Merge branch 'current' into methods

website/dbt-versions.js

@@ -20,6 +20,7 @@ exports.versions = [
   },
   {
     version: "1.9",
+    customDisplay: "1.9 (Compatible)",
     EOLDate: "2025-12-08",
   },
   {

website/docs/docs/build/dbt-tips.md

@@ -40,7 +40,7 @@ Leverage these dbt packages to streamline your workflow:
 - Set `vars` in your `dbt_project.yml` to define global defaults for certain conditions, which you can then override using the `--vars` flag in your commands.
 - Use [for loops](/guides/using-jinja?step=3) in Jinja to <Term id="dry">DRY</Term> up repetitive logic, such as selecting a series of columns that all require the same transformations and naming patterns to be applied.
 - Instead of relying on post-hooks, use the [grants config](/reference/resource-configs/grants) to apply permission grants in the warehouse resiliently.
-- Define [source-freshness](/docs/build/sources#snapshotting-source-data-freshness) thresholds on your sources to avoid running transformations on data that has already been processed.
+- Define [source-freshness](/docs/build/sources#source-data-freshness) thresholds on your sources to avoid running transformations on data that has already been processed.
 - Use the `+` operator on the left of a model `dbt build --select +model_name` to run a model and all of its upstream dependencies. Use the `+` operator on the right of the model `dbt build --select model_name+` to run a model and everything downstream that depends on it.
 - Use `dir_name` to run all models in a package or directory.
 - Use the `@` operator on the left of a model in a non-state-aware CI setup to test it. This operator runs all of a selection’s parents and children, and also runs the parents of its children, which in a fresh CI schema will likely not exist yet.

website/docs/docs/build/materializations.md

@@ -18,7 +18,11 @@ You can also configure [custom materializations](/guides/create-new-materializat
 
 
 ## Configuring materializations
-By default, dbt models are materialized as "views". Models can be configured with a different materialization by supplying the `materialized` configuration parameter as shown below.
+By default, dbt models are materialized as "views". Models can be configured with a different materialization by supplying the [`materialized` configuration](/reference/resource-configs/materialized) parameter as shown in the following tabs.
+
+<Tabs>
+
+<TabItem value="Project file">
 
 <File name='dbt_project.yml'>
 
@@ -49,6 +53,10 @@ models:
 
 </File>
 
+</TabItem>
+
+<TabItem value="Model file">
+
 Alternatively, materializations can be configured directly inside of the model sql files. This can be useful if you are also setting [Performance Optimization] configs for specific models (for example, [Redshift specific configurations](/reference/resource-configs/redshift-configs) or [BigQuery specific configurations](/reference/resource-configs/bigquery-configs)).
 
 <File name='models/events/stg_event_log.sql'>
@@ -63,6 +71,29 @@ from ...
 
 </File>
 
+</TabItem>
+
+<TabItem value="Property file">
+
+Materializations can also be configured in the model's `properties.yml` file.  The following example shows the `table` materialization type. For a complete list of materialization types, refer to [materializations](/docs/build/materializations#materializations).
+
+<File name='models/properties.yml'>
+
+```yaml
+version: 2
+
+models:
+  - name: events
+    config:
+      materialized: table
+```
+
+</File>
+
+</TabItem>
+
+</Tabs>
+
 ## Materializations
 
 

website/docs/docs/build/sources.md

@@ -130,11 +130,11 @@ You can find more details on the available properties for sources in the [refere
 <FAQ path="Tests/testing-sources" />
 <FAQ path="Runs/running-models-downstream-of-source" />
 
-## Snapshotting source data freshness
-With a couple of extra configs, dbt can optionally snapshot the "freshness" of the data in your source tables. This is useful for understanding if your data pipelines are in a healthy state, and is a critical component of defining SLAs for your warehouse.
+## Source data freshness
+With a couple of extra configs, dbt can optionally capture the "freshness" of the data in your source tables. This is useful for understanding if your data pipelines are in a healthy state, and is a critical component of defining SLAs for your warehouse.
 
