typeof window?window.JSZipUtils=e():"undefined"!=typeof global?global.JSZipUtils=e():"undefined"!=typeof self&&(self.JSZipUtils=e())}(function(){var define,module,exports;return (function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);throw new Error("Cannot find module '"+o+"'")}var f=n[o]={exports:{}};t[o][0].call(f.exports,function(e){var n=t[o][1][e];return s(n?n:e)},f,f.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o + +(c) 2014 Stuart Knightley, David Duponchel +Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip-utils/master/LICENSE.markdown. + +*/ +!function(a){"object"==typeof exports?module.exports=a():"function"==typeof define&&define.amd?define(a):"undefined"!=typeof window?window.JSZipUtils=a():"undefined"!=typeof global?global.JSZipUtils=a():"undefined"!=typeof self&&(self.JSZipUtils=a())}(function(){return function a(b,c,d){function e(g,h){if(!c[g]){if(!b[g]){var i="function"==typeof require&&require;if(!h&&i)return i(g,!0);if(f)return f(g,!0);throw new Error("Cannot find module '"+g+"'")}var j=c[g]={exports:{}};b[g][0].call(j.exports,function(a){var c=b[g][1][a];return e(c?c:a)},j,j.exports,a,b,c,d)}return c[g].exports}for(var f="function"==typeof require&&require,g=0;g + +(c) 2009-2016 Stuart Knightley +Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip/master/LICENSE.markdown. + +JSZip uses the library pako released under the MIT license : +https://github.com/nodeca/pako/blob/master/LICENSE +*/ + +(function(f){if(typeof exports==="object"&&typeof module!=="undefined"){module.exports=f()}else if(typeof define==="function"&&define.amd){define([],f)}else{var g;if(typeof window!=="undefined"){g=window}else if(typeof global!=="undefined"){g=global}else if(typeof self!=="undefined"){g=self}else{g=this}g.JSZip = f()}})(function(){var define,module,exports;return (function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o> 2; + enc2 = ((chr1 & 3) << 4) | (chr2 >> 4); + enc3 = remainingBytes > 1 ? (((chr2 & 15) << 2) | (chr3 >> 6)) : 64; + enc4 = remainingBytes > 2 ? (chr3 & 63) : 64; + + output.push(_keyStr.charAt(enc1) + _keyStr.charAt(enc2) + _keyStr.charAt(enc3) + _keyStr.charAt(enc4)); + + } + + return output.join(""); +}; + +// public method for decoding +exports.decode = function(input) { + var chr1, chr2, chr3; + var enc1, enc2, enc3, enc4; + var i = 0, resultIndex = 0; + + var dataUrlPrefix = "data:"; + + if (input.substr(0, dataUrlPrefix.length) === dataUrlPrefix) { + // This is a common error: people give a data url + // (data:image/png;base64,iVBOR...) with a {base64: true} and + // wonders why things don't work. + // We can detect that the string input looks like a data url but we + // *can't* be sure it is one: removing everything up to the comma would + // be too dangerous. + throw new Error("Invalid base64 input, it looks like a data url."); + } + + input = input.replace(/[^A-Za-z0-9\+\/\=]/g, ""); + + var totalLength = input.length * 3 / 4; + if(input.charAt(input.length - 1) === _keyStr.charAt(64)) { + totalLength--; + } + if(input.charAt(input.length - 2) === _keyStr.charAt(64)) { + totalLength--; + } + if (totalLength % 1 !== 0) { + // totalLength is not an integer, the length does not match a valid + // base64 content. That can happen if: + // - the input is not a base64 content + // - the input is *almost* a base64 content, with a extra chars at the + // beginning or at the end + // - the input uses a base64 variant (base64url for example) + throw new Error("Invalid base64 input, bad content length."); + } + var output; + if (support.uint8array) { + output = new Uint8Array(totalLength|0); + } else { + output = new Array(totalLength|0); + } + + while (i < input.length) { + + enc1 = _keyStr.indexOf(input.charAt(i++)); + enc2 = _keyStr.indexOf(input.charAt(i++)); + enc3 = _keyStr.indexOf(input.charAt(i++)); + enc4 = _keyStr.indexOf(input.charAt(i++)); + + chr1 = (enc1 << 2) | (enc2 >> 4); + chr2 = ((enc2 & 15) << 4) | (enc3 >> 2); + chr3 = ((enc3 & 3) << 6) | enc4; + + output[resultIndex++] = chr1; + + if (enc3 !== 64) { + output[resultIndex++] = chr2; + } + if (enc4 !== 64) { + output[resultIndex++] = chr3; + } + + } + + return output; +}; + +},{"./support":30,"./utils":32}],2:[function(require,module,exports){ +'use strict'; + +var external = require("./external"); +var DataWorker = require('./stream/DataWorker'); +var Crc32Probe = require('./stream/Crc32Probe'); +var DataLengthProbe = require('./stream/DataLengthProbe'); + +/** + * Represent a compressed object, with everything needed to decompress it. + * @constructor + * @param {number} compressedSize the size of the data compressed. + * @param {number} uncompressedSize the size of the data after decompression. + * @param {number} crc32 the crc32 of the decompressed file. + * @param {object} compression the type of compression, see lib/compressions.js. + * @param {String|ArrayBuffer|Uint8Array|Buffer} data the compressed data. + */ +function CompressedObject(compressedSize, uncompressedSize, crc32, compression, data) { + this.compressedSize = compressedSize; + this.uncompressedSize = uncompressedSize; + this.crc32 = crc32; + this.compression = compression; + this.compressedContent = data; +} + +CompressedObject.prototype = { + /** + * Create a worker to get the uncompressed content. + * @return {GenericWorker} the worker. + */ + getContentWorker: function () { + var worker = new DataWorker(external.Promise.resolve(this.compressedContent)) + .pipe(this.compression.uncompressWorker()) + .pipe(new DataLengthProbe("data_length")); + + var that = this; + worker.on("end", function () { + if (this.streamInfo['data_length'] !== that.uncompressedSize) { + throw new Error("Bug : uncompressed data size mismatch"); + } + }); + return worker; + }, + /** + * Create a worker to get the compressed content. + * @return {GenericWorker} the worker. + */ + getCompressedWorker: function () { + return new DataWorker(external.Promise.resolve(this.compressedContent)) + .withStreamInfo("compressedSize", this.compressedSize) + .withStreamInfo("uncompressedSize", this.uncompressedSize) + .withStreamInfo("crc32", this.crc32) + .withStreamInfo("compression", this.compression) + ; + } +}; + +/** + * Chain the given worker with other workers to compress the content with the + * given compression. + * @param {GenericWorker} uncompressedWorker the worker to pipe. + * @param {Object} compression the compression object. + * @param {Object} compressionOptions the options to use when compressing. + * @return {GenericWorker} the new worker compressing the content. + */ +CompressedObject.createWorkerFrom = function (uncompressedWorker, compression, compressionOptions) { + return uncompressedWorker + .pipe(new Crc32Probe()) + .pipe(new DataLengthProbe("uncompressedSize")) + .pipe(compression.compressWorker(compressionOptions)) + .pipe(new DataLengthProbe("compressedSize")) + .withStreamInfo("compression", compression); +}; + +module.exports = CompressedObject; + +},{"./external":6,"./stream/Crc32Probe":25,"./stream/DataLengthProbe":26,"./stream/DataWorker":27}],3:[function(require,module,exports){ +'use strict'; + +var GenericWorker = require("./stream/GenericWorker"); + +exports.STORE = { + magic: "\x00\x00", + compressWorker : function (compressionOptions) { + return new GenericWorker("STORE compression"); + }, + uncompressWorker : function () { + return new GenericWorker("STORE decompression"); + } +}; +exports.DEFLATE = require('./flate'); + +},{"./flate":7,"./stream/GenericWorker":28}],4:[function(require,module,exports){ +'use strict'; + +var utils = require('./utils'); + +/** + * The following functions come from pako, from pako/lib/zlib/crc32.js + * released under the MIT license, see pako https://github.com/nodeca/pako/ + */ + +// Use ordinary array, since untyped makes no boost here +function makeTable() { + var c, table = []; + + for(var n =0; n < 256; n++){ + c = n; + for(var k =0; k < 8; k++){ + c = ((c&1) ? (0xEDB88320 ^ (c >>> 1)) : (c >>> 1)); + } + table[n] = c; + } + + return table; +} + +// Create table on load. Just 255 signed longs. Not a problem. +var crcTable = makeTable(); + + +function crc32(crc, buf, len, pos) { + var t = crcTable, end = pos + len; + + crc = crc ^ (-1); + + for (var i = pos; i < end; i++ ) { + crc = (crc >>> 8) ^ t[(crc ^ buf[i]) & 0xFF]; + } + + return (crc ^ (-1)); // >>> 0; +} + +// That's all for the pako functions. + +/** + * Compute the crc32 of a string. + * This is almost the same as the function crc32, but for strings. Using the + * same function for the two use cases leads to horrible performances. + * @param {Number} crc the starting value of the crc. + * @param {String} str the string to use. + * @param {Number} len the length of the string. + * @param {Number} pos the starting position for the crc32 computation. + * @return {Number} the computed crc32. + */ +function crc32str(crc, str, len, pos) { + var t = crcTable, end = pos + len; + + crc = crc ^ (-1); + + for (var i = pos; i < end; i++ ) { + crc = (crc >>> 8) ^ t[(crc ^ str.charCodeAt(i)) & 0xFF]; + } + + return (crc ^ (-1)); // >>> 0; +} + +module.exports = function crc32wrapper(input, crc) { + if (typeof input === "undefined" || !input.length) { + return 0; + } + + var isArray = utils.getTypeOf(input) !== "string"; + + if(isArray) { + return crc32(crc|0, input, input.length, 0); + } else { + return crc32str(crc|0, input, input.length, 0); + } +}; + +},{"./utils":32}],5:[function(require,module,exports){ +'use strict'; +exports.base64 = false; +exports.binary = false; +exports.dir = false; +exports.createFolders = true; +exports.date = null; +exports.compression = null; +exports.compressionOptions = null; +exports.comment = null; +exports.unixPermissions = null; +exports.dosPermissions = null; + +},{}],6:[function(require,module,exports){ +/* global Promise */ +'use strict'; + +// load the global object first: +// - it should be better integrated in the system (unhandledRejection in node) +// - the environment may have a custom Promise implementation (see zone.js) +var ES6Promise = null; +if (typeof Promise !== "undefined") { + ES6Promise = Promise; +} else { + ES6Promise = require("lie"); +} + +/** + * Let the user use/change some implementations. + */ +module.exports = { + Promise: ES6Promise +}; + +},{"lie":37}],7:[function(require,module,exports){ +'use strict'; +var USE_TYPEDARRAY = (typeof Uint8Array !== 'undefined') && (typeof Uint16Array !== 'undefined') && (typeof Uint32Array !== 'undefined'); + +var pako = require("pako"); +var utils = require("./utils"); +var GenericWorker = require("./stream/GenericWorker"); + +var ARRAY_TYPE = USE_TYPEDARRAY ? "uint8array" : "array"; + +exports.magic = "\x08\x00"; + +/** + * Create a worker that uses pako to inflate/deflate. + * @constructor + * @param {String} action the name of the pako function to call : either "Deflate" or "Inflate". + * @param {Object} options the options to use when (de)compressing. + */ +function FlateWorker(action, options) { + GenericWorker.call(this, "FlateWorker/" + action); + + this._pako = null; + this._pakoAction = action; + this._pakoOptions = options; + // the `meta` object from the last chunk received + // this allow this worker to pass around metadata + this.meta = {}; +} + +utils.inherits(FlateWorker, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +FlateWorker.prototype.processChunk = function (chunk) { + this.meta = chunk.meta; + if (this._pako === null) { + this._createPako(); + } + this._pako.push(utils.transformTo(ARRAY_TYPE, chunk.data), false); +}; + +/** + * @see GenericWorker.flush + */ +FlateWorker.prototype.flush = function () { + GenericWorker.prototype.flush.call(this); + if (this._pako === null) { + this._createPako(); + } + this._pako.push([], true); +}; +/** + * @see GenericWorker.cleanUp + */ +FlateWorker.prototype.cleanUp = function () { + GenericWorker.prototype.cleanUp.call(this); + this._pako = null; +}; + +/** + * Create the _pako object. + * TODO: lazy-loading this object isn't the best solution but it's the + * quickest. The best solution is to lazy-load the worker list. See also the + * issue #446. + */ +FlateWorker.prototype._createPako = function () { + this._pako = new pako[this._pakoAction]({ + raw: true, + level: this._pakoOptions.level || -1 // default compression + }); + var self = this; + this._pako.onData = function(data) { + self.push({ + data : data, + meta : self.meta + }); + }; +}; + +exports.compressWorker = function (compressionOptions) { + return new FlateWorker("Deflate", compressionOptions); +}; +exports.uncompressWorker = function () { + return new FlateWorker("Inflate", {}); +}; + +},{"./stream/GenericWorker":28,"./utils":32,"pako":38}],8:[function(require,module,exports){ +'use strict'; + +var utils = require('../utils'); +var GenericWorker = require('../stream/GenericWorker'); +var utf8 = require('../utf8'); +var crc32 = require('../crc32'); +var signature = require('../signature'); + +/** + * Transform an integer into a string in hexadecimal. + * @private + * @param {number} dec the number to convert. + * @param {number} bytes the number of bytes to generate. + * @returns {string} the result. + */ +var decToHex = function(dec, bytes) { + var hex = "", i; + for (i = 0; i < bytes; i++) { + hex += String.fromCharCode(dec & 0xff); + dec = dec >>> 8; + } + return hex; +}; + +/** + * Generate the UNIX part of the external file attributes. + * @param {Object} unixPermissions the unix permissions or null. + * @param {Boolean} isDir true if the entry is a directory, false otherwise. + * @return {Number} a 32 bit integer. + * + * adapted from http://unix.stackexchange.com/questions/14705/the-zip-formats-external-file-attribute : + * + * TTTTsstrwxrwxrwx0000000000ADVSHR + * ^^^^____________________________ file type, see zipinfo.c (UNX_*) + * ^^^_________________________ setuid, setgid, sticky + * ^^^^^^^^^________________ permissions + * ^^^^^^^^^^______ not used ? + * ^^^^^^ DOS attribute bits : Archive, Directory, Volume label, System file, Hidden, Read only + */ +var generateUnixExternalFileAttr = function (unixPermissions, isDir) { + + var result = unixPermissions; + if (!unixPermissions) { + // I can't use octal values in strict mode, hence the hexa. + // 040775 => 0x41fd + // 0100664 => 0x81b4 + result = isDir ? 0x41fd : 0x81b4; + } + return (result & 0xFFFF) << 16; +}; + +/** + * Generate the DOS part of the external file attributes. + * @param {Object} dosPermissions the dos permissions or null. + * @param {Boolean} isDir true if the entry is a directory, false otherwise. + * @return {Number} a 32 bit integer. + * + * Bit 0 Read-Only + * Bit 1 Hidden + * Bit 2 System + * Bit 3 Volume Label + * Bit 4 Directory + * Bit 5 Archive + */ +var generateDosExternalFileAttr = function (dosPermissions, isDir) { + + // the dir flag is already set for compatibility + return (dosPermissions || 0) & 0x3F; +}; + +/** + * Generate the various parts used in the construction of the final zip file. + * @param {Object} streamInfo the hash with information about the compressed file. + * @param {Boolean} streamedContent is the content streamed ? + * @param {Boolean} streamingEnded is the stream finished ? + * @param {number} offset the current offset from the start of the zip file. + * @param {String} platform let's pretend we are this platform (change platform dependents fields) + * @param {Function} encodeFileName the function to encode the file name / comment. + * @return {Object} the zip parts. + */ +var generateZipParts = function(streamInfo, streamedContent, streamingEnded, offset, platform, encodeFileName) { + var file = streamInfo['file'], + compression = streamInfo['compression'], + useCustomEncoding = encodeFileName !== utf8.utf8encode, + encodedFileName = utils.transformTo("string", encodeFileName(file.name)), + utfEncodedFileName = utils.transformTo("string", utf8.utf8encode(file.name)), + comment = file.comment, + encodedComment = utils.transformTo("string", encodeFileName(comment)), + utfEncodedComment = utils.transformTo("string", utf8.utf8encode(comment)), + useUTF8ForFileName = utfEncodedFileName.length !== file.name.length, + useUTF8ForComment = utfEncodedComment.length !== comment.length, + dosTime, + dosDate, + extraFields = "", + unicodePathExtraField = "", + unicodeCommentExtraField = "", + dir = file.dir, + date = file.date; + + + var dataInfo = { + crc32 : 0, + compressedSize : 0, + uncompressedSize : 0 + }; + + // if the content is streamed, the sizes/crc32 are only available AFTER + // the end of the stream. + if (!streamedContent || streamingEnded) { + dataInfo.crc32 = streamInfo['crc32']; + dataInfo.compressedSize = streamInfo['compressedSize']; + dataInfo.uncompressedSize = streamInfo['uncompressedSize']; + } + + var bitflag = 0; + if (streamedContent) { + // Bit 3: the sizes/crc32 are set to zero in the local header. + // The correct values are put in the data descriptor immediately + // following the compressed data. + bitflag |= 0x0008; + } + if (!useCustomEncoding && (useUTF8ForFileName || useUTF8ForComment)) { + // Bit 11: Language encoding flag (EFS). + bitflag |= 0x0800; + } + + + var extFileAttr = 0; + var versionMadeBy = 0; + if (dir) { + // dos or unix, we set the dos dir flag + extFileAttr |= 0x00010; + } + if(platform === "UNIX") { + versionMadeBy = 0x031E; // UNIX, version 3.0 + extFileAttr |= generateUnixExternalFileAttr(file.unixPermissions, dir); + } else { // DOS or other, fallback to DOS + versionMadeBy = 0x0014; // DOS, version 2.0 + extFileAttr |= generateDosExternalFileAttr(file.dosPermissions, dir); + } + + // date + // @see http://www.delorie.com/djgpp/doc/rbinter/it/52/13.html + // @see http://www.delorie.com/djgpp/doc/rbinter/it/65/16.html + // @see http://www.delorie.com/djgpp/doc/rbinter/it/66/16.html + + dosTime = date.getUTCHours(); + dosTime = dosTime << 6; + dosTime = dosTime | date.getUTCMinutes(); + dosTime = dosTime << 5; + dosTime = dosTime | date.getUTCSeconds() / 2; + + dosDate = date.getUTCFullYear() - 1980; + dosDate = dosDate << 4; + dosDate = dosDate | (date.getUTCMonth() + 1); + dosDate = dosDate << 5; + dosDate = dosDate | date.getUTCDate(); + + if (useUTF8ForFileName) { + // set the unicode path extra field. unzip needs at least one extra + // field to correctly handle unicode path, so using the path is as good + // as any other information. This could improve the situation with + // other archive managers too. + // This field is usually used without the utf8 flag, with a non + // unicode path in the header (winrar, winzip). This helps (a bit) + // with the messy Windows' default compressed folders feature but + // breaks on p7zip which doesn't seek the unicode path extra field. + // So for now, UTF-8 everywhere ! + unicodePathExtraField = + // Version + decToHex(1, 1) + + // NameCRC32 + decToHex(crc32(encodedFileName), 4) + + // UnicodeName + utfEncodedFileName; + + extraFields += + // Info-ZIP Unicode Path Extra Field + "\x75\x70" + + // size + decToHex(unicodePathExtraField.length, 2) + + // content + unicodePathExtraField; + } + + if(useUTF8ForComment) { + + unicodeCommentExtraField = + // Version + decToHex(1, 1) + + // CommentCRC32 + decToHex(crc32(encodedComment), 4) + + // UnicodeName + utfEncodedComment; + + extraFields += + // Info-ZIP Unicode Path Extra Field + "\x75\x63" + + // size + decToHex(unicodeCommentExtraField.length, 2) + + // content + unicodeCommentExtraField; + } + + var header = ""; + + // version needed to extract + header += "\x0A\x00"; + // general purpose bit flag + header += decToHex(bitflag, 2); + // compression method + header += compression.magic; + // last mod file time + header += decToHex(dosTime, 2); + // last mod file date + header += decToHex(dosDate, 2); + // crc-32 + header += decToHex(dataInfo.crc32, 4); + // compressed size + header += decToHex(dataInfo.compressedSize, 4); + // uncompressed size + header += decToHex(dataInfo.uncompressedSize, 4); + // file name length + header += decToHex(encodedFileName.length, 2); + // extra field length + header += decToHex(extraFields.length, 2); + + + var fileRecord = signature.LOCAL_FILE_HEADER + header + encodedFileName + extraFields; + + var dirRecord = signature.CENTRAL_FILE_HEADER + + // version made by (00: DOS) + decToHex(versionMadeBy, 2) + + // file header (common to file and central directory) + header + + // file comment length + decToHex(encodedComment.length, 2) + + // disk number start + "\x00\x00" + + // internal file attributes TODO + "\x00\x00" + + // external file attributes + decToHex(extFileAttr, 4) + + // relative offset of local header + decToHex(offset, 4) + + // file name + encodedFileName + + // extra field + extraFields + + // file comment + encodedComment; + + return { + fileRecord: fileRecord, + dirRecord: dirRecord + }; +}; + +/** + * Generate the EOCD record. + * @param {Number} entriesCount the number of entries in the zip file. + * @param {Number} centralDirLength the length (in bytes) of the central dir. + * @param {Number} localDirLength the length (in bytes) of the local dir. + * @param {String} comment the zip file comment as a binary string. + * @param {Function} encodeFileName the function to encode the comment. + * @return {String} the EOCD record. + */ +var generateCentralDirectoryEnd = function (entriesCount, centralDirLength, localDirLength, comment, encodeFileName) { + var dirEnd = ""; + var encodedComment = utils.transformTo("string", encodeFileName(comment)); + + // end of central dir signature + dirEnd = signature.CENTRAL_DIRECTORY_END + + // number of this disk + "\x00\x00" + + // number of the disk with the start of the central directory + "\x00\x00" + + // total number of entries in the central directory on this disk + decToHex(entriesCount, 2) + + // total number of entries in the central directory + decToHex(entriesCount, 2) + + // size of the central directory 4 bytes + decToHex(centralDirLength, 4) + + // offset of start of central directory with respect to the starting disk number + decToHex(localDirLength, 4) + + // .ZIP file comment length + decToHex(encodedComment.length, 2) + + // .ZIP file comment + encodedComment; + + return dirEnd; +}; + +/** + * Generate data descriptors for a file entry. + * @param {Object} streamInfo the hash generated by a worker, containing information + * on the file entry. + * @return {String} the data descriptors. + */ +var generateDataDescriptors = function (streamInfo) { + var descriptor = ""; + descriptor = signature.DATA_DESCRIPTOR + + // crc-32 4 bytes + decToHex(streamInfo['crc32'], 4) + + // compressed size 4 bytes + decToHex(streamInfo['compressedSize'], 4) + + // uncompressed size 4 bytes + decToHex(streamInfo['uncompressedSize'], 4); + + return descriptor; +}; + + +/** + * A worker to concatenate other workers to create a zip file. + * @param {Boolean} streamFiles `true` to stream the content of the files, + * `false` to accumulate it. + * @param {String} comment the comment to use. + * @param {String} platform the platform to use, "UNIX" or "DOS". + * @param {Function} encodeFileName the function to encode file names and comments. + */ +function ZipFileWorker(streamFiles, comment, platform, encodeFileName) { + GenericWorker.call(this, "ZipFileWorker"); + // The number of bytes written so far. This doesn't count accumulated chunks. + this.bytesWritten = 0; + // The comment of the zip file + this.zipComment = comment; + // The platform "generating" the zip file. + this.zipPlatform = platform; + // the function to encode file names and comments. + this.encodeFileName = encodeFileName; + // Should we stream the content of the files ? + this.streamFiles = streamFiles; + // If `streamFiles` is false, we will need to accumulate the content of the + // files to calculate sizes / crc32 (and write them *before* the content). + // This boolean indicates if we are accumulating chunks (it will change a lot + // during the lifetime of this worker). + this.accumulate = false; + // The buffer receiving chunks when accumulating content. + this.contentBuffer = []; + // The list of generated directory records. + this.dirRecords = []; + // The offset (in bytes) from the beginning of the zip file for the current source. + this.currentSourceOffset = 0; + // The total number of entries in this zip file. + this.entriesCount = 0; + // the name of the file currently being added, null when handling the end of the zip file. + // Used for the emitted metadata. + this.currentFile = null; + + + + this._sources = []; +} +utils.inherits(ZipFileWorker, GenericWorker); + +/** + * @see GenericWorker.push + */ +ZipFileWorker.prototype.push = function (chunk) { + + var currentFilePercent = chunk.meta.percent || 0; + var entriesCount = this.entriesCount; + var remainingFiles = this._sources.length; + + if(this.accumulate) { + this.contentBuffer.push(chunk); + } else { + this.bytesWritten += chunk.data.length; + + GenericWorker.prototype.push.call(this, { + data : chunk.data, + meta : { + currentFile : this.currentFile, + percent : entriesCount ? (currentFilePercent + 100 * (entriesCount - remainingFiles - 1)) / entriesCount : 100 + } + }); + } +}; + +/** + * The worker started a new source (an other worker). + * @param {Object} streamInfo the streamInfo object from the new source. + */ +ZipFileWorker.prototype.openedSource = function (streamInfo) { + this.currentSourceOffset = this.bytesWritten; + this.currentFile = streamInfo['file'].name; + + var streamedContent = this.streamFiles && !streamInfo['file'].dir; + + // don't stream folders (because they don't have any content) + if(streamedContent) { + var record = generateZipParts(streamInfo, streamedContent, false, this.currentSourceOffset, this.zipPlatform, this.encodeFileName); + this.push({ + data : record.fileRecord, + meta : {percent:0} + }); + } else { + // we need to wait for the whole file before pushing anything + this.accumulate = true; + } +}; + +/** + * The worker finished a source (an other worker). + * @param {Object} streamInfo the streamInfo object from the finished source. + */ +ZipFileWorker.prototype.closedSource = function (streamInfo) { + this.accumulate = false; + var streamedContent = this.streamFiles && !streamInfo['file'].dir; + var record = generateZipParts(streamInfo, streamedContent, true, this.currentSourceOffset, this.zipPlatform, this.encodeFileName); + + this.dirRecords.push(record.dirRecord); + if(streamedContent) { + // after the streamed file, we put data descriptors + this.push({ + data : generateDataDescriptors(streamInfo), + meta : {percent:100} + }); + } else { + // the content wasn't streamed, we need to push everything now + // first the file record, then the content + this.push({ + data : record.fileRecord, + meta : {percent:0} + }); + while(this.contentBuffer.length) { + this.push(this.contentBuffer.shift()); + } + } + this.currentFile = null; +}; + +/** + * @see GenericWorker.flush + */ +ZipFileWorker.prototype.flush = function () { + + var localDirLength = this.bytesWritten; + for(var i = 0; i < this.dirRecords.length; i++) { + this.push({ + data : this.dirRecords[i], + meta : {percent:100} + }); + } + var centralDirLength = this.bytesWritten - localDirLength; + + var dirEnd = generateCentralDirectoryEnd(this.dirRecords.length, centralDirLength, localDirLength, this.zipComment, this.encodeFileName); + + this.push({ + data : dirEnd, + meta : {percent:100} + }); +}; + +/** + * Prepare the next source to be read. + */ +ZipFileWorker.prototype.prepareNextSource = function () { + this.previous = this._sources.shift(); + this.openedSource(this.previous.streamInfo); + if (this.isPaused) { + this.previous.pause(); + } else { + this.previous.resume(); + } +}; + +/** + * @see GenericWorker.registerPrevious + */ +ZipFileWorker.prototype.registerPrevious = function (previous) { + this._sources.push(previous); + var self = this; + + previous.on('data', function (chunk) { + self.processChunk(chunk); + }); + previous.on('end', function () { + self.closedSource(self.previous.streamInfo); + if(self._sources.length) { + self.prepareNextSource(); + } else { + self.end(); + } + }); + previous.on('error', function (e) { + self.error(e); + }); + return this; +}; + +/** + * @see GenericWorker.resume + */ +ZipFileWorker.prototype.resume = function () { + if(!GenericWorker.prototype.resume.call(this)) { + return false; + } + + if (!this.previous && this._sources.length) { + this.prepareNextSource(); + return true; + } + if (!this.previous && !this._sources.length && !this.generatedError) { + this.end(); + return true; + } +}; + +/** + * @see GenericWorker.error + */ +ZipFileWorker.prototype.error = function (e) { + var sources = this._sources; + if(!GenericWorker.prototype.error.call(this, e)) { + return false; + } + for(var i = 0; i < sources.length; i++) { + try { + sources[i].error(e); + } catch(e) { + // the `error` exploded, nothing to do + } + } + return true; +}; + +/** + * @see GenericWorker.lock + */ +ZipFileWorker.prototype.lock = function () { + GenericWorker.prototype.lock.call(this); + var sources = this._sources; + for(var i = 0; i < sources.length; i++) { + sources[i].lock(); + } +}; + +module.exports = ZipFileWorker; + +},{"../crc32":4,"../signature":23,"../stream/GenericWorker":28,"../utf8":31,"../utils":32}],9:[function(require,module,exports){ +'use strict'; + +var compressions = require('../compressions'); +var ZipFileWorker = require('./ZipFileWorker'); + +/** + * Find the compression to use. + * @param {String} fileCompression the compression defined at the file level, if any. + * @param {String} zipCompression the compression defined at the load() level. + * @return {Object} the compression object to use. + */ +var getCompression = function (fileCompression, zipCompression) { + + var compressionName = fileCompression || zipCompression; + var compression = compressions[compressionName]; + if (!compression) { + throw new Error(compressionName + " is not a valid compression method !"); + } + return compression; +}; + +/** + * Create a worker to generate a zip file. + * @param {JSZip} zip the JSZip instance at the right root level. + * @param {Object} options to generate the zip file. + * @param {String} comment the comment to use. + */ +exports.generateWorker = function (zip, options, comment) { + + var zipFileWorker = new ZipFileWorker(options.streamFiles, comment, options.platform, options.encodeFileName); + var entriesCount = 0; + try { + + zip.forEach(function (relativePath, file) { + entriesCount++; + var compression = getCompression(file.options.compression, options.compression); + var compressionOptions = file.options.compressionOptions || options.compressionOptions || {}; + var dir = file.dir, date = file.date; + + file._compressWorker(compression, compressionOptions) + .withStreamInfo("file", { + name : relativePath, + dir : dir, + date : date, + comment : file.comment || "", + unixPermissions : file.unixPermissions, + dosPermissions : file.dosPermissions + }) + .pipe(zipFileWorker); + }); + zipFileWorker.entriesCount = entriesCount; + } catch (e) { + zipFileWorker.error(e); + } + + return zipFileWorker; +}; + +},{"../compressions":3,"./ZipFileWorker":8}],10:[function(require,module,exports){ +'use strict'; + +/** + * Representation a of zip file in js + * @constructor + */ +function JSZip() { + // if this constructor is used without `new`, it adds `new` before itself: + if(!(this instanceof JSZip)) { + return new JSZip(); + } + + if(arguments.length) { + throw new Error("The constructor with parameters has been removed in JSZip 3.0, please check the upgrade guide."); + } + + // object containing the files : + // { + // "folder/" : {...}, + // "folder/data.txt" : {...