 ### Declaring source freshness
-To configure sources to snapshot freshness information, add a `freshness` block to your source and `loaded_at_field` to your table declaration:
+To configure source freshness information, add a `freshness` block to your source and `loaded_at_field` to your table declaration:
 
 <File name='models/<filename>.yml'>
 
@@ -164,14 +164,14 @@ sources:
 
 </File>
 
-In the `freshness` block, one or both of `warn_after` and `error_after` can be provided. If neither is provided, then dbt will not calculate freshness snapshots for the tables in this source.
+In the `freshness` block, one or both of `warn_after` and `error_after` can be provided. If neither is provided, then dbt will not calculate freshness for the tables in this source.
 
 Additionally, the `loaded_at_field` is required to calculate freshness for a table. If a `loaded_at_field` is not provided, then dbt will not calculate freshness for the table.
 
 These configs are applied hierarchically, so `freshness` and `loaded_at_field` values specified for a `source` will flow through to all of the `tables` defined in that source. This is useful when all of the tables in a source have the same `loaded_at_field`, as the config can just be specified once in the top-level source definition.
 
 ### Checking source freshness
-To snapshot freshness information for your sources, use the `dbt source freshness` command ([reference docs](/reference/commands/source)):
+To obtain freshness information for your sources, use the `dbt source freshness` command ([reference docs](/reference/commands/source)):
 
 ```
 $ dbt source freshness
@@ -182,7 +182,7 @@ Behind the scenes, dbt uses the freshness properties to construct a `select` que
 ```sql
 select
   max(_etl_loaded_at) as max_loaded_at,
-  convert_timezone('UTC', current_timestamp()) as snapshotted_at
+  convert_timezone('UTC', current_timestamp()) as calculated_at
 from raw.jaffle_shop.orders
 
 ```
@@ -198,7 +198,7 @@ Some databases can have tables where a filter over certain columns are required,
 ```sql
 select
   max(_etl_loaded_at) as max_loaded_at,
-  convert_timezone('UTC', current_timestamp()) as snapshotted_at
+  convert_timezone('UTC', current_timestamp()) as calculated_at
 from raw.jaffle_shop.orders
 where _etl_loaded_at >= date_sub(current_date(), interval 1 day)
 ```

website/docs/docs/dbt-cloud-apis/discovery-use-cases-and-examples.md

@@ -495,7 +495,7 @@ Graph example:
 
 ### Are my data sources fresh?
 
-Checking [source freshness](/docs/build/sources#snapshotting-source-data-freshness) allows you to ensure that sources loaded and used in your dbt project are compliant with expectations. The API provides the latest metadata about source loading and information about the freshness check criteria.
+Checking [source freshness](/docs/build/sources#source-data-freshness) allows you to ensure that sources loaded and used in your dbt project are compliant with expectations. The API provides the latest metadata about source loading and information about the freshness check criteria.
 
 <Lightbox src="/img/docs/dbt-cloud/discovery-api/source-freshness-page.png" width="75%" title="Source freshness page in dbt Cloud"/>
 

website/docs/docs/dbt-versions/cloud-release-tracks.md

@@ -14,16 +14,18 @@ By moving your environments and jobs to release tracks you can get all the funct
 
 ## Which release tracks are available?
 
-- **"Latest"** (available to all plans, formerly called "Versionless"): Provides a continuous release of the latest functionality in dbt Cloud. Includes early access to new features of the dbt framework before they're available in open source releases of dbt Core.
-- <Lifecycle status="coming soon"/> **"Compatible"** (available to Team + Enterprise): Provides a monthly release aligned with the most recent open source versions of dbt Core and adapters, plus functionality exclusively available in dbt Cloud.
-- <Lifecycle status="coming soon"/> **"Extended"** (available to Enterprise): Provides a delayed release of the previous month's "Compatible" release.
+| Release track | Description | Plan availability | API value |