} + // } + // NOTE: we use a null prototype because we do not + // want filenames like "toString" coming from a zip file + // to overwrite methods and attributes in a normal Object. + this.files = Object.create(null); + + this.comment = null; + + // Where we are in the hierarchy + this.root = ""; + this.clone = function() { + var newObj = new JSZip(); + for (var i in this) { + if (typeof this[i] !== "function") { + newObj[i] = this[i]; + } + } + return newObj; + }; +} +JSZip.prototype = require('./object'); +JSZip.prototype.loadAsync = require('./load'); +JSZip.support = require('./support'); +JSZip.defaults = require('./defaults'); + +// TODO find a better way to handle this version, +// a require('package.json').version doesn't work with webpack, see #327 +JSZip.version = "3.7.1"; + +JSZip.loadAsync = function (content, options) { + return new JSZip().loadAsync(content, options); +}; + +JSZip.external = require("./external"); +module.exports = JSZip; + +},{"./defaults":5,"./external":6,"./load":11,"./object":15,"./support":30}],11:[function(require,module,exports){ +'use strict'; +var utils = require('./utils'); +var external = require("./external"); +var utf8 = require('./utf8'); +var ZipEntries = require('./zipEntries'); +var Crc32Probe = require('./stream/Crc32Probe'); +var nodejsUtils = require("./nodejsUtils"); + +/** + * Check the CRC32 of an entry. + * @param {ZipEntry} zipEntry the zip entry to check. + * @return {Promise} the result. + */ +function checkEntryCRC32(zipEntry) { + return new external.Promise(function (resolve, reject) { + var worker = zipEntry.decompressed.getContentWorker().pipe(new Crc32Probe()); + worker.on("error", function (e) { + reject(e); + }) + .on("end", function () { + if (worker.streamInfo.crc32 !== zipEntry.decompressed.crc32) { + reject(new Error("Corrupted zip : CRC32 mismatch")); + } else { + resolve(); + } + }) + .resume(); + }); +} + +module.exports = function (data, options) { + var zip = this; + options = utils.extend(options || {}, { + base64: false, + checkCRC32: false, + optimizedBinaryString: false, + createFolders: false, + decodeFileName: utf8.utf8decode + }); + + if (nodejsUtils.isNode && nodejsUtils.isStream(data)) { + return external.Promise.reject(new Error("JSZip can't accept a stream when loading a zip file.")); + } + + return utils.prepareContent("the loaded zip file", data, true, options.optimizedBinaryString, options.base64) + .then(function (data) { + var zipEntries = new ZipEntries(options); + zipEntries.load(data); + return zipEntries; + }).then(function checkCRC32(zipEntries) { + var promises = [external.Promise.resolve(zipEntries)]; + var files = zipEntries.files; + if (options.checkCRC32) { + for (var i = 0; i < files.length; i++) { + promises.push(checkEntryCRC32(files[i])); + } + } + return external.Promise.all(promises); + }).then(function addFiles(results) { + var zipEntries = results.shift(); + var files = zipEntries.files; + for (var i = 0; i < files.length; i++) { + var input = files[i]; + zip.file(input.fileNameStr, input.decompressed, { + binary: true, + optimizedBinaryString: true, + date: input.date, + dir: input.dir, + comment: input.fileCommentStr.length ? input.fileCommentStr : null, + unixPermissions: input.unixPermissions, + dosPermissions: input.dosPermissions, + createFolders: options.createFolders + }); + } + if (zipEntries.zipComment.length) { + zip.comment = zipEntries.zipComment; + } + + return zip; + }); +}; + +},{"./external":6,"./nodejsUtils":14,"./stream/Crc32Probe":25,"./utf8":31,"./utils":32,"./zipEntries":33}],12:[function(require,module,exports){ +"use strict"; + +var utils = require('../utils'); +var GenericWorker = require('../stream/GenericWorker'); + +/** + * A worker that use a nodejs stream as source. + * @constructor + * @param {String} filename the name of the file entry for this stream. + * @param {Readable} stream the nodejs stream. + */ +function NodejsStreamInputAdapter(filename, stream) { + GenericWorker.call(this, "Nodejs stream input adapter for " + filename); + this._upstreamEnded = false; + this._bindStream(stream); +} + +utils.inherits(NodejsStreamInputAdapter, GenericWorker); + +/** + * Prepare the stream and bind the callbacks on it. + * Do this ASAP on node 0.10 ! A lazy binding doesn't always work. + * @param {Stream} stream the nodejs stream to use. + */ +NodejsStreamInputAdapter.prototype._bindStream = function (stream) { + var self = this; + this._stream = stream; + stream.pause(); + stream + .on("data", function (chunk) { + self.push({ + data: chunk, + meta : { + percent : 0 + } + }); + }) + .on("error", function (e) { + if(self.isPaused) { + this.generatedError = e; + } else { + self.error(e); + } + }) + .on("end", function () { + if(self.isPaused) { + self._upstreamEnded = true; + } else { + self.end(); + } + }); +}; +NodejsStreamInputAdapter.prototype.pause = function () { + if(!GenericWorker.prototype.pause.call(this)) { + return false; + } + this._stream.pause(); + return true; +}; +NodejsStreamInputAdapter.prototype.resume = function () { + if(!GenericWorker.prototype.resume.call(this)) { + return false; + } + + if(this._upstreamEnded) { + this.end(); + } else { + this._stream.resume(); + } + + return true; +}; + +module.exports = NodejsStreamInputAdapter; + +},{"../stream/GenericWorker":28,"../utils":32}],13:[function(require,module,exports){ +'use strict'; + +var Readable = require('readable-stream').Readable; + +var utils = require('../utils'); +utils.inherits(NodejsStreamOutputAdapter, Readable); + +/** +* A nodejs stream using a worker as source. +* @see the SourceWrapper in http://nodejs.org/api/stream.html +* @constructor +* @param {StreamHelper} helper the helper wrapping the worker +* @param {Object} options the nodejs stream options +* @param {Function} updateCb the update callback. +*/ +function NodejsStreamOutputAdapter(helper, options, updateCb) { + Readable.call(this, options); + this._helper = helper; + + var self = this; + helper.on("data", function (data, meta) { + if (!self.push(data)) { + self._helper.pause(); + } + if(updateCb) { + updateCb(meta); + } + }) + .on("error", function(e) { + self.emit('error', e); + }) + .on("end", function () { + self.push(null); + }); +} + + +NodejsStreamOutputAdapter.prototype._read = function() { + this._helper.resume(); +}; + +module.exports = NodejsStreamOutputAdapter; + +},{"../utils":32,"readable-stream":16}],14:[function(require,module,exports){ +'use strict'; + +module.exports = { + /** + * True if this is running in Nodejs, will be undefined in a browser. + * In a browser, browserify won't include this file and the whole module + * will be resolved an empty object. + */ + isNode : typeof Buffer !== "undefined", + /** + * Create a new nodejs Buffer from an existing content. + * @param {Object} data the data to pass to the constructor. + * @param {String} encoding the encoding to use. + * @return {Buffer} a new Buffer. + */ + newBufferFrom: function(data, encoding) { + if (Buffer.from && Buffer.from !== Uint8Array.from) { + return Buffer.from(data, encoding); + } else { + if (typeof data === "number") { + // Safeguard for old Node.js versions. On newer versions, + // Buffer.from(number) / Buffer(number, encoding) already throw. + throw new Error("The \"data\" argument must not be a number"); + } + return new Buffer(data, encoding); + } + }, + /** + * Create a new nodejs Buffer with the specified size. + * @param {Integer} size the size of the buffer. + * @return {Buffer} a new Buffer. + */ + allocBuffer: function (size) { + if (Buffer.alloc) { + return Buffer.alloc(size); + } else { + var buf = new Buffer(size); + buf.fill(0); + return buf; + } + }, + /** + * Find out if an object is a Buffer. + * @param {Object} b the object to test. + * @return {Boolean} true if the object is a Buffer, false otherwise. + */ + isBuffer : function(b){ + return Buffer.isBuffer(b); + }, + + isStream : function (obj) { + return obj && + typeof obj.on === "function" && + typeof obj.pause === "function" && + typeof obj.resume === "function"; + } +}; + +},{}],15:[function(require,module,exports){ +'use strict'; +var utf8 = require('./utf8'); +var utils = require('./utils'); +var GenericWorker = require('./stream/GenericWorker'); +var StreamHelper = require('./stream/StreamHelper'); +var defaults = require('./defaults'); +var CompressedObject = require('./compressedObject'); +var ZipObject = require('./zipObject'); +var generate = require("./generate"); +var nodejsUtils = require("./nodejsUtils"); +var NodejsStreamInputAdapter = require("./nodejs/NodejsStreamInputAdapter"); + + +/** + * Add a file in the current folder. + * @private + * @param {string} name the name of the file + * @param {String|ArrayBuffer|Uint8Array|Buffer} data the data of the file + * @param {Object} originalOptions the options of the file + * @return {Object} the new file. + */ +var fileAdd = function(name, data, originalOptions) { + // be sure sub folders exist + var dataType = utils.getTypeOf(data), + parent; + + + /* + * Correct options. + */ + + var o = utils.extend(originalOptions || {}, defaults); + o.date = o.date || new Date(); + if (o.compression !== null) { + o.compression = o.compression.toUpperCase(); + } + + if (typeof o.unixPermissions === "string") { + o.unixPermissions = parseInt(o.unixPermissions, 8); + } + + // UNX_IFDIR 0040000 see zipinfo.c + if (o.unixPermissions && (o.unixPermissions & 0x4000)) { + o.dir = true; + } + // Bit 4 Directory + if (o.dosPermissions && (o.dosPermissions & 0x0010)) { + o.dir = true; + } + + if (o.dir) { + name = forceTrailingSlash(name); + } + if (o.createFolders && (parent = parentFolder(name))) { + folderAdd.call(this, parent, true); + } + + var isUnicodeString = dataType === "string" && o.binary === false && o.base64 === false; + if (!originalOptions || typeof originalOptions.binary === "undefined") { + o.binary = !isUnicodeString; + } + + + var isCompressedEmpty = (data instanceof CompressedObject) && data.uncompressedSize === 0; + + if (isCompressedEmpty || o.dir || !data || data.length === 0) { + o.base64 = false; + o.binary = true; + data = ""; + o.compression = "STORE"; + dataType = "string"; + } + + /* + * Convert content to fit. + */ + + var zipObjectContent = null; + if (data instanceof CompressedObject || data instanceof GenericWorker) { + zipObjectContent = data; + } else if (nodejsUtils.isNode && nodejsUtils.isStream(data)) { + zipObjectContent = new NodejsStreamInputAdapter(name, data); + } else { + zipObjectContent = utils.prepareContent(name, data, o.binary, o.optimizedBinaryString, o.base64); + } + + var object = new ZipObject(name, zipObjectContent, o); + this.files[name] = object; + /* + TODO: we can't throw an exception because we have async promises + (we can have a promise of a Date() for example) but returning a + promise is useless because file(name, data) returns the JSZip + object for chaining. Should we break that to allow the user + to catch the error ? + + return external.Promise.resolve(zipObjectContent) + .then(function () { + return object; + }); + */ +}; + +/** + * Find the parent folder of the path. + * @private + * @param {string} path the path to use + * @return {string} the parent folder, or "" + */ +var parentFolder = function (path) { + if (path.slice(-1) === '/') { + path = path.substring(0, path.length - 1); + } + var lastSlash = path.lastIndexOf('/'); + return (lastSlash > 0) ? path.substring(0, lastSlash) : ""; +}; + +/** + * Returns the path with a slash at the end. + * @private + * @param {String} path the path to check. + * @return {String} the path with a trailing slash. + */ +var forceTrailingSlash = function(path) { + // Check the name ends with a / + if (path.slice(-1) !== "/") { + path += "/"; // IE doesn't like substr(-1) + } + return path; +}; + +/** + * Add a (sub) folder in the current folder. + * @private + * @param {string} name the folder's name + * @param {boolean=} [createFolders] If true, automatically create sub + * folders. Defaults to false. + * @return {Object} the new folder. + */ +var folderAdd = function(name, createFolders) { + createFolders = (typeof createFolders !== 'undefined') ? createFolders : defaults.createFolders; + + name = forceTrailingSlash(name); + + // Does this folder already exist? + if (!this.files[name]) { + fileAdd.call(this, name, null, { + dir: true, + createFolders: createFolders + }); + } + return this.files[name]; +}; + +/** +* Cross-window, cross-Node-context regular expression detection +* @param {Object} object Anything +* @return {Boolean} true if the object is a regular expression, +* false otherwise +*/ +function isRegExp(object) { + return Object.prototype.toString.call(object) === "[object RegExp]"; +} + +// return the actual prototype of JSZip +var out = { + /** + * @see loadAsync + */ + load: function() { + throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide."); + }, + + + /** + * Call a callback function for each entry at this folder level. + * @param {Function} cb the callback function: + * function (relativePath, file) {...} + * It takes 2 arguments : the relative path and the file. + */ + forEach: function(cb) { + var filename, relativePath, file; + /* jshint ignore:start */ + // ignore warning about unwanted properties because this.files is a null prototype object + for (filename in this.files) { + file = this.files[filename]; + relativePath = filename.slice(this.root.length, filename.length); + if (relativePath && filename.slice(0, this.root.length) === this.root) { // the file is in the current root + cb(relativePath, file); // TODO reverse the parameters ? need to be clean AND consistent with the filter search fn... + } + } + /* jshint ignore:end */ + }, + + /** + * Filter nested files/folders with the specified function. + * @param {Function} search the predicate to use : + * function (relativePath, file) {...} + * It takes 2 arguments : the relative path and the file. + * @return {Array} An array of matching elements. + */ + filter: function(search) { + var result = []; + this.forEach(function (relativePath, entry) { + if (search(relativePath, entry)) { // the file matches the function + result.push(entry); + } + + }); + return result; + }, + + /** + * Add a file to the zip file, or search a file. + * @param {string|RegExp} name The name of the file to add (if data is defined), + * the name of the file to find (if no data) or a regex to match files. + * @param {String|ArrayBuffer|Uint8Array|Buffer} data The file data, either raw or base64 encoded + * @param {Object} o File options + * @return {JSZip|Object|Array} this JSZip object (when adding a file), + * a file (when searching by string) or an array of files (when searching by regex). + */ + file: function(name, data, o) { + if (arguments.length === 1) { + if (isRegExp(name)) { + var regexp = name; + return this.filter(function(relativePath, file) { + return !file.dir && regexp.test(relativePath); + }); + } + else { // text + var obj = this.files[this.root + name]; + if (obj && !obj.dir) { + return obj; + } else { + return null; + } + } + } + else { // more than one argument : we have data ! + name = this.root + name; + fileAdd.call(this, name, data, o); + } + return this; + }, + + /** + * Add a directory to the zip file, or search. + * @param {String|RegExp} arg The name of the directory to add, or a regex to search folders. + * @return {JSZip} an object with the new directory as the root, or an array containing matching folders. + */ + folder: function(arg) { + if (!arg) { + return this; + } + + if (isRegExp(arg)) { + return this.filter(function(relativePath, file) { + return file.dir && arg.test(relativePath); + }); + } + + // else, name is a new folder + var name = this.root + arg; + var newFolder = folderAdd.call(this, name); + + // Allow chaining by returning a new object with this folder as the root + var ret = this.clone(); + ret.root = newFolder.name; + return ret; + }, + + /** + * Delete a file, or a directory and all sub-files, from the zip + * @param {string} name the name of the file to delete + * @return {JSZip} this JSZip object + */ + remove: function(name) { + name = this.root + name; + var file = this.files[name]; + if (!file) { + // Look for any folders + if (name.slice(-1) !== "/") { + name += "/"; + } + file = this.files[name]; + } + + if (file && !file.dir) { + // file + delete this.files[name]; + } else { + // maybe a folder, delete recursively + var kids = this.filter(function(relativePath, file) { + return file.name.slice(0, name.length) === name; + }); + for (var i = 0; i < kids.length; i++) { + delete this.files[kids[i].name]; + } + } + + return this; + }, + + /** + * Generate the complete zip file + * @param {Object} options the options to generate the zip file : + * - compression, "STORE" by default. + * - type, "base64" by default. Values are : string, base64, uint8array, arraybuffer, blob. + * @return {String|Uint8Array|ArrayBuffer|Buffer|Blob} the zip file + */ + generate: function(options) { + throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide."); + }, + + /** + * Generate the complete zip file as an internal stream. + * @param {Object} options the options to generate the zip file : + * - compression, "STORE" by default. + * - type, "base64" by default. Values are : string, base64, uint8array, arraybuffer, blob. + * @return {StreamHelper} the streamed zip file. + */ + generateInternalStream: function(options) { + var worker, opts = {}; + try { + opts = utils.extend(options || {}, { + streamFiles: false, + compression: "STORE", + compressionOptions : null, + type: "", + platform: "DOS", + comment: null, + mimeType: 'application/zip', + encodeFileName: utf8.utf8encode + }); + + opts.type = opts.type.toLowerCase(); + opts.compression = opts.compression.toUpperCase(); + + // "binarystring" is preferred but the internals use "string". + if(opts.type === "binarystring") { + opts.type = "string"; + } + + if (!opts.type) { + throw new Error("No output type specified."); + } + + utils.checkSupport(opts.type); + + // accept nodejs `process.platform` + if( + opts.platform === 'darwin' || + opts.platform === 'freebsd' || + opts.platform === 'linux' || + opts.platform === 'sunos' + ) { + opts.platform = "UNIX"; + } + if (opts.platform === 'win32') { + opts.platform = "DOS"; + } + + var comment = opts.comment || this.comment || ""; + worker = generate.generateWorker(this, opts, comment); + } catch (e) { + worker = new GenericWorker("error"); + worker.error(e); + } + return new StreamHelper(worker, opts.type || "string", opts.mimeType); + }, + /** + * Generate the complete zip file asynchronously. + * @see generateInternalStream + */ + generateAsync: function(options, onUpdate) { + return this.generateInternalStream(options).accumulate(onUpdate); + }, + /** + * Generate the complete zip file asynchronously. + * @see generateInternalStream + */ + generateNodeStream: function(options, onUpdate) { + options = options || {}; + if (!options.type) { + options.type = "nodebuffer"; + } + return this.generateInternalStream(options).toNodejsStream(onUpdate); + } +}; +module.exports = out; + +},{"./compressedObject":2,"./defaults":5,"./generate":9,"./nodejs/NodejsStreamInputAdapter":12,"./nodejsUtils":14,"./stream/GenericWorker":28,"./stream/StreamHelper":29,"./utf8":31,"./utils":32,"./zipObject":35}],16:[function(require,module,exports){ +/* + * This file is used by module bundlers (browserify/webpack/etc) when + * including a stream implementation. We use "readable-stream" to get a + * consistent behavior between nodejs versions but bundlers often have a shim + * for "stream". Using this shim greatly improve the compatibility and greatly + * reduce the final size of the bundle (only one stream implementation, not + * two). + */ +module.exports = require("stream"); + +},{"stream":undefined}],17:[function(require,module,exports){ +'use strict'; +var DataReader = require('./DataReader'); +var utils = require('../utils'); + +function ArrayReader(data) { + DataReader.call(this, data); + for(var i = 0; i < this.data.length; i++) { + data[i] = data[i] & 0xFF; + } +} +utils.inherits(ArrayReader, DataReader); +/** + * @see DataReader.byteAt + */ +ArrayReader.prototype.byteAt = function(i) { + return this.data[this.zero + i]; +}; +/** + * @see DataReader.lastIndexOfSignature + */ +ArrayReader.prototype.lastIndexOfSignature = function(sig) { + var sig0 = sig.charCodeAt(0), + sig1 = sig.charCodeAt(1), + sig2 = sig.charCodeAt(2), + sig3 = sig.charCodeAt(3); + for (var i = this.length - 4; i >= 0; --i) { + if (this.data[i] === sig0 && this.data[i + 1] === sig1 && this.data[i + 2] === sig2 && this.data[i + 3] === sig3) { + return i - this.zero; + } + } + + return -1; +}; +/** + * @see DataReader.readAndCheckSignature + */ +ArrayReader.prototype.readAndCheckSignature = function (sig) { + var sig0 = sig.charCodeAt(0), + sig1 = sig.charCodeAt(1), + sig2 = sig.charCodeAt(2), + sig3 = sig.charCodeAt(3), + data = this.readData(4); + return sig0 === data[0] && sig1 === data[1] && sig2 === data[2] && sig3 === data[3]; +}; +/** + * @see DataReader.readData + */ +ArrayReader.prototype.readData = function(size) { + this.checkOffset(size); + if(size === 0) { + return []; + } + var result = this.data.slice(this.zero + this.index, this.zero + this.index + size); + this.index += size; + return result; +}; +module.exports = ArrayReader; + +},{"../utils":32,"./DataReader":18}],18:[function(require,module,exports){ +'use strict'; +var utils = require('../utils'); + +function DataReader(data) { + this.data = data; // type : see implementation + this.length = data.length; + this.index = 0; + this.zero = 0; +} +DataReader.prototype = { + /** + * Check that the offset will not go too far. + * @param {string} offset the additional offset to check. + * @throws {Error} an Error if the offset is out of bounds. + */ + checkOffset: function(offset) { + this.checkIndex(this.index + offset); + }, + /** + * Check that the specified index will not be too far. + * @param {string} newIndex the index to check. + * @throws {Error} an Error if the index is out of bounds. + */ + checkIndex: function(newIndex) { + if (this.length < this.zero + newIndex || newIndex < 0) { + throw new Error("End of data reached (data length = " + this.length + ", asked index = " + (newIndex) + "). Corrupted zip ?"); + } + }, + /** + * Change the index. + * @param {number} newIndex The new index. + * @throws {Error} if the new index is out of the data. + */ + setIndex: function(newIndex) { + this.checkIndex(newIndex); + this.index = newIndex; + }, + /** + * Skip the next n bytes. + * @param {number} n the number of bytes to skip. + * @throws {Error} if the new index is out of the data. + */ + skip: function(n) { + this.setIndex(this.index + n); + }, + /** + * Get the byte at the specified index. + * @param {number} i the index to use. + * @return {number} a byte. + */ + byteAt: function(i) { + // see implementations + }, + /** + * Get the next number with a given byte size. + * @param {number} size the number of bytes to read. + * @return {number} the corresponding number. + */ + readInt: function(size) { + var result = 0, + i; + this.checkOffset(size); + for (i = this.index + size - 1; i >= this.index; i--) { + result = (result << 8) + this.byteAt(i); + } + this.index += size; + return result; + }, + /** + * Get the next string with a given byte size. + * @param {number} size the number of bytes to read. + * @return {string} the corresponding string. + */ + readString: function(size) { + return utils.transformTo("string", this.readData(size)); + }, + /** + * Get raw data without conversion, bytes. + * @param {number} size the number of bytes to read. + * @return {Object} the raw data, implementation specific. + */ + readData: function(size) { + // see implementations + }, + /** + * Find the last occurrence of a zip signature (4 bytes). + * @param {string} sig the signature to find. + * @return {number} the index of the last occurrence, -1 if not found. + */ + lastIndexOfSignature: function(sig) { + // see implementations + }, + /** + * Read the signature (4 bytes) at the current position and compare it with sig. + * @param {string} sig the expected signature + * @return {boolean} true if the signature matches, false otherwise. + */ + readAndCheckSignature: function(sig) { + // see implementations + }, + /** + * Get the next date. + * @return {Date} the date. + */ + readDate: function() { + var dostime = this.readInt(4); + return new Date(Date.UTC( + ((dostime >> 25) & 0x7f) + 1980, // year + ((dostime >> 21) & 0x0f) - 1, // month + (dostime >> 16) & 0x1f, // day + (dostime >> 11) & 0x1f, // hour + (dostime >> 5) & 0x3f, // minute + (dostime & 0x1f) << 1)); // second + } +}; +module.exports = DataReader; + +},{"../utils":32}],19:[function(require,module,exports){ +'use strict'; +var Uint8ArrayReader = require('./Uint8ArrayReader'); +var utils = require('../utils'); + +function NodeBufferReader(data) { + Uint8ArrayReader.call(this, data); +} +utils.inherits(NodeBufferReader, Uint8ArrayReader); + +/** + * @see DataReader.readData + */ +NodeBufferReader.prototype.readData = function(size) { + this.checkOffset(size); + var result = this.data.slice(this.zero + this.index, this.zero + this.index + size); + this.index += size; + return result; +}; +module.exports = NodeBufferReader; + +},{"../utils":32,"./Uint8ArrayReader":21}],20:[function(require,module,exports){ +'use strict'; +var DataReader = require('./DataReader'); +var utils = require('../utils'); + +function StringReader(data) { + DataReader.call(this, data); +} +utils.inherits(StringReader, DataReader); +/** + * @see DataReader.byteAt + */ +StringReader.prototype.byteAt = function(i) { + return this.data.charCodeAt(this.zero + i); +}; +/** + * @see DataReader.lastIndexOfSignature + */ +StringReader.prototype.lastIndexOfSignature = function(sig) { + return this.data.lastIndexOf(sig) - this.zero; +}; +/** + * @see DataReader.readAndCheckSignature + */ +StringReader.prototype.readAndCheckSignature = function (sig) { + var data = this.readData(4); + return sig === data; +}; +/** + * @see DataReader.readData + */ +StringReader.prototype.readData = function(size) { + this.checkOffset(size); + // this will work because the constructor applied the "& 0xff" mask. + var result = this.data.slice(this.zero + this.index, this.zero + this.index + size); + this.index += size; + return result; +}; +module.exports = StringReader; + +},{"../utils":32,"./DataReader":18}],21:[function(require,module,exports){ +'use strict'; +var ArrayReader = require('./ArrayReader'); +var utils = require('../utils'); + +function Uint8ArrayReader(data) { + ArrayReader.call(this, data); +} +utils.inherits(Uint8ArrayReader, ArrayReader); +/** + * @see DataReader.readData + */ +Uint8ArrayReader.prototype.readData = function(size) { + this.checkOffset(size); + if(size === 0) { + // in IE10, when using subarray(idx, idx), we get the array [0x00] instead of []. + return new Uint8Array(0); + } + var result = this.data.subarray(this.zero + this.index, this.zero + this.index + size); + this.index += size; + return result; +}; +module.exports = Uint8ArrayReader; + +},{"../utils":32,"./ArrayReader":17}],22:[function(require,module,exports){ +'use strict'; + +var utils = require('../utils'); +var support = require('../support'); +var ArrayReader = require('./ArrayReader'); +var StringReader = require('./StringReader'); +var NodeBufferReader = require('./NodeBufferReader'); +var Uint8ArrayReader = require('./Uint8ArrayReader'); + +/** + * Create a reader adapted to the data. + * @param {String|ArrayBuffer|Uint8Array|Buffer} data the data to read. + * @return {DataReader} the data reader. + */ +module.exports = function (data) { + var type = utils.getTypeOf(data); + utils.checkSupport(type); + if (type === "string" && !support.uint8array) { + return new StringReader(data); + } + if (type === "nodebuffer") { + return new NodeBufferReader(data); + } + if (support.uint8array) { + return new Uint8ArrayReader(utils.transformTo("uint8array", data)); + } + return new ArrayReader(utils.transformTo("array", data)); +}; + +},{"../support":30,"../utils":32,"./ArrayReader":17,"./NodeBufferReader":19,"./StringReader":20,"./Uint8ArrayReader":21}],23:[function(require,module,exports){ +'use strict'; +exports.LOCAL_FILE_HEADER = "PK\x03\x04"; +exports.CENTRAL_FILE_HEADER = "PK\x01\x02"; +exports.CENTRAL_DIRECTORY_END = "PK\x05\x06"; +exports.ZIP64_CENTRAL_DIRECTORY_LOCATOR = "PK\x06\x07"; +exports.ZIP64_CENTRAL_DIRECTORY_END = "PK\x06\x06"; +exports.DATA_DESCRIPTOR = "PK\x07\x08"; + +},{}],24:[function(require,module,exports){ +'use strict'; + +var GenericWorker = require('./GenericWorker'); +var utils = require('../utils'); + +/** + * A worker which convert chunks to a specified type. + * @constructor + * @param {String} destType the destination type. + */ +function ConvertWorker(destType) { + GenericWorker.call(this, "ConvertWorker to " + destType); + this.destType = destType; +} +utils.inherits(ConvertWorker, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +ConvertWorker.prototype.processChunk = function (chunk) { + this.push({ + data : utils.transformTo(this.destType, chunk.data), + meta : chunk.meta + }); +}; +module.exports = ConvertWorker; + +},{"../utils":32,"./GenericWorker":28}],25:[function(require,module,exports){ +'use strict'; + +var GenericWorker = require('./GenericWorker'); +var crc32 = require('../crc32'); +var utils = require('../utils'); + +/** + * A worker which calculate the crc32 of the data flowing through. + * @constructor + */ +function Crc32Probe() { + GenericWorker.call(this, "Crc32Probe"); + this.withStreamInfo("crc32", 0); +} +utils.inherits(Crc32Probe, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +Crc32Probe.prototype.processChunk = function (chunk) { + this.streamInfo.crc32 = crc32(chunk.data, this.streamInfo.crc32 || 0); + this.push(chunk); +}; +module.exports = Crc32Probe; + +},{"../crc32":4,"../utils":32,"./GenericWorker":28}],26:[function(require,module,exports){ +'use strict'; + +var utils = require('../utils'); +var GenericWorker = require('./GenericWorker'); + +/** + * A worker which calculate the total length of the data flowing through. + * @constructor + * @param {String} propName the name used to expose the length + */ +function DataLengthProbe(propName) { + GenericWorker.call(this, "DataLengthProbe for " + propName); + this.propName = propName; + this.withStreamInfo(propName, 0); +} +utils.inherits(DataLengthProbe, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +DataLengthProbe.prototype.processChunk = function (chunk) { + if(chunk) { + var length = this.streamInfo[this.propName] || 0; + this.streamInfo[this.propName] = length + chunk.data.length; + } + GenericWorker.prototype.processChunk.call(this, chunk); +}; +module.exports = DataLengthProbe; + + +},{"../utils":32,"./GenericWorker":28}],27:[function(require,module,exports){ +'use strict'; + +var utils = require('../utils'); +var GenericWorker = require('./GenericWorker'); + +// the size of the generated chunks +// TODO expose this as a public variable +var DEFAULT_BLOCK_SIZE = 16 * 1024; + +/** + * A worker that reads a content and emits chunks. + * @constructor + * @param {Promise} dataP the promise of the data to split + */ +function DataWorker(dataP) { + GenericWorker.call(this, "DataWorker"); + var self = this; + this.dataIsReady = false; + this.index = 0; + this.max = 0; + this.data = null; + this.type = ""; + + this._tickScheduled = false; + + dataP.then(function (data) { + self.dataIsReady = true; + self.data = data; + self.max = data && data.length || 0; + self.type = utils.getTypeOf(data); + if(!self.isPaused) { + self._tickAndRepeat(); + } + }, function (e) { + self.error(e); + }); +} + +utils.inherits(DataWorker, GenericWorker); + +/** + * @see GenericWorker.cleanUp + */ +DataWorker.prototype.cleanUp = function () { + GenericWorker.prototype.cleanUp.call(this); + this.data = null; +}; + +/** + * @see GenericWorker.resume + */ +DataWorker.prototype.resume = function () { + if(!GenericWorker.prototype.resume.call(this)) { + return false; + } + + if (!this._tickScheduled && this.dataIsReady) { + this._tickScheduled = true; + utils.delay(this._tickAndRepeat, [], this); + } + return true; +}; + +/** + * Trigger a tick a schedule an other call to this function. + */ +DataWorker.prototype._tickAndRepeat = function() { + this._tickScheduled = false; + if(this.isPaused || this.isFinished) { + return; + } + this._tick(); + if(!this.isFinished) { + utils.delay(this._tickAndRepeat, [], this); + this._tickScheduled = true; + } +}; + +/** + * Read and push a chunk. + */ +DataWorker.prototype._tick = function() { + + if(this.isPaused || this.isFinished) { + return false; + } + + var size = DEFAULT_BLOCK_SIZE; + var data = null, nextIndex = Math.min(this.max, this.index + size); + if (this.index >= this.max) { + // EOF + return this.end(); + } else { + switch(this.type) { + case "string": + data = this.data.substring(this.index, nextIndex); + break; + case "uint8array": + data = this.data.subarray(this.index, nextIndex); + break; + case "array": + case "nodebuffer": + data = this.data.slice(this.index, nextIndex); + break; + } + this.index = nextIndex; + return this.push({ + data : data, + meta : { + percent : this.max ? this.index / this.max * 100 : 0 + } + }); + } +}; + +module.exports = DataWorker; + +},{"../utils":32,"./GenericWorker":28}],28:[function(require,module,exports){ +'use strict'; + +/** + * A worker that does nothing but passing chunks to the next one. This is like + * a nodejs stream but with some differences. On the good side : + * - it works on IE 6-9 without any issue / polyfill + * - it weights less than the full dependencies bundled with browserify + * - it forwards errors (no need to declare an error handler EVERYWHERE) + * + * A chunk is an object with 2 attributes : `meta` and `data`. The former is an + * object containing anything (`percent` for example), see each worker for more + * details. The latter is the real data (String, Uint8Array, etc). + * + * @constructor + * @param {String} name the name of the stream (mainly used for debugging purposes) + */ +function GenericWorker(name) { + // the name of the worker + this.name = name || "default"; + // an object containing metadata about the workers chain + this.streamInfo = {}; + // an error which happened when the worker was paused + this.generatedError = null; + // an object containing metadata to be merged by this worker into the general metadata + this.extraStreamInfo = {}; + // true if the stream is paused (and should not do anything), false otherwise + this.isPaused = true; + // true if the stream is finished (and should not do anything), false otherwise + this.isFinished = false; + // true if the stream is locked to prevent further structure updates (pipe), false otherwise + this.isLocked = false; + // the event listeners + this._listeners = { + 'data':[], + 'end':[], + 'error':[] + }; + // the previous worker, if any + this.previous = null; +} + +GenericWorker.prototype = { + /** + * Push a chunk to the next workers. + * @param {Object} chunk the chunk to push + */ + push : function (chunk) { + this.emit("data", chunk); + }, + /** + * End the stream. + * @return {Boolean} true if this call ended the worker, false otherwise. + */ + end : function () { + if (this.isFinished) { + return false; + } + + this.flush(); + try { + this.emit("end"); + this.cleanUp(); + this.isFinished = true; + } catch (e) { + this.emit("error", e); + } + return true; + }, + /** + * End the stream with an error. + * @param {Error} e the error which caused the premature end. + * @return {Boolean} true if this call ended the worker with an error, false otherwise. + */ + error : function (e) { + if (this.isFinished) { + return false; + } + + if(this.isPaused) { + this.generatedError = e; + } else { + this.isFinished = true; + + this.emit("error", e); + + // in the workers chain exploded in the middle of the chain, + // the error event will go downward but we also need to notify + // workers upward that there has been an error. + if(this.previous) { + this.previous.error(e); + } + + this.cleanUp(); + } + return true; + }, + /** + * Add a callback on an event. + * @param {String} name the name of the event (data, end, error) + * @param {Function} listener the function to call when the event is triggered + * @return {GenericWorker} the current object for chainability + */ + on : function (name, listener) { + this._listeners[name].push(listener); + return this; + }, + /** + * Clean any references when a worker is ending. + */ + cleanUp : function () { + this.streamInfo = this.generatedError = this.extraStreamInfo = null; + this._listeners = []; + }, + /** + * Trigger an event. This will call registered callback with the provided arg. + * @param {String} name the name of the event (data, end, error) + * @param {Object} arg the argument to call the callback with. + */ + emit : function (name, arg) { + if (this._listeners[name]) { + for(var i = 0; i < this._listeners[name].length; i++) { + this._listeners[name][i].call(this, arg); + } + } + }, + /** + * Chain a worker with an other. + * @param {Worker} next the worker receiving events from the current one. + * @return {worker} the next worker for chainability + */ + pipe : function (next) { + return next.registerPrevious(this); + }, + /** + * Same as `pipe` in the other direction. + * Using an API with `pipe(next)` is very easy. + * Implementing the API with the point of view of the next one registering + * a source is easier, see the ZipFileWorker. + * @param {Worker} previous the previous worker, sending events to this one + * @return {Worker} the current worker for chainability + */ + registerPrevious : function (previous) { + if (this.isLocked) { + throw new Error("The stream '" + this + "' has already been used."); + } + + // sharing the streamInfo... + this.streamInfo = previous.streamInfo; + // ... and adding our own bits + this.mergeStreamInfo(); + this.previous = previous; + var self = this; + previous.on('data', function (chunk) { + self.processChunk(chunk); + }); + previous.on('end', function () { + self.end(); + }); + previous.on('error', function (e) { + self.error(e); + }); + return this; + }, + /** + * Pause the stream so it doesn't send events anymore. + * @return {Boolean} true if this call paused the worker, false otherwise. + */ + pause : function () { + if(this.isPaused || this.isFinished) { + return false; + } + this.isPaused = true; + + if(this.previous) { + this.previous.pause(); + } + return true; + }, + /** + * Resume a paused stream. + * @return {Boolean} true if this call resumed the worker, false otherwise. + */ + resume : function () { + if(!this.isPaused || this.isFinished) { + return false; + } + this.isPaused = false; + + // if true, the worker tried to resume but failed + var withError = false; + if(this.generatedError) { + this.error(this.generatedError); + withError = true; + } + if(this.previous) { + this.previous.resume(); + } + + return !withError; + }, + /** + * Flush any remaining bytes as the stream is ending. + */ + flush : function () {}, + /** + * Process a chunk. This is usually the method overridden. + * @param {Object} chunk the chunk to process. + */ + processChunk : function(chunk) { + this.push(chunk); + }, + /** + * Add a key/value to be added in the workers chain streamInfo once activated. + * @param {String} key the key to use + * @param {Object} value the associated value + * @return {Worker} the current worker for chainability + */ + withStreamInfo : function (key, value) { + this.extraStreamInfo[key] = value; + this.mergeStreamInfo(); + return this; + }, + /** + * Merge this worker's streamInfo into the chain's streamInfo. + */ + mergeStreamInfo : function () { + for(var key in this.extraStreamInfo) { + if (!this.extraStreamInfo.hasOwnProperty(key)) { + continue; + } + this.streamInfo[key] = this.extraStreamInfo[key]; + } + }, + + /** + * Lock the stream to prevent further updates on the workers chain. + * After calling this method, all calls to pipe will fail. + */ + lock: function () { + if (this.isLocked) { + throw new Error("The stream '" + this + "' has already been used."); + } + this.isLocked = true; + if (this.previous) { + this.previous.lock(); + } + }, + + /** + * + * Pretty print the workers chain. + */ + toString : function () { + var me = "Worker " + this.name; + if (this.previous) { + return this.previous + " -> " + me; + } else { + return me; + } + } +}; + +module.exports = GenericWorker; + +},{}],29:[function(require,module,exports){ +'use strict'; + +var utils = require('../utils'); +var ConvertWorker = require('./ConvertWorker'); +var GenericWorker = require('./GenericWorker'); +var base64 = require('../base64'); +var support = require("../support"); +var external = require("../external"); + +var NodejsStreamOutputAdapter = null; +if (support.nodestream) { + try { + NodejsStreamOutputAdapter = require('../nodejs/NodejsStreamOutputAdapter'); + } catch(e) {} +} + +/** + * Apply the final transformation of the data. If the user wants a Blob for + * example, it's easier to work with an U8intArray and finally do the + * ArrayBuffer/Blob conversion. + * @param {String} type the name of the final type + * @param {String|Uint8Array|Buffer} content the content to transform + * @param {String} mimeType the mime type of the content, if applicable. + * @return {String|Uint8Array|ArrayBuffer|Buffer|Blob} the content in the right format. + */ +function transformZipOutput(type, content, mimeType) { + switch(type) { + case "blob" : + return utils.newBlob(utils.transformTo("arraybuffer", content), mimeType); + case "base64" : + return base64.encode(content); + default : + return utils.transformTo(type, content); + } +} + +/** + * Concatenate an array of data of the given type. + * @param {String} type the type of the data in the given array. + * @param {Array} dataArray the array containing the data chunks to concatenate + * @return {String|Uint8Array|Buffer} the concatenated data + * @throws Error if the asked type is unsupported + */ +function concat (type, dataArray) { + var i, index = 0, res = null, totalLength = 0; + for(i = 0; i < dataArray.length; i++) { + totalLength += dataArray[i].length; + } + switch(type) { + case "string": + return dataArray.join(""); + case "array": + return Array.prototype.concat.apply([], dataArray); + case "uint8array": + res = new Uint8Array(totalLength); + for(i = 0; i < dataArray.length; i++) { + res.set(dataArray[i], index); + index += dataArray[i].length; + } + return res; + case "nodebuffer": + return Buffer.concat(dataArray); + default: + throw new Error("concat : unsupported type '" + type + "'"); + } +} + +/** + * Listen a StreamHelper, accumulate its content and concatenate it into a + * complete block. + * @param {StreamHelper} helper the helper to use. + * @param {Function} updateCallback a callback called on each update. Called + * with one arg : + * - the metadata linked to the update received. + * @return Promise the promise for the accumulation. + */ +function accumulate(helper, updateCallback) { + return new external.Promise(function (resolve, reject){ + var dataArray = []; + var chunkType = helper._internalType, + resultType = helper._outputType, + mimeType = helper._mimeType; + helper + .on('data', function (data, meta) { + dataArray.push(data); + if(updateCallback) { + updateCallback(meta); + } + }) + .on('error', function(err) { + dataArray = []; + reject(err); + }) + .on('end', function (){ + try { + var result = transformZipOutput(resultType, concat(chunkType, dataArray), mimeType); + resolve(result); + } catch (e) { + reject(e); + } + dataArray = []; + }) + .resume(); + }); +} + +/** + * An helper to easily use workers outside of JSZip. + * @constructor + * @param {Worker} worker the worker to wrap + * @param {String} outputType the type of data expected by the use + * @param {String} mimeType the mime type of the content, if applicable. + */ +function StreamHelper(worker, outputType, mimeType) { + var internalType = outputType; + switch(outputType) { + case "blob": + case "arraybuffer": + internalType = "uint8array"; + break; + case "base64": + internalType = "string"; + break; + } + + try { + // the type used internally + this._internalType = internalType; + // the type used to output results + this._outputType = outputType; + // the mime type + this._mimeType = mimeType; + utils.checkSupport(internalType); + this._worker = worker.pipe(new ConvertWorker(internalType)); + // the last workers can be rewired without issues but we need to + // prevent any updates on previous workers. + worker.lock(); + } catch(e) { + this._worker = new GenericWorker("error"); + this._worker.error(e); + } +} + +StreamHelper.prototype = { + /** + * Listen a StreamHelper, accumulate its content and concatenate it into a + * complete block. + * @param {Function} updateCb the update callback. + * @return Promise the promise for the accumulation. + */ + accumulate : function (updateCb) { + return accumulate(this, updateCb); + }, + /** + * Add a listener on an event triggered on a stream. + * @param {String} evt the name of the event + * @param {Function} fn the listener + * @return {StreamHelper} the current helper. + */ + on : function (evt, fn) { + var self = this; + + if(evt === "data") { + this._worker.on(evt, function (chunk) { + fn.call(self, chunk.data, chunk.meta); + }); + } else { + this._worker.on(evt, function () { + utils.delay(fn, arguments, self); + }); + } + return this; + }, + /** + * Resume the flow of chunks. + * @return {StreamHelper} the current helper. + */ + resume : function () { + utils.delay(this._worker.resume, [], this._worker); + return this; + }, + /** + * Pause the flow of chunks. + * @return {StreamHelper} the current helper. + */ + pause : function () { + this._worker.pause(); + return this; + }, + /** + * Return a nodejs stream for this helper. + * @param {Function} updateCb the update callback. + * @return {NodejsStreamOutputAdapter} the nodejs stream. + */ + toNodejsStream : function (updateCb) { + utils.checkSupport("nodestream"); + if (this._outputType !== "nodebuffer") { + // an object stream containing blob/arraybuffer/uint8array/string + // is strange and I don't know if it would be useful. + // I you find this comment and have a good usecase, please open a + // bug report ! + throw new Error(this._outputType + " is not supported by this method"); + } + + return new NodejsStreamOutputAdapter(this, { + objectMode : this._outputType !== "nodebuffer" + }, updateCb); + } +}; + + +module.exports = StreamHelper; + +},{"../base64":1,"../external":6,"../nodejs/NodejsStreamOutputAdapter":13,"../support":30,"../utils":32,"./ConvertWorker":24,"./GenericWorker":28}],30:[function(require,module,exports){ +'use strict'; + +exports.base64 = true; +exports.array = true; +exports.string = true; +exports.arraybuffer = typeof ArrayBuffer !== "undefined" && typeof Uint8Array !== "undefined"; +exports.nodebuffer = typeof Buffer !== "undefined"; +// contains true if JSZip can read/generate Uint8Array, false otherwise. +exports.uint8array = typeof Uint8Array !== "undefined"; + +if (typeof ArrayBuffer === "undefined") { + exports.blob = false; +} +else { + var buffer = new ArrayBuffer(0); + try { + exports.blob = new Blob([buffer], { + type: "application/zip" + }).size === 0; + } + catch (e) { + try { + var Builder = self.BlobBuilder || self.WebKitBlobBuilder || self.MozBlobBuilder || self.MSBlobBuilder; + var builder = new Builder(); + builder.append(buffer); + exports.blob = builder.getBlob('application/zip').size === 0; + } + catch (e) { + exports.blob = false; + } + } +} + +try { + exports.nodestream = !!require('readable-stream').Readable; +} catch(e) { + exports.nodestream = false; +} + +},{"readable-stream":16}],31:[function(require,module,exports){ +'use strict'; + +var utils = require('./utils'); +var support = require('./support'); +var nodejsUtils = require('./nodejsUtils'); +var GenericWorker = require('./stream/GenericWorker'); + +/** + * The following functions come from pako, from pako/lib/utils/strings + * released under the MIT license, see pako https://github.com/nodeca/pako/ + */ + +// Table with utf8 lengths (calculated by first byte of sequence) +// Note, that 5 & 6-byte values and some 4-byte values can not be represented in JS, +// because max possible codepoint is 0x10ffff +var _utf8len = new Array(256); +for (var i=0; i<256; i++) { + _utf8len[i] = (i >= 252 ? 6 : i >= 248 ? 5 : i >= 240 ? 4 : i >= 224 ? 3 : i >= 192 ? 2 : 1); +} +_utf8len[254]=_utf8len[254]=1; // Invalid sequence start + +// convert string to array (typed, when possible) +var string2buf = function (str) { + var buf, c, c2, m_pos, i, str_len = str.length, buf_len = 0; + + // count binary size + for (m_pos = 0; m_pos < str_len; m_pos++) { + c = str.charCodeAt(m_pos); + if ((c & 0xfc00) === 0xd800 && (m_pos+1 < str_len)) { + c2 = str.charCodeAt(m_pos+1); + if ((c2 & 0xfc00) === 0xdc00) { + c = 0x10000 + ((c - 0xd800) << 10) + (c2 - 0xdc00); + m_pos++; + } + } + buf_len += c < 0x80 ? 1 : c < 0x800 ? 2 : c < 0x10000 ? 3 : 4; + } + + // allocate buffer + if (support.uint8array) { + buf = new Uint8Array(buf_len); + } else { + buf = new Array(buf_len); + } + + // convert + for (i=0, m_pos = 0; i < buf_len; m_pos++) { + c = str.charCodeAt(m_pos); + if ((c & 0xfc00) === 0xd800 && (m_pos+1 < str_len)) { + c2 = str.charCodeAt(m_pos+1); + if ((c2 & 0xfc00) === 0xdc00) { + c = 0x10000 + ((c - 0xd800) << 10) + (c2 - 0xdc00); + m_pos++; + } + } + if (c < 0x80) { + /* one byte */ + buf[i++] = c; + } else if (c < 0x800) { + /* two bytes */ + buf[i++] = 0xC0 | (c >>> 6); + buf[i++] = 0x80 | (c & 0x3f); + } else if (c < 0x10000) { + /* three bytes */ + buf[i++] = 0xE0 | (c >>> 12); + buf[i++] = 0x80 | (c >>> 6 & 0x3f); + buf[i++] = 0x80 | (c & 0x3f); + } else { + /* four bytes */ + buf[i++] = 0xf0 | (c >>> 18); + buf[i++] = 0x80 | (c >>> 12 & 0x3f); + buf[i++] = 0x80 | (c >>> 6 & 0x3f); + buf[i++] = 0x80 | (c & 0x3f); + } + } + + return buf; +}; + +// Calculate max possible position in utf8 buffer, +// that will not break sequence. If that's not possible +// - (very small limits) return max size as is. +// +// buf[] - utf8 bytes array +// max - length limit (mandatory); +var utf8border = function(buf, max) { + var pos; + + max = max || buf.length; + if (max > buf.length) { max = buf.length; } + + // go back from last position, until start of sequence found + pos = max-1; + while (pos >= 0 && (buf[pos] & 0xC0) === 0x80) { pos--; } + + // Fuckup - very small and broken sequence, + // return max, because we should return something anyway. + if (pos < 0) { return max; } + + // If we came to start of buffer - that means vuffer is too small, + // return max too. + if (pos === 0) { return max; } + + return (pos + _utf8len[buf[pos]] > max) ? pos : max; +}; + +// convert array to string +var buf2string = function (buf) { + var str, i, out, c, c_len; + var len = buf.length; + + // Reserve max possible length (2 words per char) + // NB: by unknown reasons, Array is significantly faster for + // String.fromCharCode.apply than Uint16Array. + var utf16buf = new Array(len*2); + + for (out=0, i=0; i 4) { utf16buf[out++] = 0xfffd; i += c_len-1; continue; } + + // apply mask on first byte + c &= c_len === 2 ? 0x1f : c_len === 3 ? 0x0f : 0x07; + // join the rest + while (c_len > 1 && i < len) { + c = (c << 6) | (buf[i++] & 0x3f); + c_len--; + } + + // terminated by end of string? + if (c_len > 1) { utf16buf[out++] = 0xfffd; continue; } + + if (c < 0x10000) { + utf16buf[out++] = c; + } else { + c -= 0x10000; + utf16buf[out++] = 0xd800 | ((c >> 10) & 0x3ff); + utf16buf[out++] = 0xdc00 | (c & 0x3ff); + } + } + + // shrinkBuf(utf16buf, out) + if (utf16buf.length !== out) { + if(utf16buf.subarray) { + utf16buf = utf16buf.subarray(0, out); + } else { + utf16buf.length = out; + } + } + + // return String.fromCharCode.apply(null, utf16buf); + return utils.applyFromCharCode(utf16buf); +}; + + +// That's all for the pako functions. + + +/** + * Transform a javascript string into an array (typed if possible) of bytes, + * UTF-8 encoded. + * @param {String} str the string to encode + * @return {Array|Uint8Array|Buffer} the UTF-8 encoded string. + */ +exports.utf8encode = function utf8encode(str) { + if (support.nodebuffer) { + return nodejsUtils.newBufferFrom(str, "utf-8"); + } + + return string2buf(str); +}; + + +/** + * Transform a bytes array (or a representation) representing an UTF-8 encoded + * string into a javascript string. + * @param {Array|Uint8Array|Buffer} buf the data de decode + * @return {String} the decoded string. + */ +exports.utf8decode = function utf8decode(buf) { + if (support.nodebuffer) { + return utils.transformTo("nodebuffer", buf).toString("utf-8"); + } + + buf = utils.transformTo(support.uint8array ? "uint8array" : "array", buf); + + return buf2string(buf); +}; + +/** + * A worker to decode utf8 encoded binary chunks into string chunks. + * @constructor + */ +function Utf8DecodeWorker() { + GenericWorker.call(this, "utf-8 decode"); + // the last bytes if a chunk didn't end with a complete codepoint. + this.leftOver = null; +} +utils.inherits(Utf8DecodeWorker, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +Utf8DecodeWorker.prototype.processChunk = function (chunk) { + + var data = utils.transformTo(support.uint8array ? "uint8array" : "array", chunk.data); + + // 1st step, re-use what's left of the previous chunk + if (this.leftOver && this.leftOver.length) { + if(support.uint8array) { + var previousData = data; + data = new Uint8Array(previousData.length + this.leftOver.length); + data.set(this.leftOver, 0); + data.set(previousData, this.leftOver.length); + } else { + data = this.leftOver.concat(data); + } + this.leftOver = null; + } + + var nextBoundary = utf8border(data); + var usableData = data; + if (nextBoundary !== data.length) { + if (support.uint8array) { + usableData = data.subarray(0, nextBoundary); + this.leftOver = data.subarray(nextBoundary, data.length); + } else { + usableData = data.slice(0, nextBoundary); + this.leftOver = data.slice(nextBoundary, data.length); + } + } + + this.push({ + data : exports.utf8decode(usableData), + meta : chunk.meta + }); +}; + +/** + * @see GenericWorker.flush + */ +Utf8DecodeWorker.prototype.flush = function () { + if(this.leftOver && this.leftOver.length) { + this.push({ + data : exports.utf8decode(this.leftOver), + meta : {} + }); + this.leftOver = null; + } +}; +exports.Utf8DecodeWorker = Utf8DecodeWorker; + +/** + * A worker to endcode string chunks into utf8 encoded binary chunks. + * @constructor + */ +function Utf8EncodeWorker() { + GenericWorker.call(this, "utf-8 encode"); +} +utils.inherits(Utf8EncodeWorker, GenericWorker); + +/** + * @see GenericWorker.processChunk + */ +Utf8EncodeWorker.prototype.processChunk = function (chunk) { + this.push({ + data : exports.utf8encode(chunk.data), + meta : chunk.meta + }); +}; +exports.Utf8EncodeWorker = Utf8EncodeWorker; + +},{"./nodejsUtils":14,"./stream/GenericWorker":28,"./support":30,"./utils":32}],32:[function(require,module,exports){ +'use strict'; + +var support = require('./support'); +var base64 = require('./base64'); +var nodejsUtils = require('./nodejsUtils'); +var setImmediate = require('set-immediate-shim'); +var external = require("./external"); + + +/** + * Convert a string that pass as a "binary string": it should represent a byte + * array but may have > 255 char codes. Be sure to take only the first byte + * and returns the byte array. + * @param {String} str the string to transform. + * @return {Array|Uint8Array} the string in a binary format. + */ +function string2binary(str) { + var result = null; + if (support.uint8array) { + result = new Uint8Array(str.length); + } else { + result = new Array(str.length); + } + return stringToArrayLike(str, result); +} + +/** + * Create a new blob with the given content and the given type. + * @param {String|ArrayBuffer} part the content to put in the blob. DO NOT use + * an Uint8Array because the stock browser of android 4 won't accept it (it + * will be silently converted to a string, "[object Uint8Array]"). + * + * Use only ONE part to build the blob to avoid a memory leak in IE11 / Edge: + * when a large amount of Array is used to create the Blob, the amount of + * memory consumed is nearly 100 times the original data amount. + * + * @param {String} type the mime type of the blob. + * @return {Blob} the created blob. + */ +exports.newBlob = function(part, type) { + exports.checkSupport("blob"); + + try { + // Blob constructor + return new Blob([part], { + type: type + }); + } + catch (e) { + + try { + // deprecated, browser only, old way + var Builder = self.BlobBuilder || self.WebKitBlobBuilder || self.MozBlobBuilder || self.MSBlobBuilder; + var builder = new Builder(); + builder.append(part); + return builder.getBlob(type); + } + catch (e) { + + // well, fuck ?! + throw new Error("Bug : can't construct the Blob."); + } + } + + +}; +/** + * The identity function. + * @param {Object} input the input. + * @return {Object} the same input. + */ +function identity(input) { + return input; +} + +/** + * Fill in an array with a string. + * @param {String} str the string to use. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} array the array to fill in (will be mutated). + * @return {Array|ArrayBuffer|Uint8Array|Buffer} the updated array. + */ +function stringToArrayLike(str, array) { + for (var i = 0; i < str.length; ++i) { + array[i] = str.charCodeAt(i) & 0xFF; + } + return array; +} + +/** + * An helper for the function arrayLikeToString. + * This contains static information and functions that + * can be optimized by the browser JIT compiler. + */ +var arrayToStringHelper = { + /** + * Transform an array of int into a string, chunk by chunk. + * See the performances notes on arrayLikeToString. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} array the array to transform. + * @param {String} type the type of the array. + * @param {Integer} chunk the chunk size. + * @return {String} the resulting string. + * @throws Error if the chunk is too big for the stack. + */ + stringifyByChunk: function(array, type, chunk) { + var result = [], k = 0, len = array.length; + // shortcut + if (len <= chunk) { + return String.fromCharCode.apply(null, array); + } + while (k < len) { + if (type === "array" || type === "nodebuffer") { + result.push(String.fromCharCode.apply(null, array.slice(k, Math.min(k + chunk, len)))); + } + else { + result.push(String.fromCharCode.apply(null, array.subarray(k, Math.min(k + chunk, len)))); + } + k += chunk; + } + return result.join(""); + }, + /** + * Call String.fromCharCode on every item in the array. + * This is the naive implementation, which generate A LOT of intermediate string. + * This should be used when everything else fail. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} array the array to transform. + * @return {String} the result. + */ + stringifyByChar: function(array){ + var resultStr = ""; + for(var i = 0; i < array.length; i++) { + resultStr += String.fromCharCode(array[i]); + } + return resultStr; + }, + applyCanBeUsed : { + /** + * true if the browser accepts to use String.fromCharCode on Uint8Array + */ + uint8array : (function () { + try { + return support.uint8array && String.fromCharCode.apply(null, new Uint8Array(1)).length === 1; + } catch (e) { + return false; + } + })(), + /** + * true if the browser accepts to use String.fromCharCode on nodejs Buffer. + */ + nodebuffer : (function () { + try { + return support.nodebuffer && String.fromCharCode.apply(null, nodejsUtils.allocBuffer(1)).length === 1; + } catch (e) { + return false; + } + })() + } +}; + +/** + * Transform an array-like object to a string. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} array the array to transform. + * @return {String} the result. + */ +function arrayLikeToString(array) { + // Performances notes : + // -------------------- + // String.fromCharCode.apply(null, array) is the fastest, see + // see http://jsperf.com/converting-a-uint8array-to-a-string/2 + // but the stack is limited (and we can get huge arrays !). + // + // result += String.fromCharCode(array[i]); generate too many strings ! + // + // This code is inspired by http://jsperf.com/arraybuffer-to-string-apply-performance/2 + // TODO : we now have workers that split the work. Do we still need that ? + var chunk = 65536, + type = exports.getTypeOf(array), + canUseApply = true; + if (type === "uint8array") { + canUseApply = arrayToStringHelper.applyCanBeUsed.uint8array; + } else if (type === "nodebuffer") { + canUseApply = arrayToStringHelper.applyCanBeUsed.nodebuffer; + } + + if (canUseApply) { + while (chunk > 1) { + try { + return arrayToStringHelper.stringifyByChunk(array, type, chunk); + } catch (e) { + chunk = Math.floor(chunk / 2); + } + } + } + + // no apply or chunk error : slow and painful algorithm + // default browser on android 4.* + return arrayToStringHelper.stringifyByChar(array); +} + +exports.applyFromCharCode = arrayLikeToString; + + +/** + * Copy the data from an array-like to an other array-like. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} arrayFrom the origin array. + * @param {Array|ArrayBuffer|Uint8Array|Buffer} arrayTo the destination array which will be mutated. + * @return {Array|ArrayBuffer|Uint8Array|Buffer} the updated destination array. + */ +function arrayLikeToArrayLike(arrayFrom, arrayTo) { + for (var i = 0; i < arrayFrom.length; i++) { + arrayTo[i] = arrayFrom[i]; + } + return arrayTo; +} + +// a matrix containing functions to transform everything into everything. +var transform = {}; + +// string to ? +transform["string"] = { + "string": identity, + "array": function(input) { + return stringToArrayLike(input, new Array(input.length)); + }, + "arraybuffer": function(input) { + return transform["string"]["uint8array"](input).buffer; + }, + "uint8array": function(input) { + return stringToArrayLike(input, new Uint8Array(input.length)); + }, + "nodebuffer": function(input) { + return stringToArrayLike(input, nodejsUtils.allocBuffer(input.length)); + } +}; + +// array to ? +transform["array"] = { + "string": arrayLikeToString, + "array": identity, + "arraybuffer": function(input) { + return (new Uint8Array(input)).buffer; + }, + "uint8array": function(input) { + return new Uint8Array(input); + }, + "nodebuffer": function(input) { + return nodejsUtils.newBufferFrom(input); + } +}; + +// arraybuffer to ? +transform["arraybuffer"] = { + "string": function(input) { + return arrayLikeToString(new Uint8Array(input)); + }, + "array": function(input) { + return arrayLikeToArrayLike(new Uint8Array(input), new Array(input.byteLength)); + }, + "arraybuffer": identity, + "uint8array": function(input) { + return new Uint8Array(input); + }, + "nodebuffer": function(input) { + return nodejsUtils.newBufferFrom(new Uint8Array(input)); + } +}; + +// uint8array to ? +transform["uint8array"] = { + "string": arrayLikeToString, + "array": function(input) { + return arrayLikeToArrayLike(input, new Array(input.length)); + }, + "arraybuffer": function(input) { + return input.buffer; + }, + "uint8array": identity, + "nodebuffer": function(input) { + return nodejsUtils.newBufferFrom(input); + } +}; + +// nodebuffer to ? +transform["nodebuffer"] = { + "string": arrayLikeToString, + "array": function(input) { + return arrayLikeToArrayLike(input, new Array(input.length)); + }, + "arraybuffer": function(input) { + return transform["nodebuffer"]["uint8array"](input).buffer; + }, + "uint8array": function(input) { + return arrayLikeToArrayLike(input, new Uint8Array(input.length)); + }, + "nodebuffer": identity +}; + +/** + * Transform an input into any type. + * The supported output type are : string, array, uint8array, arraybuffer, nodebuffer. + * If no output type is specified, the unmodified input will be returned. + * @param {String} outputType the output type. + * @param {String|Array|ArrayBuffer|Uint8Array|Buffer} input the input to convert. + * @throws {Error} an Error if the browser doesn't support the requested output type. + */ +exports.transformTo = function(outputType, input) { + if (!input) { + // undefined, null, etc + // an empty string won't harm. + input = ""; + } + if (!outputType) { + return input; + } + exports.checkSupport(outputType); + var inputType = exports.getTypeOf(input); + var result = transform[inputType][outputType](input); + return result; +}; + +/** + * Return the type of the input. + * The type will be in a format valid for JSZip.utils.transformTo : string, array, uint8array, arraybuffer. + * @param {Object} input the input to identify. + * @return {String} the (lowercase) type of the input. + */ +exports.getTypeOf = function(input) { + if (typeof input === "string") { + return "string"; + } + if (Object.prototype.toString.call(input) === "[object Array]") { + return "array"; + } + if (support.nodebuffer && nodejsUtils.isBuffer(input)) { + return "nodebuffer"; + } + if (support.uint8array && input instanceof Uint8Array) { + return "uint8array"; + } + if (support.arraybuffer && input instanceof ArrayBuffer) { + return "arraybuffer"; + } +}; + +/** + * Throw an exception if the type is not supported. + * @param {String} type the type to check. + * @throws {Error} an Error if the browser doesn't support the requested type. + */ +exports.checkSupport = function(type) { + var supported = support[type.toLowerCase()]; + if (!supported) { + throw new Error(type + " is not supported by this platform"); + } +}; + +exports.MAX_VALUE_16BITS = 65535; +exports.MAX_VALUE_32BITS = -1; // well, "\xFF\xFF\xFF\xFF\xFF\xFF\xFF\xFF" is parsed as -1 + +/** + * Prettify a string read as binary. + * @param {string} str the string to prettify. + * @return {string} a pretty string. + */ +exports.pretty = function(str) { + var res = '', + code, i; + for (i = 0; i < (str || "").length; i++) { + code = str.charCodeAt(i); + res += '\\x' + (code < 16 ? "0" : "") + code.toString(16).toUpperCase(); + } + return res; +}; + +/** + * Defer the call of a function. + * @param {Function} callback the function to call asynchronously. + * @param {Array} args the arguments to give to the callback. + */ +exports.delay = function(callback, args, self) { + setImmediate(function () { + callback.apply(self || null, args || []); + }); +}; + +/** + * Extends a prototype with an other, without calling a constructor with + * side effects. Inspired by nodejs' `utils.inherits` + * @param {Function} ctor the constructor to augment + * @param {Function} superCtor the parent constructor to use + */ +exports.inherits = function (ctor, superCtor) { + var Obj = function() {}; + Obj.prototype = superCtor.prototype; + ctor.prototype = new Obj(); +}; + +/** + * Merge the objects passed as parameters into a new one. + * @private + * @param {...Object} var_args All objects to merge. + * @return {Object} a new object with the data of the others. + */ +exports.extend = function() { + var result = {}, i, attr; + for (i = 0; i < arguments.length; i++) { // arguments is not enumerable in some browsers + for (attr in arguments[i]) { + if (arguments[i].hasOwnProperty(attr) && typeof result[attr] === "undefined") { + result[attr] = arguments[i][attr]; + } + } + } + return result; +}; + +/** + * Transform arbitrary content into a Promise. + * @param {String} name a name for the content being processed. + * @param {Object} inputData the content to process. + * @param {Boolean} isBinary true if the content is not an unicode string + * @param {Boolean} isOptimizedBinaryString true if the string content only has one byte per character. + * @param {Boolean} isBase64 true if the string content is encoded with base64. + * @return {Promise} a promise in a format usable by JSZip. + */ +exports.prepareContent = function(name, inputData, isBinary, isOptimizedBinaryString, isBase64) { + + // if inputData is already a promise, this flatten it. + var promise = external.Promise.resolve(inputData).then(function(data) { + + + var isBlob = support.blob && (data instanceof Blob || ['[object File]', '[object Blob]'].indexOf(Object.prototype.toString.call(data)) !== -1); + + if (isBlob && typeof FileReader !== "undefined") { + return new external.Promise(function (resolve, reject) { + var reader = new FileReader(); + + reader.onload = function(e) { + resolve(e.target.result); + }; + reader.onerror = function(e) { + reject(e.target.error); + }; + reader.readAsArrayBuffer(data); + }); + } else { + return data; + } + }); + + return promise.then(function(data) { + var dataType = exports.getTypeOf(data); + + if (!dataType) { + return external.Promise.reject( + new Error("Can't read the data of '" + name + "'. Is it " + + "in a supported JavaScript type (String, Blob, ArrayBuffer, etc) ?") + ); + } + // special case : it's way easier to work with Uint8Array than with ArrayBuffer + if (dataType === "arraybuffer") { + data = exports.transformTo("uint8array", data); + } else if (dataType === "string") { + if (isBase64) { + data = base64.decode(data); + } + else if (isBinary) { + // optimizedBinaryString === true means that the file has already been filtered with a 0xFF mask + if (isOptimizedBinaryString !== true) { + // this is a string, not in a base64 format. + // Be sure that this is a correct "binary string" + data = string2binary(data); + } + } + } + return data; + }); +}; + +},{"./base64":1,"./external":6,"./nodejsUtils":14,"./support":30,"set-immediate-shim":54}],33:[function(require,module,exports){ +'use strict'; +var readerFor = require('./reader/readerFor'); +var utils = require('./utils'); +var sig = require('./signature'); +var ZipEntry = require('./zipEntry'); +var utf8 = require('./utf8'); +var support = require('./support'); +// class ZipEntries {{{ +/** + * All the entries in the zip file. + * @constructor + * @param {Object} loadOptions Options for loading the stream. + */ +function ZipEntries(loadOptions) { + this.files = []; + this.loadOptions = loadOptions; +} +ZipEntries.prototype = { + /** + * Check that the reader is on the specified signature. + * @param {string} expectedSignature the expected signature. + * @throws {Error} if it is an other signature. + */ + checkSignature: function(expectedSignature) { + if (!this.reader.readAndCheckSignature(expectedSignature)) { + this.reader.index -= 4; + var signature = this.reader.readString(4); + throw new Error("Corrupted zip or bug: unexpected signature " + "(" + utils.pretty(signature) + ", expected " + utils.pretty(expectedSignature) + ")"); + } + }, + /** + * Check if the given signature is at the given index. + * @param {number} askedIndex the index to check. + * @param {string} expectedSignature the signature to expect. + * @return {boolean} true if the signature is here, false otherwise. + */ + isSignature: function(askedIndex, expectedSignature) { + var currentIndex = this.reader.index; + this.reader.setIndex(askedIndex); + var signature = this.reader.readString(4); + var result = signature === expectedSignature; + this.reader.setIndex(currentIndex); + return result; + }, + /** + * Read the end of the central directory. + */ + readBlockEndOfCentral: function() { + this.diskNumber = this.reader.readInt(2); + this.diskWithCentralDirStart = this.reader.readInt(2); + this.centralDirRecordsOnThisDisk = this.reader.readInt(2); + this.centralDirRecords = this.reader.readInt(2); + this.centralDirSize = this.reader.readInt(4); + this.centralDirOffset = this.reader.readInt(4); + + this.zipCommentLength = this.reader.readInt(2); + // warning : the encoding depends of the system locale + // On a linux machine with LANG=en_US.utf8, this field is utf8 encoded. + // On a windows machine, this field is encoded with the localized windows code page. + var zipComment = this.reader.readData(this.zipCommentLength); + var decodeParamType = support.uint8array ? "uint8array" : "array"; + // To get consistent behavior with the generation part, we will assume that + // this is utf8 encoded unless specified otherwise. + var decodeContent = utils.transformTo(decodeParamType, zipComment); + this.zipComment = this.loadOptions.decodeFileName(decodeContent); + }, + /** + * Read the end of the Zip 64 central directory. + * Not merged with the method readEndOfCentral : + * The end of central can coexist with its Zip64 brother, + * I don't want to read the wrong number of bytes ! + */ + readBlockZip64EndOfCentral: function() { + this.zip64EndOfCentralSize = this.reader.readInt(8); + this.reader.skip(4); + // this.versionMadeBy = this.reader.readString(2); + // this.versionNeeded = this.reader.readInt(2); + this.diskNumber = this.reader.readInt(4); + this.diskWithCentralDirStart = this.reader.readInt(4); + this.centralDirRecordsOnThisDisk = this.reader.readInt(8); + this.centralDirRecords = this.reader.readInt(8); + this.centralDirSize = this.reader.readInt(8); + this.centralDirOffset = this.reader.readInt(8); + + this.zip64ExtensibleData = {}; + var extraDataSize = this.zip64EndOfCentralSize - 44, + index = 0, + extraFieldId, + extraFieldLength, + extraFieldValue; + while (index < extraDataSize) { + extraFieldId = this.reader.readInt(2); + extraFieldLength = this.reader.readInt(4); + extraFieldValue = this.reader.readData(extraFieldLength); + this.zip64ExtensibleData[extraFieldId] = { + id: extraFieldId, + length: extraFieldLength, + value: extraFieldValue + }; + } + }, + /** + * Read the end of the Zip 64 central directory locator. + */ + readBlockZip64EndOfCentralLocator: function() { + this.diskWithZip64CentralDirStart = this.reader.readInt(4); + this.relativeOffsetEndOfZip64CentralDir = this.reader.readInt(8); + this.disksCount = this.reader.readInt(4); + if (this.disksCount > 1) { + throw new Error("Multi-volumes zip are not supported"); + } + }, + /** + * Read the local files, based on the offset read in the central part. + */ + readLocalFiles: function() { + var i, file; + for (i = 0; i < this.files.length; i++) { + file = this.files[i]; + this.reader.setIndex(file.localHeaderOffset); + this.checkSignature(sig.LOCAL_FILE_HEADER); + file.readLocalPart(this.reader); + file.handleUTF8(); + file.processAttributes(); + } + }, + /** + * Read the central directory. + */ + readCentralDir: function() { + var file; + + this.reader.setIndex(this.centralDirOffset); + while (this.reader.readAndCheckSignature(sig.CENTRAL_FILE_HEADER)) { + file = new ZipEntry({ + zip64: this.zip64 + }, this.loadOptions); + file.readCentralPart(this.reader); + this.files.push(file); + } + + if (this.centralDirRecords !== this.files.length) { + if (this.centralDirRecords !== 0 && this.files.length === 0) { + // We expected some records but couldn't find ANY. + // This is really suspicious, as if something went wrong. + throw new Error("Corrupted zip or bug: expected " + this.centralDirRecords + " records in central dir, got " + this.files.length); + } else { + // We found some records but not all. + // Something is wrong but we got something for the user: no error here. + // console.warn("expected", this.centralDirRecords, "records in central dir, got", this.files.length); + } + } + }, + /** + * Read the end of central directory. + */ + readEndOfCentral: function() { + var offset = this.reader.lastIndexOfSignature(sig.CENTRAL_DIRECTORY_END); + if (offset < 0) { + // Check if the content is a truncated zip or complete garbage. + // A "LOCAL_FILE_HEADER" is not required at the beginning (auto + // extractible zip for example) but it can give a good hint. + // If an ajax request was used without responseType, we will also + // get unreadable data. + var isGarbage = !this.isSignature(0, sig.LOCAL_FILE_HEADER); + + if (isGarbage) { + throw new Error("Can't find end of central directory : is this a zip file ? " + + "If it is, see https://stuk.github.io/jszip/documentation/howto/read_zip.html"); + } else { + throw new Error("Corrupted zip: can't find end of central directory"); + } + + } + this.reader.setIndex(offset); + var endOfCentralDirOffset = offset; + this.checkSignature(sig.CENTRAL_DIRECTORY_END); + this.readBlockEndOfCentral(); + + + /* extract from the zip spec : + 4) If one of the fields in the end of central directory + record is too small to hold required data, the field + should be set to -1 (0xFFFF or 0xFFFFFFFF) and the + ZIP64 format record should be created. + 5) The end of central directory record and the + Zip64 end of central directory locator record must + reside on the same disk when splitting or spanning + an archive. + */ + if (this.diskNumber === utils.MAX_VALUE_16BITS || this.diskWithCentralDirStart === utils.MAX_VALUE_16BITS || this.centralDirRecordsOnThisDisk === utils.MAX_VALUE_16BITS || this.centralDirRecords === utils.MAX_VALUE_16BITS || this.centralDirSize === utils.MAX_VALUE_32BITS || this.centralDirOffset === utils.MAX_VALUE_32BITS) { + this.zip64 = true; + + /* + Warning : the zip64 extension is supported, but ONLY if the 64bits integer read from + the zip file can fit into a 32bits integer. This cannot be solved : JavaScript represents + all numbers as 64-bit double precision IEEE 754 floating point numbers. + So, we have 53bits for integers and bitwise operations treat everything as 32bits. + see https://developer.mozilla.org/en-US/docs/JavaScript/Reference/Operators/Bitwise_Operators + and http://www.ecma-international.org/publications/files/ECMA-ST/ECMA-262.pdf section 8.5 + */ + + // should look for a zip64 EOCD locator + offset = this.reader.lastIndexOfSignature(sig.ZIP64_CENTRAL_DIRECTORY_LOCATOR); + if (offset < 0) { + throw new Error("Corrupted zip: can't find the ZIP64 end of central directory locator"); + } + this.reader.setIndex(offset); + this.checkSignature(sig.ZIP64_CENTRAL_DIRECTORY_LOCATOR); + this.readBlockZip64EndOfCentralLocator(); + + // now the zip64 EOCD record + if (!this.isSignature(this.relativeOffsetEndOfZip64CentralDir, sig.ZIP64_CENTRAL_DIRECTORY_END)) { + // console.warn("ZIP64 end of central directory not where expected."); + this.relativeOffsetEndOfZip64CentralDir = this.reader.lastIndexOfSignature(sig.ZIP64_CENTRAL_DIRECTORY_END); + if (this.relativeOffsetEndOfZip64CentralDir < 0) { + throw new Error("Corrupted zip: can't find the ZIP64 end of central directory"); + } + } + this.reader.setIndex(this.relativeOffsetEndOfZip64CentralDir); + this.checkSignature(sig.ZIP64_CENTRAL_DIRECTORY_END); + this.readBlockZip64EndOfCentral(); + } + + var expectedEndOfCentralDirOffset = this.centralDirOffset + this.centralDirSize; + if (this.zip64) { + expectedEndOfCentralDirOffset += 20; // end of central dir 64 locator + expectedEndOfCentralDirOffset += 12 /* should not include the leading 12 bytes */ + this.zip64EndOfCentralSize; + } + + var extraBytes = endOfCentralDirOffset - expectedEndOfCentralDirOffset; + + if (extraBytes > 0) { + // console.warn(extraBytes, "extra bytes at beginning or within zipfile"); + if (this.isSignature(endOfCentralDirOffset, sig.CENTRAL_FILE_HEADER)) { + // The offsets seem wrong, but we have something at the specified offset. + // So… we keep it. + } else { + // the offset is wrong, update the "zero" of the reader + // this happens if data has been prepended (crx files for example) + this.reader.zero = extraBytes; + } + } else if (extraBytes < 0) { + throw new Error("Corrupted zip: missing " + Math.abs(extraBytes) + " bytes."); + } + }, + prepareReader: function(data) { + this.reader = readerFor(data); + }, + /** + * Read a zip file and create ZipEntries. + * @param {String|ArrayBuffer|Uint8Array|Buffer} data the binary string representing a zip file. + */ + load: function(data) { + this.prepareReader(data); + this.readEndOfCentral(); + this.readCentralDir(); + this.readLocalFiles(); + } +}; +// }}} end of ZipEntries +module.exports = ZipEntries; + +},{"./reader/readerFor":22,"./signature":23,"./support":30,"./utf8":31,"./utils":32,"./zipEntry":34}],34:[function(require,module,exports){ +'use strict'; +var readerFor = require('./reader/readerFor'); +var utils = require('./utils'); +var CompressedObject = require('./compressedObject'); +var crc32fn = require('./crc32'); +var utf8 = require('./utf8'); +var compressions = require('./compressions'); +var support = require('./support'); + +var MADE_BY_DOS = 0x00; +var MADE_BY_UNIX = 0x03; + +/** + * Find a compression registered in JSZip. + * @param {string} compressionMethod the method magic to find. + * @return {Object|null} the JSZip compression object, null if none found. + */ +var findCompression = function(compressionMethod) { + for (var method in compressions) { + if (!compressions.hasOwnProperty(method)) { + continue; + } + if (compressions[method].magic === compressionMethod) { + return compressions[method]; + } + } + return null; +}; + +// class ZipEntry {{{ +/** + * An entry in the zip file. + * @constructor + * @param {Object} options Options of the current file. + * @param {Object} loadOptions Options for loading the stream. + */ +function ZipEntry(options, loadOptions) { + this.options = options; + this.loadOptions = loadOptions; +} +ZipEntry.prototype = { + /** + * say if the file is encrypted. + * @return {boolean} true if the file is encrypted, false otherwise. + */ + isEncrypted: function() { + // bit 1 is set + return (this.bitFlag & 0x0001) === 0x0001; + }, + /** + * say if the file has utf-8 filename/comment. + * @return {boolean} true if the filename/comment is in utf-8, false otherwise. + */ + useUTF8: function() { + // bit 11 is set + return (this.bitFlag & 0x0800) === 0x0800; + }, + /** + * Read the local part of a zip file and add the info in this object. + * @param {DataReader} reader the reader to use. + */ + readLocalPart: function(reader) { + var compression, localExtraFieldsLength; + + // we already know everything from the central dir ! + // If the central dir data are false, we are doomed. + // On the bright side, the local part is scary : zip64, data descriptors, both, etc. + // The less data we get here, the more reliable this should be. + // Let's skip the whole header and dash to the data ! + reader.skip(22); + // in some zip created on windows, the filename stored in the central dir contains \ instead of /. + // Strangely, the filename here is OK. + // I would love to treat these zip files as corrupted (see http://www.info-zip.org/FAQ.html#backslashes + // or APPNOTE#4.4.17.1, "All slashes MUST be forward slashes '/'") but there are a lot of bad zip generators... + // Search "unzip mismatching "local" filename continuing with "central" filename version" on + // the internet. + // + // I think I see the logic here : the central directory is used to display + // content and the local directory is used to extract the files. Mixing / and \ + // may be used to display \ to windows users and use / when extracting the files. + // Unfortunately, this lead also to some issues : http://seclists.org/fulldisclosure/2009/Sep/394 + this.fileNameLength = reader.readInt(2); + localExtraFieldsLength = reader.readInt(2); // can't be sure this will be the same as the central dir + // the fileName is stored as binary data, the handleUTF8 method will take care of the encoding. + this.fileName = reader.readData(this.fileNameLength); + reader.skip(localExtraFieldsLength); + + if (this.compressedSize === -1 || this.uncompressedSize === -1) { + throw new Error("Bug or corrupted zip : didn't get enough information from the central directory " + "(compressedSize === -1 || uncompressedSize === -1)"); + } + + compression = findCompression(this.compressionMethod); + if (compression === null) { // no compression found + throw new Error("Corrupted zip : compression " + utils.pretty(this.compressionMethod) + " unknown (inner file : " + utils.transformTo("string", this.fileName) + ")"); + } + this.decompressed = new CompressedObject(this.compressedSize, this.uncompressedSize, this.crc32, compression, reader.readData(this.compressedSize)); + }, + + /** + * Read the central part of a zip file and add the info in this object. + * @param {DataReader} reader the reader to use. + */ + readCentralPart: function(reader) { + this.versionMadeBy = reader.readInt(2); + reader.skip(2); + // this.versionNeeded = reader.readInt(2); + this.bitFlag = reader.readInt(2); + this.compressionMethod = reader.readString(2); + this.date = reader.readDate(); + this.crc32 = reader.readInt(4); + this.compressedSize = reader.readInt(4); + this.uncompressedSize = reader.readInt(4); + var fileNameLength = reader.readInt(2); + this.extraFieldsLength = reader.readInt(2); + this.fileCommentLength = reader.readInt(2); + this.diskNumberStart = reader.readInt(2); + this.internalFileAttributes = reader.readInt(2); + this.externalFileAttributes = reader.readInt(4); + this.localHeaderOffset = reader.readInt(4); + + if (this.isEncrypted()) { + throw new Error("Encrypted zip are not supported"); + } + + // will be read in the local part, see the comments there + reader.skip(fileNameLength); + this.readExtraFields(reader); + this.parseZIP64ExtraField(reader); + this.fileComment = reader.readData(this.fileCommentLength); + }, + + /** + * Parse the external file attributes and get the unix/dos permissions. + */ + processAttributes: function () { + this.unixPermissions = null; + this.dosPermissions = null; + var madeBy = this.versionMadeBy >> 8; + + // Check if we have the DOS directory flag set. + // We look for it in the DOS and UNIX permissions + // but some unknown platform could set it as a compatibility flag. + this.dir = this.externalFileAttributes & 0x0010 ? true : false; + + if(madeBy === MADE_BY_DOS) { + // first 6 bits (0 to 5) + this.dosPermissions = this.externalFileAttributes & 0x3F; + } + + if(madeBy === MADE_BY_UNIX) { + this.unixPermissions = (this.externalFileAttributes >> 16) & 0xFFFF; + // the octal permissions are in (this.unixPermissions & 0x01FF).toString(8); + } + + // fail safe : if the name ends with a / it probably means a folder + if (!this.dir && this.fileNameStr.slice(-1) === '/') { + this.dir = true; + } + }, + + /** + * Parse the ZIP64 extra field and merge the info in the current ZipEntry. + * @param {DataReader} reader the reader to use. + */ + parseZIP64ExtraField: function(reader) { + + if (!this.extraFields[0x0001]) { + return; + } + + // should be something, preparing the extra reader + var extraReader = readerFor(this.extraFields[0x0001].value); + + // I really hope that these 64bits integer can fit in 32 bits integer, because js + // won't let us have more. + if (this.uncompressedSize === utils.MAX_VALUE_32BITS) { + this.uncompressedSize = extraReader.readInt(8); + } + if (this.compressedSize === utils.MAX_VALUE_32BITS) { + this.compressedSize = extraReader.readInt(8); + } + if (this.localHeaderOffset === utils.MAX_VALUE_32BITS) { + this.localHeaderOffset = extraReader.readInt(8); + } + if (this.diskNumberStart === utils.MAX_VALUE_32BITS) { + this.diskNumberStart = extraReader.readInt(4); + } + }, + /** + * Read the central part of a zip file and add the info in this object. + * @param {DataReader} reader the reader to use. + */ + readExtraFields: function(reader) { + var end = reader.index + this.extraFieldsLength, + extraFieldId, + extraFieldLength, + extraFieldValue; + + if (!this.extraFields) { + this.extraFields = {}; + } + + while (reader.index + 4 < end) { + extraFieldId = reader.readInt(2); + extraFieldLength = reader.readInt(2); + extraFieldValue = reader.readData(extraFieldLength); + + this.extraFields[extraFieldId] = { + id: extraFieldId, + length: extraFieldLength, + value: extraFieldValue + }; + } + + reader.setIndex(end); + }, + /** + * Apply an UTF8 transformation if needed. + */ + handleUTF8: function() { + var decodeParamType = support.uint8array ? "uint8array" : "array"; + if (this.useUTF8()) { + this.fileNameStr = utf8.utf8decode(this.fileName); + this.fileCommentStr = utf8.utf8decode(this.fileComment); + } else { + var upath = this.findExtraFieldUnicodePath(); + if (upath !== null) { + this.fileNameStr = upath; + } else { + // ASCII text or unsupported code page + var fileNameByteArray = utils.transformTo(decodeParamType, this.fileName); + this.fileNameStr = this.loadOptions.decodeFileName(fileNameByteArray); + } + + var ucomment = this.findExtraFieldUnicodeComment(); + if (ucomment !== null) { + this.fileCommentStr = ucomment; + } else { + // ASCII text or unsupported code page + var commentByteArray = utils.transformTo(decodeParamType, this.fileComment); + this.fileCommentStr = this.loadOptions.decodeFileName(commentByteArray); + } + } + }, + + /** + * Find the unicode path declared in the extra field, if any. + * @return {String} the unicode path, null otherwise. + */ + findExtraFieldUnicodePath: function() { + var upathField = this.extraFields[0x7075]; + if (upathField) { + var extraReader = readerFor(upathField.value); + + // wrong version + if (extraReader.readInt(1) !== 1) { + return null; + } + + // the crc of the filename changed, this field is out of date. + if (crc32fn(this.fileName) !== extraReader.readInt(4)) { + return null; + } + + return utf8.utf8decode(extraReader.readData(upathField.length - 5)); + } + return null; + }, + + /** + * Find the unicode comment declared in the extra field, if any. + * @return {String} the unicode comment, null otherwise. + */ + findExtraFieldUnicodeComment: function() { + var ucommentField = this.extraFields[0x6375]; + if (ucommentField) { + var extraReader = readerFor(ucommentField.value); + + // wrong version + if (extraReader.readInt(1) !== 1) { + return null; + } + + // the crc of the comment changed, this field is out of date. + if (crc32fn(this.fileComment) !== extraReader.readInt(4)) { + return null; + } + + return utf8.utf8decode(extraReader.readData(ucommentField.length - 5)); + } + return null; + } +}; +module.exports = ZipEntry; + +},{"./compressedObject":2,"./compressions":3,"./crc32":4,"./reader/readerFor":22,"./support":30,"./utf8":31,"./utils":32}],35:[function(require,module,exports){ +'use strict'; + +var StreamHelper = require('./stream/StreamHelper'); +var DataWorker = require('./stream/DataWorker'); +var utf8 = require('./utf8'); +var CompressedObject = require('./compressedObject'); +var GenericWorker = require('./stream/GenericWorker'); + +/** + * A simple object representing a file in the zip file. + * @constructor + * @param {string} name the name of the file + * @param {String|ArrayBuffer|Uint8Array|Buffer} data the data + * @param {Object} options the options of the file + */ +var ZipObject = function(name, data, options) { + this.name = name; + this.dir = options.dir; + this.date = options.date; + this.comment = options.comment; + this.unixPermissions = options.unixPermissions; + this.dosPermissions = options.dosPermissions; + + this._data = data; + this._dataBinary = options.binary; + // keep only the compression + this.options = { + compression : options.compression, + compressionOptions : options.compressionOptions + }; +}; + +ZipObject.prototype = { + /** + * Create an internal stream for the content of this object. + * @param {String} type the type of each chunk. + * @return StreamHelper the stream. + */ + internalStream: function (type) { + var result = null, outputType = "string"; + try { + if (!type) { + throw new Error("No output type specified."); + } + outputType = type.toLowerCase(); + var askUnicodeString = outputType === "string" || outputType === "text"; + if (outputType === "binarystring" || outputType === "text") { + outputType = "string"; + } + result = this._decompressWorker(); + + var isUnicodeString = !this._dataBinary; + + if (isUnicodeString && !askUnicodeString) { + result = result.pipe(new utf8.Utf8EncodeWorker()); + } + if (!isUnicodeString && askUnicodeString) { + result = result.pipe(new utf8.Utf8DecodeWorker()); + } + } catch (e) { + result = new GenericWorker("error"); + result.error(e); + } + + return new StreamHelper(result, outputType, ""); + }, + + /** + * Prepare the content in the asked type. + * @param {String} type the type of the result. + * @param {Function} onUpdate a function to call on each internal update. + * @return Promise the promise of the result. + */ + async: function (type, onUpdate) { + return this.internalStream(type).accumulate(onUpdate); + }, + + /** + * Prepare the content as a nodejs stream. + * @param {String} type the type of each chunk. + * @param {Function} onUpdate a function to call on each internal update. + * @return Stream the stream. + */ + nodeStream: function (type, onUpdate) { + return this.internalStream(type || "nodebuffer").toNodejsStream(onUpdate); + }, + + /** + * Return a worker for the compressed content. + * @private + * @param {Object} compression the compression object to use. + * @param {Object} compressionOptions the options to use when compressing. + * @return Worker the worker. + */ + _compressWorker: function (compression, compressionOptions) { + if ( + this._data instanceof CompressedObject && + this._data.compression.magic === compression.magic + ) { + return this._data.getCompressedWorker(); + } else { + var result = this._decompressWorker(); + if(!this._dataBinary) { + result = result.pipe(new utf8.Utf8EncodeWorker()); + } + return CompressedObject.createWorkerFrom(result, compression, compressionOptions); + } + }, + /** + * Return a worker for the decompressed content. + * @private + * @return Worker the worker. + */ + _decompressWorker : function () { + if (this._data instanceof CompressedObject) { + return this._data.getContentWorker(); + } else if (this._data instanceof GenericWorker) { + return this._data; + } else { + return new DataWorker(this._data); + } + } +}; + +var removedMethods = ["asText", "asBinary", "asNodeBuffer", "asUint8Array", "asArrayBuffer"]; +var removedFn = function () { + throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide."); +}; + +for(var i = 0; i < removedMethods.length; i++) { + ZipObject.prototype[removedMethods[i]] = removedFn; +} +module.exports = ZipObject; + +},{"./compressedObject":2,"./stream/DataWorker":27,"./stream/GenericWorker":28,"./stream/StreamHelper":29,"./utf8":31}],36:[function(require,module,exports){ +(function (global){ +'use strict'; +var Mutation = global.MutationObserver || global.WebKitMutationObserver; + +var scheduleDrain; + +{ + if (Mutation) { + var called = 0; + var observer = new Mutation(nextTick); + var element = global.document.createTextNode(''); + observer.observe(element, { + characterData: true + }); + scheduleDrain = function () { + element.data = (called = ++called % 2); + }; + } else if (!global.setImmediate && typeof global.MessageChannel !== 'undefined') { + var channel = new global.MessageChannel(); + channel.port1.onmessage = nextTick; + scheduleDrain = function () { + channel.port2.postMessage(0); + }; + } else if ('document' in global && 'onreadystatechange' in global.document.createElement('script')) { + scheduleDrain = function () { + + // Create a + + + + + +
+ +

index.html

+
+ + diff --git a/static/apidocs/javadoc/overview-tree.html b/static/apidocs/javadoc/overview-tree.html new file mode 100644 index 0000000000..923e76ed95 --- /dev/null +++ b/static/apidocs/javadoc/overview-tree.html @@ -0,0 +1,353 @@ + + + + + +Class Hierarchy (openlineage-java 0.21.0-SNAPSHOT API) + + + + + + + + + + + + + + +
+ +
+
+
+

Hierarchy For All Packages

+Package Hierarchies: + +
+
+
+

Class Hierarchy

+ +
+
+

Interface Hierarchy

+ +
+
+

Enum Hierarchy

+ +
+
+
+
+ +
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All rights reserved. + * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. + * + * This code is free software; you can redistribute it and/or modify it + * under the terms of the GNU General Public License version 2 only, as + * published by the Free Software Foundation. Oracle designates this + * particular file as subject to the "Classpath" exception as provided + * by Oracle in the LICENSE file that accompanied this code. + * + * This code is distributed in the hope that it will be useful, but WITHOUT + * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or + * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License + * version 2 for more details (a copy is included in the LICENSE file that + * accompanied this code). + * + * You should have received a copy of the GNU General Public License version + * 2 along with this work; if not, write to the Free Software Foundation, + * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. + * + * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA + * or visit www.oracle.com if you need additional information or have any + * questions. + */ + +var moduleSearchIndex; +var packageSearchIndex; +var typeSearchIndex; +var memberSearchIndex; +var tagSearchIndex; +function loadScripts(doc, tag) { + createElem(doc, tag, 'jquery/jszip/dist/jszip.js'); + createElem(doc, tag, 'jquery/jszip-utils/dist/jszip-utils.js'); + if (window.navigator.userAgent.indexOf('MSIE ') > 0 || window.navigator.userAgent.indexOf('Trident/') > 0 || + window.navigator.userAgent.indexOf('Edge/') > 0) { + createElem(doc, tag, 'jquery/jszip-utils/dist/jszip-utils-ie.js'); + } + createElem(doc, tag, 'search.js'); + + $.get(pathtoroot + "module-search-index.zip") + .done(function() { + JSZipUtils.getBinaryContent(pathtoroot + "module-search-index.zip", function(e, data) { + JSZip.loadAsync(data).then(function(zip){ + zip.file("module-search-index.json").async("text").then(function(content){ + moduleSearchIndex = JSON.parse(content); + }); + }); + }); + }); + $.get(pathtoroot + "package-search-index.zip") + .done(function() { + JSZipUtils.getBinaryContent(pathtoroot + "package-search-index.zip", function(e, data) { + JSZip.loadAsync(data).then(function(zip){ + zip.file("package-search-index.json").async("text").then(function(content){ + packageSearchIndex = JSON.parse(content); + }); + }); + }); + }); + $.get(pathtoroot + "type-search-index.zip") + .done(function() { + JSZipUtils.getBinaryContent(pathtoroot + "type-search-index.zip", function(e, data) { + JSZip.loadAsync(data).then(function(zip){ + zip.file("type-search-index.json").async("text").then(function(content){ + typeSearchIndex = JSON.parse(content); + }); + }); + }); + }); + $.get(pathtoroot + "member-search-index.zip") + .done(function() { + JSZipUtils.getBinaryContent(pathtoroot + "member-search-index.zip", function(e, data) { + JSZip.loadAsync(data).then(function(zip){ + zip.file("member-search-index.json").async("text").then(function(content){ + memberSearchIndex = JSON.parse(content); + }); + }); + }); + }); + $.get(pathtoroot + "tag-search-index.zip") + .done(function() { + JSZipUtils.getBinaryContent(pathtoroot + "tag-search-index.zip", function(e, data) { + JSZip.loadAsync(data).then(function(zip){ + zip.file("tag-search-index.json").async("text").then(function(content){ + tagSearchIndex = JSON.parse(content); + }); + }); + }); + }); + if (!moduleSearchIndex) { + createElem(doc, tag, 'module-search-index.js'); + } + if (!packageSearchIndex) { + createElem(doc, tag, 'package-search-index.js'); + } + if (!typeSearchIndex) { + createElem(doc, tag, 'type-search-index.js'); + } + if (!memberSearchIndex) { + createElem(doc, tag, 'member-search-index.js'); + } + if (!tagSearchIndex) { + createElem(doc, tag, 'tag-search-index.js'); + } + $(window).resize(function() { + $('.navPadding').css('padding-top', $('.fixedNav').css("height")); + }); +} + +function createElem(doc, tag, path) { + var script = doc.createElement(tag); + var scriptElement = doc.getElementsByTagName(tag)[0]; + script.src = pathtoroot + path; + scriptElement.parentNode.insertBefore(script, scriptElement); +} + +function show(type) { + count = 0; + for (var key in data) { + var row = document.getElementById(key); + if ((data[key] & type) !== 0) { + row.style.display = ''; + row.className = (count++ % 2) ? rowColor : altColor; + } + else + row.style.display = 'none'; + } + updateTabs(type); +} + +function updateTabs(type) { + for (var value in tabs) { + var sNode = document.getElementById(tabs[value][0]); + var spanNode = sNode.firstChild; + if (value == type) { + sNode.className = activeTableTab; + spanNode.innerHTML = tabs[value][1]; + } + else { + sNode.className = tableTab; + spanNode.innerHTML = "" + tabs[value][1] + ""; + } + } +} + +function updateModuleFrame(pFrame, cFrame) { + top.packageFrame.location = pFrame; + top.classFrame.location = cFrame; +} diff --git a/static/apidocs/javadoc/search.js b/static/apidocs/javadoc/search.js new file mode 100644 index 0000000000..8492271e71 --- /dev/null +++ b/static/apidocs/javadoc/search.js @@ -0,0 +1,326 @@ +/* + * Copyright (c) 2015, 2018, Oracle and/or its affiliates. All rights reserved. + * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. + * + * This code is free software; you can redistribute it and/or modify it + * under the terms of the GNU General Public License version 2 only, as + * published by the Free Software Foundation. Oracle designates this + * particular file as subject to the "Classpath" exception as provided + * by Oracle in the LICENSE file that accompanied this code. + * + * This code is distributed in the hope that it will be useful, but WITHOUT + * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or + * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License + * version 2 for more details (a copy is included in the LICENSE file that + * accompanied this code). + * + * You should have received a copy of the GNU General Public License version + * 2 along with this work; if not, write to the Free Software Foundation, + * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. + * + * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA + * or visit www.oracle.com if you need additional information or have any + * questions. + */ + +var noResult = {l: "No results found"}; +var catModules = "Modules"; +var catPackages = "Packages"; +var catTypes = "Types"; +var catMembers = "Members"; +var catSearchTags = "SearchTags"; +var highlight = "$&"; +var camelCaseRegexp = ""; +var secondaryMatcher = ""; +function getHighlightedText(item) { + var ccMatcher = new RegExp(camelCaseRegexp); + var label = item.replace(ccMatcher, highlight); + if (label === item) { + label = item.replace(secondaryMatcher, highlight); + } + return label; +} +function getURLPrefix(ui) { + var urlPrefix=""; + if (useModuleDirectories) { + var slash = "/"; + if (ui.item.category === catModules) { + return ui.item.l + slash; + } else if (ui.item.category === catPackages && ui.item.m) { + return ui.item.m + slash; + } else if ((ui.item.category === catTypes && ui.item.p) || ui.item.category === catMembers) { + $.each(packageSearchIndex, function(index, item) { + if (item.m && ui.item.p == item.l) { + urlPrefix = item.m + slash; + } + }); + return urlPrefix; + } else { + return urlPrefix; + } + } + return urlPrefix; +} +var watermark = 'Search'; +$(function() { + $("#search").val(''); + $("#search").prop("disabled", false); + $("#reset").prop("disabled", false); + $("#search").val(watermark).addClass('watermark'); + $("#search").blur(function() { + if ($(this).val().length == 0) { + $(this).val(watermark).addClass('watermark'); + } + }); + $("#search").on('click keydown', function() { + if ($(this).val() == watermark) { + $(this).val('').removeClass('watermark'); + } + }); + $("#reset").click(function() { + $("#search").val(''); + $("#search").focus(); + }); + $("#search").focus(); + $("#search")[0].setSelectionRange(0, 0); +}); +$.widget("custom.catcomplete", $.ui.autocomplete, { + _create: function() { + this._super(); + this.widget().menu("option", "items", "> :not(.ui-autocomplete-category)"); + }, + _renderMenu: function(ul, items) { + var rMenu = this, + currentCategory = ""; + rMenu.menu.bindings = $(); + $.each(items, function(index, item) { + var li; + if (item.l !== noResult.l && item.category !== currentCategory) { + ul.append("
  • " + item.category + "
  • "); + currentCategory = item.category; + } + li = rMenu._renderItemData(ul, item); + if (item.category) { + li.attr("aria-label", item.category + " : " + item.l); + li.attr("class", "resultItem"); + } else { + li.attr("aria-label", item.l); + li.attr("class", "resultItem"); + } + }); + }, + _renderItem: function(ul, item) { + var label = ""; + if (item.category === catModules) { + label = getHighlightedText(item.l); + } else if (item.category === catPackages) { + label = (item.m) + ? getHighlightedText(item.m + "/" + item.l) + : getHighlightedText(item.l); + } else if (item.category === catTypes) { + label = (item.p) + ? getHighlightedText(item.p + "." + item.l) + : getHighlightedText(item.l); + } else if (item.category === catMembers) { + label = getHighlightedText(item.p + "." + (item.c + "." + item.l)); + } else if (item.category === catSearchTags) { + label = getHighlightedText(item.l); + } else { + label = item.l; + } + var li = $("
  • ").appendTo(ul); + var div = $("
    ").appendTo(li); + if (item.category === catSearchTags) { + if (item.d) { + div.html(label + " (" + item.h + ")
    " + + item.d + "
    "); + } else { + div.html(label + " (" + item.h + ")"); + } + } else { + div.html(label); + } + return li; + } +}); +$(function() { + $("#search").catcomplete({ + minLength: 1, + delay: 100, + source: function(request, response) { + var result = new Array(); + var presult = new Array(); + var tresult = new Array(); + var mresult = new Array(); + var tgresult = new Array(); + var secondaryresult = new Array(); + var displayCount = 0; + var exactMatcher = new RegExp("^" + $.ui.autocomplete.escapeRegex(request.term) + "$", "i"); + camelCaseRegexp = ($.ui.autocomplete.escapeRegex(request.term)).split(/(?=[A-Z])/).join("([a-z0-9_$]*?)"); + var camelCaseMatcher = new RegExp("^" + camelCaseRegexp); + secondaryMatcher = new RegExp($.ui.autocomplete.escapeRegex(request.term), "i"); + + // Return the nested innermost name from the specified object + function nestedName(e) { + return e.l.substring(e.l.lastIndexOf(".") + 1); + } + + function concatResults(a1, a2) { + a1 = a1.concat(a2); + a2.length = 0; + return a1; + } + + if (moduleSearchIndex) { + var mdleCount = 0; + $.each(moduleSearchIndex, function(index, item) { + item.category = catModules; + if (exactMatcher.test(item.l)) { + result.push(item); + mdleCount++; + } else if (camelCaseMatcher.test(item.l)) { + result.push(item); + } else if (secondaryMatcher.test(item.l)) { + secondaryresult.push(item); + } + }); + displayCount = mdleCount; + result = concatResults(result, secondaryresult); + } + if (packageSearchIndex) { + var pCount = 0; + var pkg = ""; + $.each(packageSearchIndex, function(index, item) { + item.category = catPackages; + pkg = (item.m) + ? 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page header and footer. + */ +.header, .footer { + clear:both; + margin:0 20px; + padding:5px 0 0 0; +} +.indexNav { + position:relative; + font-size:12px; + background-color:#dee3e9; +} +.indexNav ul { + margin-top:0; + padding:5px; +} +.indexNav ul li { + display:inline; + list-style-type:none; + padding-right:10px; + text-transform:uppercase; +} +.indexNav h1 { + font-size:13px; +} +.title { + color:#2c4557; + margin:10px 0; +} +.subTitle { + margin:5px 0 0 0; +} +.header ul { + margin:0 0 15px 0; + padding:0; +} +.footer ul { + margin:20px 0 5px 0; +} +.header ul li, .footer ul li { + list-style:none; + font-size:13px; +} +/* + * Styles for headings. + */ +div.details ul.blockList ul.blockList ul.blockList li.blockList h4, div.details ul.blockList ul.blockList ul.blockListLast li.blockList h4 { + background-color:#dee3e9; + border:1px solid #d0d9e0; + margin:0 0 6px -8px; + padding:7px 5px; +} +ul.blockList ul.blockList ul.blockList li.blockList h3 { + background-color:#dee3e9; + 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zJJYPorg1FFRz^&ELA`Uni`i|LyI&^xWFBjhdSK{kWB9;7`&CCm;_CH#s6Tof@@98;l~%-^&kW(44 + + + + + OpenLineage API Docs + + + + + + + + + +

    OpenLineage (1-0-5)

    Download OpenAPI specification:Download

    License: Apache 2.0

    OpenLineage is an open source lineage and metadata collection API for the data ecosystem.

    +

    OpenLineage

    Send an event related to the state of a run

    Updates a run state for a job.

    +
    Request Body schema: application/json
    eventType
    string
    Enum: "START" "RUNNING" "COMPLETE" "ABORT" "FAIL" "OTHER"

    the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete

    +
    eventTime
    required
    string <date-time>

    the time the event occurred at

    +
    required
    object (Run)
    required
    object (Job)
    Array of objects (InputDataset)

    The set of input datasets.

    +
    Array of objects (OutputDataset)

    The set of output datasets.

    +
    producer
    required
    string <uri>

    URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha

    +
    schemaURL
    required
    string <uri>

    The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent

    +

    Responses

    Request samples

    Content type
    application/json
    {}
    + + + + \ No newline at end of file diff --git a/static/spec/1-0-0/OpenLineage.json b/static/spec/1-0-0/OpenLineage.json new file mode 100644 index 0000000000..a225bf5a6a --- /dev/null +++ b/static/spec/1-0-0/OpenLineage.json @@ -0,0 +1,586 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-0/OpenLineage.json", + "definitions": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occured at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/definitions/Run" + }, + "job": { + "$ref": "#/definitions/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/definitions/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/definitions/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "properties": { + "nominalTime": { + "$ref": "#/definitions/NominalTimeRunFacet" + }, + "parent": { + "$ref": "#/definitions/ParentRunFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "runId" + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "properties": { + "documentation": { + "$ref": "#/definitions/DocumentationJobFacet" + }, + "sourceCodeLocation": { + "$ref": "#/definitions/SourceCodeLocationJobFacet" + }, + "sql": { + "$ref": "#/definitions/SQLJobFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/definitions/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "properties": { + "dataQualityMetrics" : { + "$ref": "#/definitions/DataQualityMetricsInputDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + } + } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/definitions/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "properties": { + "outputStatistics": { + "$ref": "#/definitions/OutputStatisticsOutputDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + } + } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "properties": { + "documentation": { + "$ref": "#/definitions/DocumentationDatasetFacet" + }, + "schema": { + "$ref": "#/definitions/SchemaDatasetFacet" + }, + "dataSource": { + "$ref": "#/definitions/DatasourceDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json#/definitions/BaseFacet" + } + }, + "required": [ + "_producer", + "_schemaURL" + ] + }, + + "CustomFacet": { + "description": "a Custom Facet is defined is a separate spec. field must not start with _", + "type": "object", + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "additionalProperties": true + } + ] + }, + + "NominalTimeRunFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "nominalStartTime": { + "description": "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal start time (included) of the run. AKA the schedule time", + "type": "string", + "format": "date-time", + "example": "2020-12-17T03:00:00.000Z" + }, + "nominalEndTime": { + "description": "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal end time (excluded) of the run. (Should be the nominal start time of the next run)", + "type": "string", + "format": "date-time", + "example": "2020-12-17T04:00:00.000Z" + } + }, + "required": [ + "nominalStartTime" + ] + } + ], + "type": "object" + }, + "ParentRunFacet": { + "description": "the id of the parent run and job, iff this run was spawn from an other run (for example, the Dag run scheduling its tasks)", + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + } + }, + "required": [ + "runId" + ] + }, + "job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + } + }, + "required": [ + "namespace", + "name" + ] + } + }, + "required": [ + "run", + "job" + ] + } + ], + "type": "object" + }, + + "DocumentationJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "description": { + "description": "The description of the job.", + "type": "string" + } + }, + "required": [ + "description" + ] + } + ], + "type": "object" + }, + "SourceCodeLocationJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "type": { + "type": "string", + "description": "the source control system", + "example":"git|svn" + }, + "url": { + "type": "string", + "description": "the full http URL to locate the file", + "format": "uri", + "example": "https://github.com/MarquezProject/marquez-airflow-quickstart/blob/693e35482bc2e526ced2b5f9f76ef83dec6ec691/dags/dummy_example.py" + }, + "repoUrl": { + "type": "string", + "description": "the URL to the repository", + "example": "git@github.com:{org}/{repo}.git or https://github.com/{org}/{repo}.git|svn:///" + }, + "path": { + "type": "string", + "description": "the path in the repo containing the source files", + "example": "path/to/my/dags" + }, + "version": { + "type": "string", + "description": "the current version deployed (not a branch name, the actual unique version)", + "example": "git: the git sha | Svn: the revision number" + }, + "tag": { + "type": "string", + "description": "optional tag name" + }, + "branch": { + "type": "string", + "description": "optional branch name" + } + }, + "required": [ + "type", "url" + ] + } + ], + "type": "object" + }, + "SQLJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "query": { + "type": "string", + "example": "SELECT * FROM foo" + } + }, + "required": [ + "query" + ] + } + ], + "type": "object" + }, + "OutputStatisticsOutputDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "rowCount": { + "description": "The number of rows written to the dataset", + "type": "integer" + }, + "size": { + "description": "The size in bytes written to the dataset", + "type": "integer" + } + }, + "required": [ + "rowCount" + ] + } + ] + }, + "DataQualityMetricsInputDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "required": ["columnMetrics"], + "properties": { + "rowCount": { + "description": "The number of rows evaluated", + "type": "integer" + }, + "bytes": { + "description": "The size in bytes", + "type": "integer" + }, + "columnMetrics": { + "description": "The property key is the column name", + "type": "object", + "additionalProperties": { + "type": "object", + "properties": { + "nullCount": { + "description": "The number of null values in this column for the rows evaluated", + "type": "integer" + }, + "distinctCount": { + "description": "The number of distinct values in this column for the rows evaluated", + "type": "integer" + }, + "sum": { + "description": "The total sum of values in this column for the rows evaluated", + "type": "number" + }, + "count": { + "description": "The number of values in this column", + "type": "number" + }, + "min": {"type": "number"}, + "max": {"type": "number"}, + "quantiles": { + "description": "The property key is the quantile. Examples: 0.1 0.25 0.5 0.75 1", + "type": "object", + "additionalProperties": {"type": "number"} + } + } + } + } + } + } + ], + "type": "object" + }, + "DocumentationDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "description": { + "description": "The description of the dataset.", + "type": "string", + "example": "canonical representation of entity Foo" + } + }, + "required": [ + "description" + ] + } + ], + "type": "object" + }, + "SchemaDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "fields": { + "description": "The fields of the table.", + "type": "array", + "items": { + "type": "object", + "properties": { + "name": { + "description": "The name of the field.", + "type": "string", + "example": "column1" + }, + "type": { + "description": "The type of the field.", + "type": "string", + "example": "VARCHAR|INT|..." + }, + "description": { + "description": "The description of the field.", + "type": "string" + } + }, + "required": [ + "name" + ] + } + } + } + } + ], + "type": "object" + }, + "DatasourceDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "name": { + "type": "string" + }, + "uri": { + "type": "string", + "format": "uri" + } + } + } + ], + "type": "object" + } + }, + "oneOf": [ + { + "$ref": "#/definitions/RunEvent" + } + ] +} diff --git a/static/spec/1-0-1/OpenLineage.json b/static/spec/1-0-1/OpenLineage.json new file mode 100644 index 0000000000..1215bd651a --- /dev/null +++ b/static/spec/1-0-1/OpenLineage.json @@ -0,0 +1,624 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-1/OpenLineage.json", + "definitions": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occured at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/definitions/Run" + }, + "job": { + "$ref": "#/definitions/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/definitions/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/definitions/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "properties": { + "nominalTime": { + "$ref": "#/definitions/NominalTimeRunFacet" + }, + "parent": { + "$ref": "#/definitions/ParentRunFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "runId" + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "properties": { + "documentation": { + "$ref": "#/definitions/DocumentationJobFacet" + }, + "sourceCodeLocation": { + "$ref": "#/definitions/SourceCodeLocationJobFacet" + }, + "sql": { + "$ref": "#/definitions/SQLJobFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/definitions/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "properties": { + "dataQualityMetrics" : { + "$ref": "#/definitions/DataQualityMetricsInputDatasetFacet" + }, + "dataQualityAssertions": { + "$ref": "#/definitions/DataQualityAssertionsDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + } + } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/definitions/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "properties": { + "outputStatistics": { + "$ref": "#/definitions/OutputStatisticsOutputDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + } + } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "properties": { + "documentation": { + "$ref": "#/definitions/DocumentationDatasetFacet" + }, + "schema": { + "$ref": "#/definitions/SchemaDatasetFacet" + }, + "dataSource": { + "$ref": "#/definitions/DatasourceDatasetFacet" + } + }, + "additionalProperties": { + "$ref": "#/definitions/CustomFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json#/definitions/BaseFacet" + } + }, + "required": [ + "_producer", + "_schemaURL" + ] + }, + + "CustomFacet": { + "description": "a Custom Facet is defined is a separate spec. field must not start with _", + "type": "object", + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "additionalProperties": true + } + ] + }, + + "NominalTimeRunFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "nominalStartTime": { + "description": "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal start time (included) of the run. AKA the schedule time", + "type": "string", + "format": "date-time", + "example": "2020-12-17T03:00:00.000Z" + }, + "nominalEndTime": { + "description": "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal end time (excluded) of the run. (Should be the nominal start time of the next run)", + "type": "string", + "format": "date-time", + "example": "2020-12-17T04:00:00.000Z" + } + }, + "required": [ + "nominalStartTime" + ] + } + ], + "type": "object" + }, + "ParentRunFacet": { + "description": "the id of the parent run and job, iff this run was spawn from an other run (for example, the Dag run scheduling its tasks)", + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + } + }, + "required": [ + "runId" + ] + }, + "job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + } + }, + "required": [ + "namespace", + "name" + ] + } + }, + "required": [ + "run", + "job" + ] + } + ], + "type": "object" + }, + + "DocumentationJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "description": { + "description": "The description of the job.", + "type": "string" + } + }, + "required": [ + "description" + ] + } + ], + "type": "object" + }, + "SourceCodeLocationJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "type": { + "type": "string", + "description": "the source control system", + "example":"git|svn" + }, + "url": { + "type": "string", + "description": "the full http URL to locate the file", + "format": "uri", + "example": "https://github.com/MarquezProject/marquez-airflow-quickstart/blob/693e35482bc2e526ced2b5f9f76ef83dec6ec691/dags/dummy_example.py" + }, + "repoUrl": { + "type": "string", + "description": "the URL to the repository", + "example": "git@github.com:{org}/{repo}.git or https://github.com/{org}/{repo}.git|svn:///" + }, + "path": { + "type": "string", + "description": "the path in the repo containing the source files", + "example": "path/to/my/dags" + }, + "version": { + "type": "string", + "description": "the current version deployed (not a branch name, the actual unique version)", + "example": "git: the git sha | Svn: the revision number" + }, + "tag": { + "type": "string", + "description": "optional tag name" + }, + "branch": { + "type": "string", + "description": "optional branch name" + } + }, + "required": [ + "type", "url" + ] + } + ], + "type": "object" + }, + "SQLJobFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "query": { + "type": "string", + "example": "SELECT * FROM foo" + } + }, + "required": [ + "query" + ] + } + ], + "type": "object" + }, + "OutputStatisticsOutputDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "rowCount": { + "description": "The number of rows written to the dataset", + "type": "integer" + }, + "size": { + "description": "The size in bytes written to the dataset", + "type": "integer" + } + }, + "required": [ + "rowCount" + ] + } + ] + }, + "DataQualityAssertionsDatasetFacet": { + "description": "list of tests performed on dataset or dataset columns, and their results", + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "required": ["assertions"], + "properties": { + "assertions": { + "type": "array", + "items": { + "type": "object", + "properties": { + "assertion": { + "type": "string", + "description": "Type of expectation test that dataset is subjected to", + "example": "not_null" + }, + "success": {"type": "boolean"}, + "column": { + "type": "string", + "description": "Column that expectation is testing. It should match the name provided in SchemaDatasetFacet. If column field is empty, then expectation refers to whole dataset.", + "example": "id" + } + }, + "required": ["assertion", "success"] + } + } + } + } + ], + "type": "object" + }, + "DataQualityMetricsInputDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "required": ["columnMetrics"], + "properties": { + "rowCount": { + "description": "The number of rows evaluated", + "type": "integer" + }, + "bytes": { + "description": "The size in bytes", + "type": "integer" + }, + "columnMetrics": { + "description": "The property key is the column name", + "type": "object", + "additionalProperties": { + "type": "object", + "properties": { + "nullCount": { + "description": "The number of null values in this column for the rows evaluated", + "type": "integer" + }, + "distinctCount": { + "description": "The number of distinct values in this column for the rows evaluated", + "type": "integer" + }, + "sum": { + "description": "The total sum of values in this column for the rows evaluated", + "type": "number" + }, + "count": { + "description": "The number of values in this column", + "type": "number" + }, + "min": {"type": "number"}, + "max": {"type": "number"}, + "quantiles": { + "description": "The property key is the quantile. Examples: 0.1 0.25 0.5 0.75 1", + "type": "object", + "additionalProperties": {"type": "number"} + } + } + } + } + } + } + ], + "type": "object" + }, + "DocumentationDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "description": { + "description": "The description of the dataset.", + "type": "string", + "example": "canonical representation of entity Foo" + } + }, + "required": [ + "description" + ] + } + ], + "type": "object" + }, + "SchemaDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "fields": { + "description": "The fields of the table.", + "type": "array", + "items": { + "type": "object", + "properties": { + "name": { + "description": "The name of the field.", + "type": "string", + "example": "column1" + }, + "type": { + "description": "The type of the field.", + "type": "string", + "example": "VARCHAR|INT|..." + }, + "description": { + "description": "The description of the field.", + "type": "string" + } + }, + "required": [ + "name" + ] + } + } + } + } + ], + "type": "object" + }, + "DatasourceDatasetFacet": { + "allOf": [ + { + "$ref": "#/definitions/BaseFacet" + }, + { + "type": "object", + "properties": { + "name": { + "type": "string" + }, + "uri": { + "type": "string", + "format": "uri" + } + } + } + ], + "type": "object" + } + }, + "oneOf": [ + { + "$ref": "#/definitions/RunEvent" + } + ] +} diff --git a/static/spec/1-0-2/OpenLineage.json b/static/spec/1-0-2/OpenLineage.json new file mode 100644 index 0000000000..6945d62f4d --- /dev/null +++ b/static/spec/1-0-2/OpenLineage.json @@ -0,0 +1,236 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-2/OpenLineage.json", + "$defs": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occurred at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/$defs/Run" + }, + "job": { + "$ref": "#/$defs/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/RunFacet" + } + } + }, + "required": [ + "runId" + ] + }, + "RunFacet": { + "description": "A Run Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/JobFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "JobFacet": { + "description": "A Job Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/InputDatasetFacet" + } + } + } + } + ] + }, + "InputDatasetFacet": { + "description": "An Input Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/OutputDatasetFacet" + } + } + } + } + ] + }, + "OutputDatasetFacet": { + "description": "An Output Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/DatasetFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "DatasetFacet": { + "description": "A Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/BaseFacet" + } + }, + "additionalProperties": true, + "required": [ + "_producer", + "_schemaURL" + ] + } + }, + "$ref": "#/$defs/RunEvent" +} diff --git a/static/spec/1-0-3/OpenLineage.json b/static/spec/1-0-3/OpenLineage.json new file mode 100644 index 0000000000..4e61a76aec --- /dev/null +++ b/static/spec/1-0-3/OpenLineage.json @@ -0,0 +1,237 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-3/OpenLineage.json", + "$defs": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "RUNNING", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|RUNNING|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occurred at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/$defs/Run" + }, + "job": { + "$ref": "#/$defs/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/RunFacet" + } + } + }, + "required": [ + "runId" + ] + }, + "RunFacet": { + "description": "A Run Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/JobFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "JobFacet": { + "description": "A Job Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/InputDatasetFacet" + } + } + } + } + ] + }, + "InputDatasetFacet": { + "description": "An Input Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/OutputDatasetFacet" + } + } + } + } + ] + }, + "OutputDatasetFacet": { + "description": "An Output Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "additionalProperties": { + "$ref": "#/$defs/DatasetFacet" + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "DatasetFacet": { + "description": "A Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/BaseFacet" + } + }, + "additionalProperties": true, + "required": [ + "_producer", + "_schemaURL" + ] + } + }, + "$ref": "#/$defs/RunEvent" +} diff --git a/static/spec/1-0-4/OpenLineage.json b/static/spec/1-0-4/OpenLineage.json new file mode 100644 index 0000000000..9271e6d8f3 --- /dev/null +++ b/static/spec/1-0-4/OpenLineage.json @@ -0,0 +1,266 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-4/OpenLineage.json", + "$defs": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "RUNNING", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|RUNNING|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occurred at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/$defs/Run" + }, + "job": { + "$ref": "#/$defs/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "additionalProperties": { + "anyOf": [ + { "$ref": "#/$defs/RunFacet" }, + { "$ref": "facets/ErrorMessageRunFacet.json" }, + { "$ref": "facets/NominalTimeRunFacet.json" }, + { "$ref": "facets/ParentRunFacet.json" } + ] + } + } + }, + "required": [ + "runId" + ] + }, + "RunFacet": { + "description": "A Run Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "additionalProperties": { + "anyOf": [ + { "$ref": "#/$defs/JobFacet" }, + { "$ref": "facets/DocumentationJobFacet.json" }, + { "$ref": "facets/OwnershipJobFacet.json" }, + { "$ref": "facets/SourceCodeJobFacet.json" }, + { "$ref": "facets/SourceCodeLocationJobFacet.json" }, + { "$ref": "facets/SQLJobFacet.json" } + ] + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "JobFacet": { + "description": "A Job Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "additionalProperties": { + "anyOf": [ + { "$ref": "#/$defs/InputDatasetFacet" }, + { "$ref": "facets/DataQualityMetricsInputDatasetFacet.json"} + ] + } + } + } + } + ] + }, + "InputDatasetFacet": { + "description": "An Input Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "additionalProperties": { + "anyOf": [ + { "$ref": "#/$defs/OutputDatasetFacet" }, + { "$ref": "facets/OutputStatisticsOutputDatasetFacet.json"} + ] + } + } + } + } + ] + }, + "OutputDatasetFacet": { + "description": "An Output Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "additionalProperties": { + "anyOf": [ + { "$ref": "#/$defs/DatasetFacet" }, + { "$ref": "facets/ColumnLineageDatasetFacet.json" }, + { "$ref": "facets/DatasourceDatasetFacet.json" }, + { "$ref": "facets/DataQualityAssertionsDatasetFacet.json" }, + { "$ref": "facets/LifecycleStateChangeDatasetFacet.json" }, + { "$ref": "facets/OwnershipDatasetFacet.json" }, + { "$ref": "facets/SchemaDatasetFacet.json" }, + { "$ref": "facets/StorageDatasetFacet.json" }, + { "$ref": "facets/SymlinksDatasetFacet.json" }, + { "$ref": "facets/DatasetVersionDatasetFacet.json" } + ] + } + } + }, + "required": [ + "namespace", + "name" + ] + }, + "DatasetFacet": { + "description": "A Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/BaseFacet" + } + }, + "additionalProperties": true, + "required": [ + "_producer", + "_schemaURL" + ] + } + }, + "$ref": "#/$defs/RunEvent" +} diff --git a/static/spec/1-0-5/OpenLineage.json b/static/spec/1-0-5/OpenLineage.json new file mode 100644 index 0000000000..92ba831478 --- /dev/null +++ b/static/spec/1-0-5/OpenLineage.json @@ -0,0 +1,272 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/1-0-5/OpenLineage.json", + "$defs": { + "RunEvent": { + "type": "object", + "properties": { + "eventType": { + "description": "the current transition of the run state. It is required to issue 1 START event and 1 of [ COMPLETE, ABORT, FAIL ] event per run. Additional events with OTHER eventType can be added to the same run. For example to send additional metadata after the run is complete", + "type": "string", + "enum": [ + "START", + "RUNNING", + "COMPLETE", + "ABORT", + "FAIL", + "OTHER" + ], + "example": "START|RUNNING|COMPLETE|ABORT|FAIL|OTHER" + }, + "eventTime": { + "description": "the time the event occurred at", + "type": "string", + "format": "date-time" + }, + "run": { + "$ref": "#/$defs/Run" + }, + "job": { + "$ref": "#/$defs/Job" + }, + "inputs": { + "description": "The set of **input** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/InputDataset" + } + }, + "outputs": { + "description": "The set of **output** datasets.", + "type": "array", + "items": { + "$ref": "#/$defs/OutputDataset" + } + }, + "producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this RunEvent", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/0-0-1/OpenLineage.json" + } + }, + "required": [ + "run", + "job", + "eventTime", + "producer", + "schemaURL" + ] + }, + "Run": { + "type": "object", + "properties": { + "runId": { + "description": "The globally unique ID of the run associated with the job.", + "type": "string", + "format": "uuid" + }, + "facets": { + "description": "The run facets.", + "type": "object", + "anyOf": [ + { + "type": "object", + "additionalProperties": { "$ref": "#/$defs/RunFacet" } + }, + { "$ref": "facets/ErrorMessageRunFacet.json" }, + { "$ref": "facets/ExternalQueryRunFacet.json" }, + { "$ref": "facets/NominalTimeRunFacet.json" }, + { "$ref": "facets/ParentRunFacet.json" } + ] + } + }, + "required": [ + "runId" + ] + }, + "RunFacet": { + "description": "A Run Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Job": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that job", + "type": "string", + "example": "my-scheduler-namespace" + }, + "name": { + "description": "The unique name for that job within that namespace", + "type": "string", + "example": "myjob.mytask" + }, + "facets": { + "description": "The job facets.", + "type": "object", + "anyOf": [ + { + "type": "object", + "additionalProperties": { "$ref": "#/$defs/JobFacet" } + }, + { "$ref": "facets/DocumentationJobFacet.json" }, + { "$ref": "facets/OwnershipJobFacet.json" }, + { "$ref": "facets/SourceCodeJobFacet.json" }, + { "$ref": "facets/SourceCodeLocationJobFacet.json" }, + { "$ref": "facets/SQLJobFacet.json" } + ] + } + }, + "required": [ + "namespace", + "name" + ] + }, + "JobFacet": { + "description": "A Job Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "InputDataset": { + "description": "An input dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "inputFacets": { + "description": "The input facets for this dataset.", + "type": "object", + "anyOf": [ + { + "type": "object", + "additionalProperties": { "$ref": "#/$defs/InputDatasetFacet" } + }, + { "$ref": "facets/DataQualityMetricsInputDatasetFacet.json"} + ] + } + } + } + ] + }, + "InputDatasetFacet": { + "description": "An Input Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "OutputDataset": { + "description": "An output dataset", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/Dataset" }, + { + "type": "object", + "properties": { + "outputFacets": { + "description": "The output facets for this dataset", + "type": "object", + "anyOf": [ + { + "type": "object", + "additionalProperties": { "$ref": "#/$defs/OutputDatasetFacet" } + }, + { "$ref": "facets/OutputStatisticsOutputDatasetFacet.json"} + ] + } + } + } + ] + }, + "OutputDatasetFacet": { + "description": "An Output Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "Dataset": { + "type": "object", + "properties": { + "namespace": { + "description": "The namespace containing that dataset", + "type": "string", + "example": "my-datasource-namespace" + }, + "name": { + "description": "The unique name for that dataset within that namespace", + "type": "string", + "example": "instance.schema.table" + }, + "facets": { + "description": "The facets for this dataset", + "type": "object", + "anyOf": [ + { + "type": "object", + "additionalProperties": { "$ref": "#/$defs/DatasetFacet" } + }, + { "$ref": "facets/ColumnLineageDatasetFacet.json" }, + { "$ref": "facets/DatasourceDatasetFacet.json" }, + { "$ref": "facets/DataQualityAssertionsDatasetFacet.json" }, + { "$ref": "facets/LifecycleStateChangeDatasetFacet.json" }, + { "$ref": "facets/OwnershipDatasetFacet.json" }, + { "$ref": "facets/SchemaDatasetFacet.json" }, + { "$ref": "facets/StorageDatasetFacet.json" }, + { "$ref": "facets/SymlinksDatasetFacet.json" }, + { "$ref": "facets/DatasetVersionDatasetFacet.json" } + ] + } + }, + "required": [ + "namespace", + "name" + ] + }, + "DatasetFacet": { + "description": "A Dataset Facet", + "type": "object", + "allOf": [ + { "$ref": "#/$defs/BaseFacet" } + ] + }, + "BaseFacet": { + "description": "all fields of the base facet are prefixed with _ to avoid name conflicts in facets", + "type": "object", + "properties": { + "_producer": { + "description": "URI identifying the producer of this metadata. For example this could be a git url with a given tag or sha", + "type": "string", + "format": "uri", + "example": "https://github.com/OpenLineage/OpenLineage/blob/v1-0-0/client" + }, + "_schemaURL": { + "description": "The JSON Pointer (https://tools.ietf.org/html/rfc6901) URL to the corresponding version of the schema definition for this facet", + "type": "string", + "format": "uri", + "example": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/BaseFacet" + } + }, + "additionalProperties": true, + "required": [ + "_producer", + "_schemaURL" + ] + } + }, + "$ref": "#/$defs/RunEvent" +} diff --git a/static/spec/OpenLineage.yml b/static/spec/OpenLineage.yml new file mode 100644 index 0000000000..50b7996fe5 --- /dev/null +++ b/static/spec/OpenLineage.yml @@ -0,0 +1,25 @@ +openapi: 3.0.2 +info: + title: OpenLineage + version: 1-0-5 + description: OpenLineage is an open source **lineage and metadata collection API** for the data ecosystem. + license: + name: Apache 2.0 + url: http://www.apache.org/licenses/LICENSE-2.0.html +paths: + /lineage: + post: + summary: Send an event related to the state of a run + description: Updates a run state for a job. + operationId: postRunEvent + tags: + - OpenLineage + requestBody: + content: + application/json: + schema: + $ref: 'OpenLineage.json#/$defs/RunEvent' + responses: + '200': + description: OK + diff --git a/static/spec/facets/1-0-0/ColumnLineageDatasetFacet.json b/static/spec/facets/1-0-0/ColumnLineageDatasetFacet.json new file mode 100644 index 0000000000..dec3543730 --- /dev/null +++ b/static/spec/facets/1-0-0/ColumnLineageDatasetFacet.json @@ -0,0 +1,59 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/facets/1-0-0/ColumnLineageDatasetFacet.json", + "$defs": { + "ColumnLineageDatasetFacet": { + "allOf": [{ + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type": "object", + "properties": { + "fields": { + "description": "Column level lineage that maps output fields into input fields used to evaluate them.", + "type": "object", + "additionalProperties": { + "type": "object", + "properties": { + "inputFields": { + "type": "array", + "items": { + "type": "object", + "properties": { + "namespace": { + "type": "string", + "description": "The input dataset namespace" + }, + "name": { + "type": "string", + "description": "The input dataset name" + }, + "field": { + "type": "string", + "description": "The input field" + } + }, + "required": [ + "namespace", "name", "field" + ] + } + } + }, + "required": ["inputFields"] + } + } + }, + "additionalProperties": true, + "required": [ + "fields" + ] + }], + "type": "object" + } + }, + "type": "object", + "properties": { + "columnLineage": { + "$ref": "#/$defs/ColumnLineageDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/DataQualityAssertionsDatasetFacet.json b/static/spec/facets/1-0-0/DataQualityAssertionsDatasetFacet.json new file mode 100644 index 0000000000..b7a6bc4f65 --- /dev/null +++ b/static/spec/facets/1-0-0/DataQualityAssertionsDatasetFacet.json @@ -0,0 +1,46 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DataQualityAssertionsDatasetFacet.json", + "$defs" : { + "DataQualityAssertionsDatasetFacet" : { + "description" : "list of tests performed on dataset or dataset columns, and their results", + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/InputDatasetFacet" + }, { + "type" : "object", + "required" : [ "assertions" ], + "properties" : { + "assertions" : { + "type" : "array", + "items" : { + "type" : "object", + "properties" : { + "assertion" : { + "type" : "string", + "description" : "Type of expectation test that dataset is subjected to", + "example" : "not_null" + }, + "success" : { + "type" : "boolean" + }, + "column" : { + "type" : "string", + "description" : "Column that expectation is testing. It should match the name provided in SchemaDatasetFacet. If column field is empty, then expectation refers to whole dataset.", + "example" : "id" + } + }, + "required" : [ "assertion", "success" ] + } + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "dataQualityAssertions" : { + "$ref" : "#/$defs/DataQualityAssertionsDatasetFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/DataQualityMetricsInputDatasetFacet.json b/static/spec/facets/1-0-0/DataQualityMetricsInputDatasetFacet.json new file mode 100644 index 0000000000..f0a965a32a --- /dev/null +++ b/static/spec/facets/1-0-0/DataQualityMetricsInputDatasetFacet.json @@ -0,0 +1,69 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DataQualityMetricsInputDatasetFacet.json", + "$defs" : { + "DataQualityMetricsInputDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/InputDatasetFacet" + }, { + "type" : "object", + "required" : [ "columnMetrics" ], + "properties" : { + "rowCount" : { + "description" : "The number of rows evaluated", + "type" : "integer" + }, + "bytes" : { + "description" : "The size in bytes", + "type" : "integer" + }, + "columnMetrics" : { + "description" : "The property key is the column name", + "type" : "object", + "additionalProperties" : { + "type" : "object", + "properties" : { + "nullCount" : { + "description" : "The number of null values in this column for the rows evaluated", + "type" : "integer" + }, + "distinctCount" : { + "description" : "The number of distinct values in this column for the rows evaluated", + "type" : "integer" + }, + "sum" : { + "description" : "The total sum of values in this column for the rows evaluated", + "type" : "number" + }, + "count" : { + "description" : "The number of values in this column", + "type" : "number" + }, + "min" : { + "type" : "number" + }, + "max" : { + "type" : "number" + }, + "quantiles" : { + "description" : "The property key is the quantile. Examples: 0.1 0.25 0.5 0.75 1", + "type" : "object", + "additionalProperties" : { + "type" : "number" + } + } + } + } + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "dataQualityMetrics" : { + "$ref" : "#/$defs/DataQualityMetricsInputDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/DatasetVersionDatasetFacet.json b/static/spec/facets/1-0-0/DatasetVersionDatasetFacet.json new file mode 100644 index 0000000000..200d09a243 --- /dev/null +++ b/static/spec/facets/1-0-0/DatasetVersionDatasetFacet.json @@ -0,0 +1,33 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DatasetVersionDatasetFacet.json", + "$defs" : { + "DatasetVersionDatasetFacet": { + "allOf": [ + { + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, + { + "type": "object", + "properties": { + "datasetVersion": { + "description": "The version of the dataset.", + "type": "string" + } + }, + "additionalProperties": true, + "required": [ + "datasetVersion" + ] + } + ], + "type": "object" + } + }, + "type" : "object", + "properties" : { + "version" : { + "$ref" : "#/$defs/DatasetVersionDatasetFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/DatasourceDatasetFacet.json b/static/spec/facets/1-0-0/DatasourceDatasetFacet.json new file mode 100644 index 0000000000..7eb3ec4279 --- /dev/null +++ b/static/spec/facets/1-0-0/DatasourceDatasetFacet.json @@ -0,0 +1,29 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DatasourceDatasetFacet.json", + "$defs" : { + "DatasourceDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type" : "object", + "properties" : { + "name" : { + "type" : "string" + }, + "uri" : { + "type" : "string", + "format" : "uri" + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "dataSource" : { + "$ref" : "#/$defs/DatasourceDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/DocumentationDatasetFacet.json b/static/spec/facets/1-0-0/DocumentationDatasetFacet.json new file mode 100644 index 0000000000..40964dea35 --- /dev/null +++ b/static/spec/facets/1-0-0/DocumentationDatasetFacet.json @@ -0,0 +1,28 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DocumentationDatasetFacet.json", + "$defs" : { + "DocumentationDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type" : "object", + "properties" : { + "description" : { + "description" : "The description of the dataset.", + "type" : "string", + "example" : "canonical representation of entity Foo" + } + }, + "required" : [ "description" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "documentation" : { + "$ref" : "#/$defs/DocumentationDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/DocumentationJobFacet.json b/static/spec/facets/1-0-0/DocumentationJobFacet.json new file mode 100644 index 0000000000..cd892a187e --- /dev/null +++ b/static/spec/facets/1-0-0/DocumentationJobFacet.json @@ -0,0 +1,27 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/DocumentationJobFacet.json", + "$defs" : { + "DocumentationJobFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/JobFacet" + }, { + "type" : "object", + "properties" : { + "description" : { + "description" : "The description of the job.", + "type" : "string" + } + }, + "required" : [ "description" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "documentation" : { + "$ref" : "#/$defs/DocumentationJobFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/ErrorMessageRunFacet.json b/static/spec/facets/1-0-0/ErrorMessageRunFacet.json new file mode 100644 index 0000000000..59c249e8ac --- /dev/null +++ b/static/spec/facets/1-0-0/ErrorMessageRunFacet.json @@ -0,0 +1,38 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/ErrorMessageRunFacet.json", + "$defs" : { + "ErrorMessageRunFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/RunFacet" + }, { + "type" : "object", + "properties" : { + "message" : { + "description" : "A human-readable string representing error message generated by observed system", + "type" : "string", + "example" : "org.apache.spark.sql.AnalysisException: Table or view not found: wrong_table_name; line 1 pos 14" + }, + "programmingLanguage" : { + "description" : "Programming language the observed system uses.", + "type" : "string", + "example" : "JAVA" + }, + "stackTrace" : { + "description" : "A language-specific stack trace generated by observed system", + "type" : "string", + "example" : "Exception in thread \"main\" java.lang.RuntimeException: A test exception\nat io.openlineage.SomeClass.method(SomeClass.java:13)\nat io.openlineage.SomeClass.anotherMethod(SomeClass.java:9)" + } + }, + "required" : [ "message", "programmingLanguage" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "errorMessage" : { + "$ref" : "#/$defs/ErrorMessageRunFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/ExternalQueryRunFacet.json b/static/spec/facets/1-0-0/ExternalQueryRunFacet.json new file mode 100644 index 0000000000..09ba5f7101 --- /dev/null +++ b/static/spec/facets/1-0-0/ExternalQueryRunFacet.json @@ -0,0 +1,33 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/ExternalQueryRunFacet.json", + "$defs" : { + "ExternalQueryRunFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/RunFacet" + }, { + "type" : "object", + "properties" : { + "externalQueryId" : { + "description" : "Identifier for the external system", + "type" : "string", + "example" : "my-project-1234:US.bquijob_123x456_123y123z123c" + }, + "source" : { + "description" : "source of the external query", + "type" : "string", + "example" : "bigquery" + } + }, + "required" : [ "externalQueryId", "source" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "externalQuery" : { + "$ref" : "#/$defs/ExternalQueryRunFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/ExtractionErrorRunFacet.json b/static/spec/facets/1-0-0/ExtractionErrorRunFacet.json new file mode 100644 index 0000000000..099680dba9 --- /dev/null +++ b/static/spec/facets/1-0-0/ExtractionErrorRunFacet.json @@ -0,0 +1,64 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/facets/1-0-0/ExtractionErrorRunFacet.json", + "$defs": { + "ExtractionErrorRunFacet": { + "allOf": [ + { + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/RunFacet" + }, + { + "type": "object", + "properties": { + "totalTasks": { + "description": "The number of distinguishable tasks in a run that were processed by OpenLineage, whether successfully or not. Those could be, for example, distinct SQL statements.", + "type": "integer" + }, + "failedTasks": { + "description": "The number of distinguishable tasks in a run that were processed not successfully by OpenLineage. Those could be, for example, distinct SQL statements.", + "type": "integer" + }, + "errors": { + "type": "array", + "items": { + "type": "object", + "properties": { + "errorMessage": { + "description": "Text representation of extraction error message.", + "type": "string" + }, + "stackTrace": { + "description": "Stack trace of extraction error message", + "type": "string" + }, + "task": { + "description": "Text representation of task that failed. This can be, for example, SQL statement that parser could not interpret.", + "type": "string" + }, + "taskNumber": { + "description": "Order of task (counted from 0).", + "type": "integer" + } + }, + "required": [ + "errorMessage" + ] + } + } + }, + "required": [ + "totalElements", + "failedElements", + "errors" + ] + } + ] + } + }, + "type": "object", + "properties": { + "extractionError": { + "$ref": "#/$defs/ExtractionErrorRunFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/LifecycleStateChangeDatasetFacet.json b/static/spec/facets/1-0-0/LifecycleStateChangeDatasetFacet.json new file mode 100644 index 0000000000..dfdec3c2d5 --- /dev/null +++ b/static/spec/facets/1-0-0/LifecycleStateChangeDatasetFacet.json @@ -0,0 +1,43 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/facets/1-0-0/LifecycleStateChangeDatasetFacet.json", + "$defs": { + "LifecycleStateChangeDatasetFacet": { + "allOf": [{ + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type": "object", + "properties": { + "lifecycleStateChange": { + "description": "The lifecycle state change.", + "type": "string", + "enum": ["ALTER", "CREATE", "DROP", "OVERWRITE", "RENAME", "TRUNCATE"] + }, + "previousIdentifier": { + "description": "Previous name of the dataset in case of renaming it.", + "type": "object", + "properties": { + "name": { + "documentation": "Previous dataset name.", + "type": "string" + }, + "namespace": { + "documentation": "Previous dataset namespace.", + "type": "string" + } + }, + "required": ["name", "namespace"] + } + }, + "required": ["lifecycleStateChange"] + }], + "type": "object" + } + }, + "type": "object", + "properties": { + "lifecycleStateChange": { + "$ref": "#/$defs/LifecycleStateChangeDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/NominalTimeRunFacet.json b/static/spec/facets/1-0-0/NominalTimeRunFacet.json new file mode 100644 index 0000000000..b48350714c --- /dev/null +++ b/static/spec/facets/1-0-0/NominalTimeRunFacet.json @@ -0,0 +1,35 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/NominalTimeRunFacet.json", + "$defs" : { + "NominalTimeRunFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/RunFacet" + }, { + "type" : "object", + "properties" : { + "nominalStartTime" : { + "description" : "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal start time (included) of the run. AKA the schedule time", + "type" : "string", + "format" : "date-time", + "example" : "2020-12-17T03:00:00.000Z" + }, + "nominalEndTime" : { + "description" : "An [ISO-8601](https://en.wikipedia.org/wiki/ISO_8601) timestamp representing the nominal end time (excluded) of the run. (Should be the nominal start time of the next run)", + "type" : "string", + "format" : "date-time", + "example" : "2020-12-17T04:00:00.000Z" + } + }, + "required" : [ "nominalStartTime" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "nominalTime" : { + "$ref" : "#/$defs/NominalTimeRunFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/OutputStatisticsOutputDatasetFacet.json b/static/spec/facets/1-0-0/OutputStatisticsOutputDatasetFacet.json new file mode 100644 index 0000000000..e0dbc1f6a2 --- /dev/null +++ b/static/spec/facets/1-0-0/OutputStatisticsOutputDatasetFacet.json @@ -0,0 +1,30 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/OutputStatisticsOutputDatasetFacet.json", + "$defs" : { + "OutputStatisticsOutputDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/OutputDatasetFacet" + }, { + "type" : "object", + "properties" : { + "rowCount" : { + "description" : "The number of rows written to the dataset", + "type" : "integer" + }, + "size" : { + "description" : "The size in bytes written to the dataset", + "type" : "integer" + } + }, + "required" : [ "rowCount" ] + } ] + } + }, + "type" : "object", + "properties" : { + "outputStatistics" : { + "$ref" : "#/$defs/OutputStatisticsOutputDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/OwnershipDatasetFacet.json b/static/spec/facets/1-0-0/OwnershipDatasetFacet.json new file mode 100644 index 0000000000..47a7c61c06 --- /dev/null +++ b/static/spec/facets/1-0-0/OwnershipDatasetFacet.json @@ -0,0 +1,42 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/OwnershipDatasetFacet.json", + "$defs" : { + "OwnershipDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-3/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type" : "object", + "properties" : { + "owners" : { + "description" : "The owners of the dataset.", + "type" : "array", + "items" : { + "type" : "object", + "properties" : { + "name" : { + "description" : "the identifier of the owner of the Dataset. It is recommended to define this as a URN. For example application:foo, user:jdoe, team:data", + "type" : "string", + "example" : "application:app_name" + }, + "type" : { + "description" : "The type of ownership (optional)", + "type" : "string", + "example" : "MAINTAINER" + } + }, + "required" : [ "name" ] + } + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "ownership" : { + "$ref" : "#/$defs/OwnershipDatasetFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/OwnershipJobFacet.json b/static/spec/facets/1-0-0/OwnershipJobFacet.json new file mode 100644 index 0000000000..822da45b34 --- /dev/null +++ b/static/spec/facets/1-0-0/OwnershipJobFacet.json @@ -0,0 +1,42 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/OwnershipJobFacet.json", + "$defs" : { + "OwnershipJobFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-3/OpenLineage.json#/$defs/JobFacet" + }, { + "type" : "object", + "properties" : { + "owners" : { + "description" : "The owners of the job.", + "type" : "array", + "items" : { + "type" : "object", + "properties" : { + "name" : { + "description" : "the identifier of the owner of the Job. It is recommended to define this as a URN. For example application:foo, user:jdoe, team:data", + "type" : "string", + "example" : "application:app_name" + }, + "type" : { + "description" : "The type of ownership (optional)", + "type" : "string", + "example" : "MAINTAINER" + } + }, + "required" : [ "name" ] + } + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "ownership" : { + "$ref" : "#/$defs/OwnershipJobFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/ParentRunFacet.json b/static/spec/facets/1-0-0/ParentRunFacet.json new file mode 100644 index 0000000000..1c774406d6 --- /dev/null +++ b/static/spec/facets/1-0-0/ParentRunFacet.json @@ -0,0 +1,51 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/ParentRunFacet.json", + "$defs" : { + "ParentRunFacet" : { + "description" : "the id of the parent run and job, iff this run was spawn from an other run (for example, the Dag run scheduling its tasks)", + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/RunFacet" + }, { + "type" : "object", + "properties" : { + "run" : { + "type" : "object", + "properties" : { + "runId" : { + "description" : "The globally unique ID of the run associated with the job.", + "type" : "string", + "format" : "uuid" + } + }, + "required" : [ "runId" ] + }, + "job" : { + "type" : "object", + "properties" : { + "namespace" : { + "description" : "The namespace containing that job", + "type" : "string", + "example" : "my-scheduler-namespace" + }, + "name" : { + "description" : "The unique name for that job within that namespace", + "type" : "string", + "example" : "myjob.mytask" + } + }, + "required" : [ "namespace", "name" ] + } + }, + "required" : [ "run", "job" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "parent" : { + "$ref" : "#/$defs/ParentRunFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/ProcessingEngineRunFacet.json b/static/spec/facets/1-0-0/ProcessingEngineRunFacet.json new file mode 100644 index 0000000000..315a514d20 --- /dev/null +++ b/static/spec/facets/1-0-0/ProcessingEngineRunFacet.json @@ -0,0 +1,41 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/facets/1-0-0/ProcessingEngineRunFacet.json", + "$defs": { + "ProcessingEngineRunFacet": { + "allOf": [ + { + "$ref": "https://openlineage.io/spec/1-0-3/OpenLineage.json#/$defs/RunFacet" + }, + { + "type": "object", + "properties": { + "version": { + "description": "Processing engine version. Might be Airflow or Spark version.", + "type": "string", + "example": "2.5.0" + }, + "name": { + "description": "Processing engine name, e.g. Airflow or Spark", + "type": "string", + "example": "Airflow" + }, + "openlineageAdapterVersion": { + "description": "OpenLineage adapter package version. Might be e.g. OpenLineage Airflow integration package version", + "type": "string", + "example": "0.19.0" + } + }, + "required": ["engine_version"] + } + ], + "type": "object" + } + }, + "type": "object", + "properties": { + "processing_engine": { + "$ref": "#/$defs/ProcessingEngineRunFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/SQLJobFacet.json b/static/spec/facets/1-0-0/SQLJobFacet.json new file mode 100644 index 0000000000..9aa9e6a5b1 --- /dev/null +++ b/static/spec/facets/1-0-0/SQLJobFacet.json @@ -0,0 +1,27 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/SQLJobFacet.json", + "$defs" : { + "SQLJobFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/JobFacet" + }, { + "type" : "object", + "properties" : { + "query" : { + "type" : "string", + "example" : "SELECT * FROM foo" + } + }, + "required" : [ "query" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "sql" : { + "$ref" : "#/$defs/SQLJobFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/SchemaDatasetFacet.json b/static/spec/facets/1-0-0/SchemaDatasetFacet.json new file mode 100644 index 0000000000..ccaad87d7b --- /dev/null +++ b/static/spec/facets/1-0-0/SchemaDatasetFacet.json @@ -0,0 +1,46 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/SchemaDatasetFacet.json", + "$defs" : { + "SchemaDatasetFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type" : "object", + "properties" : { + "fields" : { + "description" : "The fields of the table.", + "type" : "array", + "items" : { + "type" : "object", + "properties" : { + "name" : { + "description" : "The name of the field.", + "type" : "string", + "example" : "column1" + }, + "type" : { + "description" : "The type of the field.", + "type" : "string", + "example" : "VARCHAR|INT|..." + }, + "description" : { + "description" : "The description of the field.", + "type" : "string" + } + }, + "required" : [ "name" ] + } + } + } + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "schema" : { + "$ref" : "#/$defs/SchemaDatasetFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/SourceCodeJobFacet.json b/static/spec/facets/1-0-0/SourceCodeJobFacet.json new file mode 100644 index 0000000000..2d238c2275 --- /dev/null +++ b/static/spec/facets/1-0-0/SourceCodeJobFacet.json @@ -0,0 +1,31 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/SourceCodeJobFacet.json", + "$defs" : { + "SourceCodeJobFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/JobFacet" + }, { + "type" : "object", + "properties" : { + "language" : { + "description" : "Language in which source code of this job was written.", + "type" : "string" + }, + "sourceCode" : { + "description" : "Source code of this job.", + "type" : "string" + } + }, + "required" : [ "language", "sourceCode" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "sourceCode" : { + "$ref" : "#/$defs/SourceCodeJobFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/SourceCodeLocationJobFacet.json b/static/spec/facets/1-0-0/SourceCodeLocationJobFacet.json new file mode 100644 index 0000000000..0b08b6195d --- /dev/null +++ b/static/spec/facets/1-0-0/SourceCodeLocationJobFacet.json @@ -0,0 +1,57 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/SourceCodeLocationJobFacet.json", + "$defs" : { + "SourceCodeLocationJobFacet" : { + "allOf" : [ { + "$ref" : "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/JobFacet" + }, { + "type" : "object", + "properties" : { + "type" : { + "type" : "string", + "description" : "the source control system", + "example" : "git|svn" + }, + "url" : { + "type" : "string", + "description" : "the full http URL to locate the file", + "format" : "uri", + "example" : "https://github.com/MarquezProject/marquez-airflow-quickstart/blob/693e35482bc2e526ced2b5f9f76ef83dec6ec691/dags/dummy_example.py" + }, + "repoUrl" : { + "type" : "string", + "description" : "the URL to the repository", + "example" : "git@github.com:{org}/{repo}.git or https://github.com/{org}/{repo}.git|svn:///" + }, + "path" : { + "type" : "string", + "description" : "the path in the repo containing the source files", + "example" : "path/to/my/dags" + }, + "version" : { + "type" : "string", + "description" : "the current version deployed (not a branch name, the actual unique version)", + "example" : "git: the git sha | Svn: the revision number" + }, + "tag" : { + "type" : "string", + "description" : "optional tag name" + }, + "branch" : { + "type" : "string", + "description" : "optional branch name" + } + }, + "required" : [ "type", "url" ] + } ], + "type" : "object" + } + }, + "type" : "object", + "properties" : { + "sourceCodeLocation" : { + "$ref" : "#/$defs/SourceCodeLocationJobFacet" + } + } +} \ No newline at end of file diff --git a/static/spec/facets/1-0-0/StorageDatasetFacet.json b/static/spec/facets/1-0-0/StorageDatasetFacet.json new file mode 100644 index 0000000000..ea318c1c8f --- /dev/null +++ b/static/spec/facets/1-0-0/StorageDatasetFacet.json @@ -0,0 +1,37 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/StorageDatasetFacet.json", + "$defs" : { + "StorageDatasetFacet": { + "allOf": [ + { + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, + { + "type": "object", + "properties": { + "storageLayer": { + "description": "Storage layer provider with allowed values: iceberg, delta.", + "type": "string" + }, + "fileFormat": { + "description": "File format with allowed values: parquet, orc, avro, json, csv, text, xml.", + "type": "string" + } + }, + "additionalProperties": true, + "required": [ + "storageLayer" + ] + } + ], + "type": "object" + } + }, + "type" : "object", + "properties" : { + "storage" : { + "$ref" : "#/$defs/StorageDatasetFacet" + } + } +} diff --git a/static/spec/facets/1-0-0/SymlinksDatasetFacet.json b/static/spec/facets/1-0-0/SymlinksDatasetFacet.json new file mode 100644 index 0000000000..28c3ad053a --- /dev/null +++ b/static/spec/facets/1-0-0/SymlinksDatasetFacet.json @@ -0,0 +1,47 @@ +{ + "$schema" : "https://json-schema.org/draft/2020-12/schema", + "$id" : "https://openlineage.io/spec/facets/1-0-0/SymlinksDatasetFacet.json", + "$defs" : { + "SymlinksDatasetFacet": { + "allOf": [ + { + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, + { + "type" : "object", + "properties": { + "identifiers": { + "type": "array", + "items": { + "type": "object", + "properties": { + "namespace": { + "type": "string", + "description": "The dataset namespace" + }, + "name": { + "type": "string", + "description": "The dataset name" + }, + "type": { + "type": "string", + "description": "Identifier type", + "example": "table" + } + }, + "required": ["namespace", "name", "type"] + } + } + } + } + ], + "type": "object" + } + }, + "type" : "object", + "properties" : { + "symlinks" : { + "$ref" : "#/$defs/SymlinksDatasetFacet" + } + } +} diff --git a/static/spec/facets/1-0-1/ColumnLineageDatasetFacet.json b/static/spec/facets/1-0-1/ColumnLineageDatasetFacet.json new file mode 100644 index 0000000000..a171a89bae --- /dev/null +++ b/static/spec/facets/1-0-1/ColumnLineageDatasetFacet.json @@ -0,0 +1,69 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "https://openlineage.io/spec/facets/1-0-1/ColumnLineageDatasetFacet.json", + "$defs": { + "ColumnLineageDatasetFacet": { + "allOf": [{ + "$ref": "https://openlineage.io/spec/1-0-2/OpenLineage.json#/$defs/DatasetFacet" + }, { + "type": "object", + "properties": { + "fields": { + "description": "Column level lineage that maps output fields into input fields used to evaluate them.", + "type": "object", + "additionalProperties": { + "type": "object", + "properties": { + "inputFields": { + "type": "array", + "items": { + "type": "object", + "properties": { + "namespace": { + "type": "string", + "description": "The input dataset namespace" + }, + "name": { + "type": "string", + "description": "The input dataset name" + }, + "field": { + "type": "string", + "description": "The input field" + } + }, + "additionalProperties": true, + "required": [ + "namespace", "name", "field" + ] + } + }, + "transformationDescription": { + "type": "string", + "description": "a string representation of the transformation applied" + }, + "transformationType": { + "type": "string", + "description": "IDENTITY|MASKED reflects a clearly defined behavior. IDENTITY: exact same as input; MASKED: no original data available (like a hash of PII for example)" + } + }, + "additionalProperties": true, + "required": ["inputFields"] + } + } + }, + "additionalProperties": true, + "required": [ + "fields" + ] + }], + "type": "object" + } + }, + "type": "object", + "properties": { + "columnLineage": { + "$ref": "#/$defs/ColumnLineageDatasetFacet" + } + } +} From 99ee78c328de4f2550887ff47993ca2c7adaaccf Mon Sep 17 00:00:00 2001 From: tito1212 Date: Mon, 13 Mar 2023 12:55:49 +0100 Subject: [PATCH 3/9] Remove integration page. Update files from website commit 3d09dc94529de93f8bab6c519f74f00882608892 Signed-off-by: tito1212 --- README.md | 6 - blog/data-council-meetup/banner.svg | 1 + blog/data-council-meetup/image.svg | 1 + blog/data-council-meetup/index.mdx | 41 +++++ blog/data-lineage-meetup/index.mdx | 17 +- docusaurus.config.js | 1 - src/components/item-integration.tsx | 46 ----- .../apache-airflow/af-schematic.svg | 1 - .../integration/apache-airflow/banner.svg | 1 - .../integration/apache-airflow/index.mdx | 91 --------- .../integration/apache-airflow/stack.png | Bin 65720 -> 0 bytes src/pages/integration/apache-spark/banner.svg | 1 - src/pages/integration/apache-spark/index.mdx | 173 ------------------ .../apache-spark/spark-job-creation.dot | 22 --- .../apache-spark/spark-job-creation.dot.png | Bin 35513 -> 0 bytes src/pages/integration/apache-spark/stack.png | Bin 67912 -> 0 bytes src/pages/integration/dbt/banner.svg | 1 - src/pages/integration/dbt/index.mdx | 70 ------- 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.../apidocs/javadoc/package-search-index.zip | Bin 256 -> 256 bytes static/apidocs/javadoc/serialized-form.html | 4 +- static/apidocs/javadoc/type-search-index.zip | Bin 1130 -> 1130 bytes 198 files changed, 407 insertions(+), 832 deletions(-) create mode 100644 blog/data-council-meetup/banner.svg create mode 100644 blog/data-council-meetup/image.svg create mode 100644 blog/data-council-meetup/index.mdx delete mode 100644 src/components/item-integration.tsx delete mode 100644 src/pages/integration/apache-airflow/af-schematic.svg delete mode 100644 src/pages/integration/apache-airflow/banner.svg delete mode 100644 src/pages/integration/apache-airflow/index.mdx delete mode 100644 src/pages/integration/apache-airflow/stack.png delete mode 100644 src/pages/integration/apache-spark/banner.svg delete mode 100644 src/pages/integration/apache-spark/index.mdx delete mode 100644 src/pages/integration/apache-spark/spark-job-creation.dot delete mode 100644 src/pages/integration/apache-spark/spark-job-creation.dot.png delete mode 100644 src/pages/integration/apache-spark/stack.png delete mode 100644 src/pages/integration/dbt/banner.svg delete mode 100644 src/pages/integration/dbt/index.mdx delete mode 100644 src/pages/integration/index.tsx diff --git a/README.md b/README.md index 7cdb005a2d..01279c315d 100644 --- a/README.md +++ b/README.md @@ -54,12 +54,6 @@ $ nvm install 16 $ nvm use 16 ``` -Install Yarn and the Gatsby CLI: - -``` -$ npm install -g yarn gatsby-cli -``` - Run Yarn to install all of the Node dependencies for the project: ``` diff --git a/blog/data-council-meetup/banner.svg b/blog/data-council-meetup/banner.svg new file mode 100644 index 0000000000..abcae1289f --- /dev/null +++ b/blog/data-council-meetup/banner.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/data-council-meetup/image.svg b/blog/data-council-meetup/image.svg new file mode 100644 index 0000000000..17bde83de2 --- /dev/null +++ b/blog/data-council-meetup/image.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/blog/data-council-meetup/index.mdx b/blog/data-council-meetup/index.mdx new file mode 100644 index 0000000000..2bb5449d1a --- /dev/null +++ b/blog/data-council-meetup/index.mdx @@ -0,0 +1,41 @@ +--- +title: Meet Us at Data Council Austin +date: 2023-02-28 +author: Michael Robinson +image: ./image.svg +banner: ./banner.svg +description: The OpenLineage community will be gathering on March 30th at Data Council Austin -- join us! +--- + +[Data Council](https://www.datacouncil.ai/), known for putting on wonderful +events that attract the best and brightest speakers in the data ecosystem, will +be holding its only [conference of 2023](https://www.datacouncil.ai/austin) in +Austin, Texas, on March 28-30th, and OpenLineage will be there. + +![](./banner.svg#full-width) + + + +Among the speakers at this year's event will be OpenLineage Project Lead and +[Astronomer](https://astronomer.io) Chief Architect [Julien Le Dem](https://www.datacouncil.ai/talks/ten-years-of-building-open-source-standards?hsLang=en). +Julien will be speaking on March 30th at 10 am CST. + +Also, we are planning an OpenLineage event for conference attendees. Join Julien +and other members of the OpenLineage community on March 30th from 12:15-1:30 pm +at the [AT&T Hotel and Conference Center](https://meetattexas.com/hotel) on the +campus of UT Austin for a community meetup. + +You can expect a wide-ranging, open-ended discussion of the past, present and +future of the OpenLineage spec. You'll also meet other members of the data +ecosystem, learn more about the project's goals and design, and be able to +participate in a conversation about what's next. + +If you haven't registered for this event yet, click +[this link](https://www.tickettailor.com/events/datacouncil/747883?hsCtaTracking=dc0af239-1ec5-4c9f-a175-f487bb858074%7Ca9aa7625-43fb-436d-b05d-9666bab6e414&_ga=2.239870401.316757827.1677608801-1529956930.1676647160) +and use the code OpenLineage20. Also, watch this space for additional details +about the meetup as the date draws near. We hope to see you there. + +### Meetup Details +- Date: March 30, 2023 +- Time: 12:15-1:30 pm CST +- Place: AT&T Hotel and Conference Center, UT Austin, Room 105 diff --git a/blog/data-lineage-meetup/index.mdx b/blog/data-lineage-meetup/index.mdx index 1db2660cb0..10194cfd4f 100644 --- a/blog/data-lineage-meetup/index.mdx +++ b/blog/data-lineage-meetup/index.mdx @@ -6,23 +6,22 @@ image: ./image.svg banner: ./banner.svg description: The inaugural Data Lineage Meetup will take place on March 9th in Providence, RI. --- -The inaugural Data Lineage Meetup will take place on March 9th in Providence, RI. + +Join us on Thursday, March 9, 2023 from 6-8 pm in Providence, Rhode Island, to learn more about the present and future of OpenLineage. Meet other members of the ecosystem, learn about the project’s goals and fundamental design, and participate in a discussion about the future of the project. Bring your ideas and vision for OpenLineage! ![](./banner.svg#full-width) -Join us on Thursday, March 9, 2023 from 6-8 pm in Providence, Rhode Island to learn more about the present and future of OpenLineage. Meet other members of the ecosystem, learn about the project’s goals and fundamental design, and participate in a discussion about the future of the project. Bring your ideas and vision for OpenLineage! - -Food will be provided, and the meetup is open to all, no registration needed. Don't miss this opportunity to influence the direction of this important new standard! We hope to see you there. +Food will be provided, and the meetup is open to all. Don't miss this opportunity to influence the direction of this important new standard! We hope to see you there. Please [sign up](https://www.meetup.com/providence-data-lineage-meetup/events/291847062/) to let us know you're coming. ### Time, Place & Format Date: March 9, 2023 +Format: In-person Time: 6-8 pm ET -Address: [CIC](https://cic.com/providence), [225 Dyer Street](https://goo.gl/maps/NYBbs4ht91dWWaRs9) -City: Providence, RI, US 02903 -Format: In-person +Address: [CIC](https://cic.com/providence), [225 Dyer Street](https://goo.gl/maps/NYBbs4ht91dWWaRs9), Providence, RI, US 02903 +

    #### Getting There - Air: the nearest airport is T.F. Green/PVD. Boston Logan is also within 1.5-2 hours' driving distance. @@ -35,4 +34,8 @@ Format: In-person #### Getting In - Check in with the CIC concierge inside the north entrance. The concierge will direct you to the Hope Island Room on the 3rd floor. +#### Arriving Early? +- Come to the coffee bar in [Plant City](https://www.plantcitypvd.com/) at 334 South Water Street, Providence RI 02903, which is a short walk from CIC. Other out-of-towners will be meeting up there between 3 and 6 pm. +

    + ### Hope to see you there! diff --git a/docusaurus.config.js b/docusaurus.config.js index fab18702de..c573a0cf21 100644 --- a/docusaurus.config.js +++ b/docusaurus.config.js @@ -6,7 +6,6 @@ const darkCodeTheme = require('prism-react-renderer/themes/dracula'); const links = [ { to: '/docs/getting-started/', label: 'Getting Started', position: 'left' }, - { to: 'integration', label: 'Integration', position: 'left' }, { to: '/resources', label: 'Resources', position: 'left' }, { to: '/blog', label: 'Blog', position: 'left' }, { to: '/ecosystem', label: 'Ecosystem', position: 'left' }, diff --git a/src/components/item-integration.tsx b/src/components/item-integration.tsx deleted file mode 100644 index 6e69faca56..0000000000 --- a/src/components/item-integration.tsx +++ /dev/null @@ -1,46 +0,0 @@ -import React from "react" -import { ArrowRight } from "react-feather" -export const ItemIntegration = ({ data, even }) => { - - let datasources = data.datasources.split(',') - - let rowList = datasources.map((datasource, index) => { - return ( - - {index === 0 && ( - -

    {data.title}

    -

    {data.description}

    - - )} - - {index === 0 && ( - - {data.version.split(',').map((item, i) =>

    {item}

    )} - - )} - -

    {datasource}

    - - {index === 0 && ( - - - - )} - - ) - }) - - return rowList -} - -export default ItemIntegration; \ No newline at end of file diff --git a/src/pages/integration/apache-airflow/af-schematic.svg b/src/pages/integration/apache-airflow/af-schematic.svg deleted file mode 100644 index 8263bc9765..0000000000 --- a/src/pages/integration/apache-airflow/af-schematic.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/src/pages/integration/apache-airflow/banner.svg b/src/pages/integration/apache-airflow/banner.svg deleted file mode 100644 index 10b8464c1d..0000000000 --- a/src/pages/integration/apache-airflow/banner.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/src/pages/integration/apache-airflow/index.mdx b/src/pages/integration/apache-airflow/index.mdx deleted file mode 100644 index 2749034996..0000000000 --- a/src/pages/integration/apache-airflow/index.mdx +++ /dev/null @@ -1,91 +0,0 @@ ---- -title: Apache Airflow -description: Enabling OpenLineage in Apache Airflow automatically tracks metadata about jobs and datasets as DAGs execute. -image: ./stack.png -banner: ./banner.svg -version: 1.10+, 2.0+ -datasources: PostgreSQL, MySQL, Snowflake, Amazon Athena, Amazon Redshift, Amazon SageMaker, Amazon S3 Copy, Google BigQuery, Great Expectations, SFTP -github: https://github.com/OpenLineage/OpenLineage/tree/main/integration/airflow -blog: https://openlineage.io/blog/backfilling-airflow-dags-using-marquez/ -slug: integration/apache-airflow ---- - -![image](./banner.svg#full-width) - -## What is Apache Airflow? - -**Airflow** is a widely-used workflow automation and scheduling platform that can be used to author and manage data pipelines. Airflow uses workflows made of directed acyclic graphs (DAGs) of tasks. To learn more about Airflow, check out the Airflow [documentation](https://airflow.apache.org/docs/apache-airflow/stable/index.html). - -## How does Airflow work with OpenLineage? - -Understanding complex inter-DAG dependencies and providing up-to-date runtime visibility into DAG execution can be challenging. OpenLineage integrates with Airflow to collect DAG lineage metadata so that inter-DAG dependencies are easily maintained and viewable via a lineage graph, while also keeping a catalog of historical runs of DAGs. - - -![image](./af-schematic.svg) - - -The integration is implemented using the [openlineage-airflow](https://pypi.org/project/openlineage-airflow) integration library, which sends OpenLineage events to [Marquez](https://marquezproject.ai). The DAG metadata collected can answer questions like: - -* Why has a DAG failed? -* Why has the DAG runtime increased after a code change? -* What are the upstream dependencies of a DAG? - - -## How can I use this integration? - -### Prerequisites - -To use the OpenLineage Airflow integration, you'll need a running Airflow instance. You'll also need an OpenLineage compatible [HTTP backend](https://github.com/OpenLineage/OpenLineage#scope). In this guide, we'll be using the `openlineage-airflow` library to automatically send OpenLineage events to [Marquez](https://marquezproject.ai). - -### Configuration - -Next, we'll need to specify where we want Airflow to send OpenLineage events. `openlineage-airflow` will use the `OPENLINEAGE_URL` environment variable to send OpenLineage events to Marquez. Optionally, we can also specify a namespace where the lineage events will be stored using the `OPENLINEAGE_NAMESPACE` environment variable. - -For example, to send OpenLineage events to a local instance of Marquez with the `dev` namespace, use: - -```bash -OPENLINEAGE_URL=http://localhost:5000 -OPENLINEAGE_NAMESPACE="dev" -``` - -### Usage -#### Airflow 1.10+ - -First, download and install the latest `openlineage-airflow` library, by updating the `requirements.txt` file of your running Airflow instance with: - -``` -openlineage-airflow -``` - -Then, to begin collecting Airflow DAG metadata with Marquez, make the following change to your DAG: - -```diff -- from airflow import DAG -+ from openlineage.airflow import DAG -``` - -#### Airflow 2.0+ -Set your LineageBackend in your [airflow.cfg](https://airflow.apache.org/docs/apache-airflow/stable/howto/set-config.html) or via environmental variable `AIRFLOW__LINEAGE__BACKEND` to -``` -openlineage.lineage_backend.OpenLineageBackend -``` -In contrast to integration via subclassing `DAG`, the `LineageBackend` based approach collects all metadata for task on each task completion. - -### What to expect -When enabled, the library will: - -* On DAG **start**, collect metadata for each task -* Collect task input / output metadata (source, schema, etc) -* Collect task run-level metadata (execution time, state, parameters, etc) -* On DAG **complete**, also mark the task as complete in Marquez - -## Where can I learn more? - -* Take a look at Marquez's Airflow [example](https://github.com/MarquezProject/marquez/tree/main/examples/airflow) to learn how to enable OpenLineage metadata collection for Airflow DAGs and troubleshoot failing DAGs using Marquez. -* Watch [Data Lineage with Apache Airflow](https://www.youtube.com/watch?v=dfRetdg9444) - -## Feedback - -What did you think of this guide? 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zA$L-!sV(R{^ak_tLT{G*-r(p^f&L{Tzi`P!?H+B4N#P!YX9l~iW!5?1Jw9C+Y5GhS z7O2Xys>`3er&}N#`ur!SJ4IuJ()&KHkR!6}f(naj;PY8Q)eA?R?uqIx+S=V3b}W=i z5pSB&&#_px6>;zByliGR<&L)LU*PUkZ&ttYb6X0gkQ;(m@z74SazTx%*OQ6ECRdPh24hT7<)8miQPQuvcEPL z#oYBgNT2=(B~||`%X2+Q(~+oH!W(52!(~L{T*cU`g8~-l+W#?M|8G~h z{+Y@1|9wsFU)27mm79Md;lEhd{TGJ*g`xlMyMg}!7-E4B9R)#R3547fG1h^j(0Qn@ KiP8A;uYUvo(wB7r diff --git a/src/pages/integration/apache-spark/banner.svg b/src/pages/integration/apache-spark/banner.svg deleted file mode 100644 index 35eba1ce2f..0000000000 --- a/src/pages/integration/apache-spark/banner.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/src/pages/integration/apache-spark/index.mdx b/src/pages/integration/apache-spark/index.mdx deleted file mode 100644 index 532e5cb4dd..0000000000 --- a/src/pages/integration/apache-spark/index.mdx +++ /dev/null @@ -1,173 +0,0 @@ ---- -title: Apache Spark -description: OpenLineage can automatically track lineage of jobs and datasets across Spark jobs. -image: ./stack.png -banner: ./banner.svg -version: 2.4+ -datasources: JDBC, HDFS, Google Cloud Storage, Google BigQuery, Amazon S3, Azure Blob Storage, Azure Data Lake Gen2, Azure Synapse -github: https://github.com/OpenLineage/OpenLineage/tree/main/integration/spark -slug: integration/apache-spark ---- - -Spark jobs typically run on clusters of machines. A single machine hosts the "driver" application, -which constructs a graph of jobs - e.g., reading data from a source, filtering, transforming, and -joining records, and writing results to some sink- and manages execution of those jobs. Spark's -fundamental abstraction is the Resilient Distributed Dataset (RDD), which encapsulates distributed -reads and modifications of records. While RDDs can be used directly, it is far more common to work -with Spark Datasets or Dataframes, which is an API that adds explicit schemas for better performance -and the ability to interact with datasets using SQL. The Dataframe's declarative API enables Spark -to optimize jobs by analyzing and manipulating an abstract query plan prior to execution. - - -## Collecting Lineage in Spark -Collecting lineage requires hooking into Spark's `ListenerBus` in the driver application and -collecting and analyzing execution events as they happen. Both raw RDD and Dataframe jobs post events -to the listener bus during execution. These events expose the structure of the job, including the -optimized query plan, allowing the Spark integration to analyze the job for datasets consumed and -produced, including attributes about the storage, such as location in GCS or S3, table names in a -relational database or warehouse, such as Redshift or Bigquery, and schemas. In addition to dataset -and job lineage, Spark SQL jobs also report logical plans, which can be compared across job runs to -track important changes in query plans, which may affect the correctness or speed of a job. - -A single Spark application may execute multiple jobs. The Spark OpenLineage integration maps one -Spark job to a single OpenLineage Job. The application will be assigned a Run id at startup and each -job that executes will report the application's Run id as its parent job run. Thus, an application -that reads one or more source datasets, writes an intermediate dataset, then transforms that -intermediate dataset and writes a final output dataset will report three jobs- the parent application -job, the initial job that reads the sources and creates the intermediate dataset, and the final job -that consumes the intermediate dataset and produces the final output. As an image: -![image](./spark-job-creation.dot.png) - -## How to Use the Integration -Adding OpenLineage metadata collection to existing Spark jobs was designed to be straightforward -and unobtrusive to the application. The Spark integration works as either a `javaagent` or as a -`SparkListener`. - -### SparkListener -The `SparkListener` approach is very simple and covers most cases. The listener simply analyzes -events, as they are posted by the SparkContext, and extracts job and dataset metadata that are -exposed by the RDD and Dataframe dependency graphs. Most data sources, such as filesystem sources -(including S3 and GCS), JDBC backends, and warehouses such as Redshift and Bigquery can be analyzed -and reported in this way. - -#### spark-submit -The listener can be enabled by adding the following configuration to a `spark-submit` command: - -```bash -spark-submit --conf "spark.extraListeners=io.openlineage.spark.agent.OpenLineageSparkListener" \ - --packages "io.openlineage:openlineage-spark:0.2.+" \ - --conf "spark.openlineage.host=http://" \ - --conf "spark.openlineage.namespace=my_job_namespace" \ - --class com.mycompany.MySparkApp my_application.jar -``` - -Additional configuration can be set if applicable - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Configuration KeyDescriptionDefault
    spark.openlineage.parentJobNameThe job name of the parent job that triggered this Spark application
    spark.openlineage.parentRunIdThe RunId of the parent job Run that triggered this Spark application 
    spark.openlineage.apiKeyThe API Key used to authenticate with the OpenLineage server that collects events 
    spark.openlineage.versionThe API version of the OpenLineage specification1
    - -#### spark-defaults.conf -Alternatively, the same configuration parameters can be added to the `spark-defaults.conf` file on -cluster creation. Add the following key/value parameters to the `spark-defaults.conf` file: - -``` -spark.jars.packages io.openlineage:openlineage-spark:0.2.+ -spark.extraListeners io.openlineage.spark.agent.OpenLineageSparkListener -spark.openlineage.host http:// -spark.openlineage.namespace my_job_namespace -``` - -The optional keys defined above can also be added here. When the job is submitted, additional or -overriding configuration values can be supplied. E.g., the `spark.openlineage.host` and `spark.openlineage.namespace` -can be defined in the `spark-defaults.conf` file and the `spark.openlineage.parentRunId` and `spark.openlineage.parentJobName` -configuration can be supplied when the job is submitted by the parent job. - -### Javaagent -The Javaagent approach is the earliest approach to adding lineage events. It was aimed to support -instrumenting Spark code directly by manipulating bytecode at runtime. In the case of Dataframe or -RDD code that doesn't expose the underlying datasource directly, the javaagent approach will allow -injecting bytecode at runtime to expose the required information. This approach requires being able -to add the `openlineage-spark` jar on the driver host and adding the correct JVM startup parameters. This -may not be possible, e.g., on a serverless Spark platform, such as AWS Glue. - -#### spark-submit -The following configuration must be added to the `spark-submit` command when the job is submitted: - -```bash -spark-submit --conf spark.driver.extraJavaOptions=-javaagent:=http:///api/v1/namespaces//?api_key= -``` - -If a parent job run is triggering the Spark job run, the parent job's name and Run id can be included as such: - -```bash -spark-submit --conf spark.driver.extraJavaOptions=-javaagent:=http:///api/v1/namespaces//jobs//runs/?api_key= -``` - -### From Airflow -The same parameters passed to `spark-submit` can be supplied from Airflow and other schedulers. If -using the [openlineage-airflow](../apache-airflow/) integration, each task in the DAG has its own Run id -which can be connected to the Spark job run via the `spark.openlineage.parentRunId` parameter. For example, -here is an example of a `DataProcPySparkOperator` that submits a Pyspark application on Dataproc: - -```python -t1 = DataProcPySparkOperator( - task_id=job_name, - gcp_conn_id='google_cloud_default', - project_id='project_id', - cluster_name='cluster-name', - region='us-west1', - main='gs://bucket/your-prog.py', - job_name=job_name, - dataproc_pyspark_properties={ - "spark.extraListeners": "io.openlineage.spark.agent.OpenLineageSparkListener", - "spark.jars.packages": "io.openlineage:openlineage-spark:0.2.+", - "spark.openlineage.url": f"{openlineage_url}/api/v1/namespaces/{openlineage_namespace}/jobs/dump_orders_to_gcs/runs/{{{{task_run_id(run_id, task)}}}}?api_key={api_key}" - }, - dag=dag) -``` - -The same job can be submitted using the `javaagent` approach: -```python -t1 = DataProcPySparkOperator( - task_id=job_name, - gcp_conn_id='google_cloud_default', - project_id='project_id', - cluster_name='cluster-name', - region='us-west1', - main='gs://bucket/your-prog.py', - job_name=job_name, - dataproc_pyspark_properties={ - 'spark.driver.extraJavaOptions': - f"-javaagent:openlineage-spark-0.2.2.jar={openlineage_url}/api/v1/namespaces/{openlineage_namespace}/jobs/dump_orders_to_gcs/runs/{{{{task_run_id(run_id, task)}}}}?api_key={api_key}" - files="https://repo1.maven.org/maven2/io/openlineage/openlineage-spark/0.2.2/openlineage-spark-0.2.2.jar", - dag=dag) -``` diff --git a/src/pages/integration/apache-spark/spark-job-creation.dot b/src/pages/integration/apache-spark/spark-job-creation.dot deleted file mode 100644 index 958027a1b9..0000000000 --- a/src/pages/integration/apache-spark/spark-job-creation.dot +++ /dev/null @@ -1,22 +0,0 @@ -digraph Creation { - ranksep=1; - rankdir=LR; - newrank="true"; - subgraph cluster0{ - label="Spark Application" - labeljust=l - shape=folder - SourceData1[rank=1,fillcolor="#919aab",style=filled,shape=cylinder,label="Source Dataset 1"]; - SourceData2[rank=1,fillcolor="#919aab",style=filled,shape=cylinder,label="Source Dataset 2"]; - JobA1[fillcolor="#d1d1d1",shape="Mcircle",style=filled,label="Job A"]; - IntermediateData[fillcolor="#919aab",style=filled,shape=cylinder,label="Intermediate Dataset"]; - JobB[fillcolor="#d1d1d1",shape="Mcircle",style=filled,label="Job B"]; - FinalData[fillcolor="#919aab",style=filled,shape=cylinder,label="Final Dataset"]; - SourceData1 -> JobA1[label="consumes"]; - SourceData2 -> JobA1[label="consumes"]; - JobA1 -> IntermediateData [label="creates"]; - IntermediateData -> JobB [label="consumes"]; - JobB -> FinalData [label="creates"]; - } - -} diff --git a/src/pages/integration/apache-spark/spark-job-creation.dot.png b/src/pages/integration/apache-spark/spark-job-creation.dot.png deleted file mode 100644 index 87e66700549dca751dfe2c00bf048767e02570b3..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 35513 zcmd43Wn7f)7d487BT@>|tpWm4(#?pdNQ;z&bc2*MhzufK0@5NPAPn6pA}!6(Dc#Z_ zbvDoA^Z%Xq)A{gzIk*0BRG7G~eeJ#WT5I3_it-Qfa42xFu(0qRKax_$!n$+?9{)s~ zhp)Qc1!sR?>pyuYg>`!N>tl6#Bo-DO)?+D273YMNF(-9mwE?W(m5wF+5}!#a_0Roy zGseGb{b{g4DmCBzaS&HDkDR`oe&B8MALmP61nMgirIFniO!At*heY})9EcD-Bu)a0Y@niq}TUU>yHSXWX zAJcqB$^Jf;cyhU%>+j>&(fD=-e;;GrrJia0@3E#(bMU#pe<^YZqrC99Lj`NJxB}PxjI|oLzo3As{ApGS?pOhD7Dfj(ce+F}CmE}1s_9T1$ z$&{zRtDZM`bg;E^`b+wc_2LKP}_jB;^2=6xALXuFx_Yndt)j?4Xj0#e{Z1(I@j z(tqvg=?TC2u*NQ4Pfu@W@PALMX&yEzKu=$1$;V2J)Ak;ZlJ9*?%)m6`f`e;fGywqt zEx+|>vBdzqq;4&jA~SItv76hWn)O{FAy>@TXZ=rg(s}>em*N4s@{K&bdO~EONoR=& zJ8Sr(Xm)LxnvS-%k!m-7Ny7a6{47=UaJhZDYF2Uf;X-$6US6J2TXdqRTR*oFOVrwU zH6^{n#;*pscs}xA>E(9qvX@g`uyXj+1tNbA-;|XJczK;hv8pkkV69YLyeW`h1vM>< z3k4Y&=aRin@@17WRUU>=9V}(#GB7aA*ty^xk`WQz)BAogN~YLpeZ0B3ndSLYmZ;j3 zKg)5v7RdYe?d|RF_QID^n+a>a_{fNee)Mxv8XBF@&}V-SfkdE0U&H6ek+8hmJq>;4 z#g&!9$mY5_dN#J7uKlp2KlHic+ja6@)Im5j=X65|buI5)l(ZbHaP0ah32%;-wXL@| zQdWk5TIk2r%LRu&A=JW0M@NK6e}8{g)$F{Bw6wGnS!%hI{MKZ+ZmlusR})i95+a3zyM zl1gdl-ulG)NNKK*&wW|hpT~!LtfkRmVO?oYVtUgRV&1<$g18o;S^qs%e^D|)+-tn9 z?i_s)M9bc|o6XM;T!@sN<$-}+jREWypMTvCy4wWA=0EH z0X`isZxkKki8U1wQK4x!165O2;LKugI_&gqUB9<)8BjHUma<5rGwDB57;DToUX&DZ z{{1bYog!Eo0ssy{cp=0}n<4kjn>Q^6o30QsmX()lAPcPVnrvxllXGiNhPj>oY%j_( z-V+pzr9*6b?nBfxYrvLV#l_8D8~gW@VZAn9zhO81mZCoMS(Yj(hmMHnQJIfVJ%kcD zAz@fpm_)}fyK)Di>Zj@QGr6p4IiGtM2XeIUBN`eTbF?c-=-)>~M8wC(hlfkDPp_;5 z5mJbIiXfYtnwkotrkg^OMO^IWI}&9X3o9P&t_o96L+qlShCtWDvOxs8q2r|lMy?d9PoejzQS?M=_A|?`ct^K_T zuO?AaYU<#xna$6P9u+4WwOjIKVU|98_|RHtKG?KmXW%dOhOmH!Zn(bQr|!kOhF@{@ zf8Pq0BIQmp<;cj0*JcZoK*;ki5J!#+UFVKVlk*zdr;LIDxD(mQYLL^Y^h9grx$bMmYzKqEtMK)L5bW&E1sC%&hslQ$CzqghV{HHVc zz`aH~^({U04RAosTEb*ORk_`!HINr7 zFE9V#!GqY?ScN1Jr7TQ8`rzQ8JxTO%xY#24vVX2_?Kmvlrl7eUm07ipLI(>g>rK{3 z%v$HA|2}1Rf40Wc!!-DDf5JF8Fztcb6%PI~X(vZpomZ}0G3iW#rJRKfRBAQChwbA{ zSn+b|JLI%$NT?Ev*nL!2-8E>vAnvETLB`3%`C{Cn0$SprWd(YHh4?>%bj#R&_`? 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-datasources: Snowflake, Google BigQuery -github: https://github.com/OpenLineage/OpenLineage/tree/main/integration/dbt -blog: https://openlineage.io/blog/dbt-with-marquez/ -slug: integration/dbt ---- - -## What is dbt? - -dbt (data build tool) is a powerful transformation engine. It operates on data already within a warehouse, making it easy for data engineers to build complex pipelines from the comfort of their laptops. While it doesn’t perform extraction and loading of data, it’s extremely powerful at transformations. - -To learn more about dbt, visit the [documentation site](https://docs.getdbt.com) or run through the [getting started tutorial](https://docs.getdbt.com/tutorial/setting-up). - -## How does dbt work with OpenLineage? - -Fortunately, dbt already collects a lot of the data required to create and emit OpenLineage events. When it runs, it creates a `target/manifest.json` file containing information about jobs and the datasets they affect, and a `target/run_results.json` file containing information about the run-cycle. These files can be used to trace lineage and job performance. In addition, by using the `create catalog` command, a user can instruct dbt to create a `target/catalog.json` file containing information about dataset schemas. - -These files contain everything needed to trace lineage. However, the `target/manifest.json` and `target/run_results.json` files are only populated with comprehensive metadata after completion of a run-cycle. - -This integration is implemented as a wrapper script, `dbt-ol`, that calls `dbt` and, after the run has completed, collects information from the three json files and calls the OpenLineage API accordingly. For most users, enabling OpenLineage metadata collection can be accomplished by simply substituting `dbt-ol` for `dbt` when performing a run. - -## Preparing a dbt project for OpenLineage - -First, we need to install the integration: - -```bash -pip3 install openlineage-dbt -``` - -Next, we specify where we want dbt to send OpenLineage events by setting the `OPENLINEAGE_URL` environment variable. For example, to send OpenLineage events to a local instance of Marquez, use: - -```bash -OPENLINEAGE_URL=http://localhost:5000 -``` - -Finally, we can optionally specify a namespace where the lineage events will be stored. For example, to use the namespace "dev": - -```bash -OPENLINEAGE_NAMESPACE=dev -``` - -## Running dbt with OpenLineage - -To run your dbt project with OpenLineage collection, simply replace `dbt` with `dbt-ol`: - -```bash -dbt-ol run -``` - -The `dbt-ol` wrapper supports all of the standard `dbt` subcommands, and is safe to use as a substitutuon (i.e., in an alias). Once the run has completed, you will see output containing the number of events sent via the OpenLineage API: - -```bash -Completed successfully - -Done. PASS=2 WARN=0 ERROR=0 SKIP=0 TOTAL=2 -Emitted 4 openlineage events -``` - -## Where can I learn more? - -* Watch [a short demonstration of the integration in action](https://youtu.be/7caHXLDKacg) - -## Feedback - -What did you think of this guide? You can reach out to us on [slack](http://bit.ly/OpenLineageSlack) and leave us feedback! diff --git a/src/pages/integration/index.tsx b/src/pages/integration/index.tsx deleted file mode 100644 index bd35892c4c..0000000000 --- a/src/pages/integration/index.tsx +++ /dev/null @@ -1,63 +0,0 @@ -import React, { useEffect } from "react" -import Layout from '@theme/Layout' -import IntegrationItem from "../../components/item-integration" -import { getPageData } from "../../components/utils" - -export default function integrationList({ }: JSX.Element) { - const seoTitle = 'Integrations'; - const seoDescription = "Data lineage is the foundation for a new generation of powerful, context-aware data tools and best practices. OpenLineage enables consistent collection of lineage metadata, creating a deeper understanding of how data is produced and used."; - - const filesData = [ - require('./apache-airflow/index.mdx'), - require('./apache-spark/index.mdx'), - require('./dbt/index.mdx') - ]; - - const data = filesData.map(e => { - return getPageData(e) - }) - - useEffect(() => { - window.dispatchEvent(new CustomEvent('scroll')) - }, []) - - const integrationItems = data.map((item, i) => ( - - )) - - return ( - -

    - - ) -} \ No newline at end of file diff --git a/src/pages/resources/index.mdx b/src/pages/resources/index.mdx index 6feb88bc8d..3ee878b5b5 100644 --- a/src/pages/resources/index.mdx +++ b/src/pages/resources/index.mdx @@ -19,9 +19,14 @@ These resources have been gathered to help new users learn about OpenLineage, or ## Conference Talks +* [Cross-platform Data Lineage with OpenLineage](https://www.youtube.com/watch?v=pLBVGIPuwEo) - Julien Le Dem @ Berlin Buzzwords (2022) +* [Data Observability and Pipelines: OpenLineage and Marquez](https://mattturck.com/datakin/) - Matt Turck @ Data Driven NYC (2021) +* [Data Lineage and Observability with Marquez and OpenLineage](https://bigdatatechwarsaw.eu/edition-2021/) - Julien Le Dem @ Big Data Technology Warsaw Summit (2021) * [Data Lineage with Apache Airflow using OpenLineage](https://airflowsummit.org/sessions/2021/data-lineage-with-apache-airflow-using-openlineage/) - Julien Le Dem & Willy Lulciuc @ Airflow Summit (2021) * [Observability for data pipelines with OpenLineage](https://2021.berlinbuzzwords.de/session/observability-data-pipelines-openlineage) - Julien Le Dem @ Berlin Buzzwords (2021) * [Data Observability and Pipelines: OpenLineage and Marquez](https://www.youtube.com/watch?v=MoW-YGjHLgI) - Julien Le Dem @ Data Driven NYC (2021) +* [OpenLineage Lightning Talk](https://www.youtube.com/watch?v=anlV5Er_BpM) - Julien Le Dem @ MetaSpeak Metadata Day (2020) +* [Observability for Data Pipelines: OpenLineage Project Launch](https://www.coss.community/coss/ocs-2020-breakout-julien-le-dem-3eh4) - Julien Le Dem @ Open Core Summit (2020) ## Blog Posts diff --git a/static/apidocs/javadoc/allclasses-index.html b/static/apidocs/javadoc/allclasses-index.html index 9b733c9687..69f3089a0d 100644 --- a/static/apidocs/javadoc/allclasses-index.html +++ b/static/apidocs/javadoc/allclasses-index.html @@ -3,7 +3,7 @@ -All Classes (openlineage-java 0.21.0-SNAPSHOT API) +All Classes (openlineage-java 0.22.0-SNAPSHOT API) @@ -21,7 +21,7 @@
  • {data.title}

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