+| ------------- | ----------- | ----------------- | --------- |
+| **Latest** <br /> <Lifecycle status="GA"/> |  Formerly called "Versionless", provides a continuous release of the latest functionality in dbt Cloud. Includes early access to new features of the dbt framework before they're available in open source releases of dbt Core. | All plans | `latest` (or `versionless`) |
+| **Compatible** <Lifecycle status="preview"/>  | Provides a monthly release aligned with the most recent open source versions of dbt Core and adapters, plus functionality exclusively available in dbt Cloud. |  Team + Enterprise | `compatible` |
+| **Extended** <Lifecycle status="preview"/> | The previous month's "Compatible" release. | Enterprise | `extended` |
 
-The first "Compatible" release will be in December 2024, after the final release of dbt Core v1.9.0. For December 2024 only, the "Extended" release is the same as "Compatible." Starting in January 2025, "Extended" will be one month behind "Compatible."
+The first "Compatible" release was on December 12, 2024, after the final release of dbt Core v1.9.0. For December 2024 only, the "Extended" release is the same as "Compatible." Starting in January 2025, "Extended" will be one month behind "Compatible."
 
 To configure an environment in the [dbt Cloud Admin API](/docs/dbt-cloud-apis/admin-cloud-api) or [Terraform](https://registry.terraform.io/providers/dbt-labs/dbtcloud/latest) to use a release track, set `dbt_version` to the release track name:
-- `latest` (formerly called `versionless`; the old name is still supported)
-- `compatible` (available to Team + Enterprise)
-- `extended` (available to Enterprise)
+- `latest` (or `versionless`, the old name is still supported)
+- `compatible`
+- `extended`
 
 ## Which release track should I choose?
 
@@ -69,17 +71,15 @@ To learn more about how dbt Labs deploys stable dbt upgrades in a safe manner to
 
 If you're running dbt version 1.6 or older, please know that your version of dbt Core has reached [end-of-life (EOL)](/docs/dbt-versions/core#eol-version-support) and is no longer supported. We strongly recommend that you update to a newer version as soon as reasonably possible.
 
-dbt Labs has extended the critical support period of dbt Core v1.7 for dbt Cloud Enterprise customers to January 31, 2024. At that point, we will be asking all customers to select a Release Track for receiving ongoing updates to dbt in dbt Cloud.
+dbt Labs has extended the critical support period of dbt Core v1.7 for dbt Cloud Enterprise customers to March 2025. At that point, we will be encouraging all customers to select a Release Track for ongoing updates in dbt Cloud.
 
 <Expandable alt_header="I'm using an older version of dbt in dbt Cloud. What should I do? What happens if I do nothing?" >
 
 If you're running dbt version v1.6 or older, please know that your version of dbt Core has reached [end-of-life (EOL)](/docs/dbt-versions/core#eol-version-support) and is no longer supported. We strongly recommend that you update to a newer version as soon as reasonably possible.
 
 dbt Labs has extended the "Critical Support" period of dbt Core v1.7 for dbt Cloud Enterprise customers while we work through the migration with those customers to Release Tracks. In the meantime, this means that v1.7 will continue to be accessible in dbt Cloud for Enteprise customers, jobs and environments on v1.7 for those customers will not be automatically migrated to "Latest," and dbt Labs will continue to fix critical bugs and security issues.
 
-dbt Cloud accounts on the Developer and Team plans will be migrated to the "Latest" release track after November 1, 2024. If you know that your project will not be compatible with the upgrade, for one of the reasons described here, or a different reason in your own testing, you should [contact dbt Cloud support](https://docs.getdbt.com/docs/dbt-support#dbt-cloud-support) to request an extension.
-
-If your account has been migrated to the "Latest" release track, and you are seeing net-new failures in your scheduled dbt jobs, you should also [contact dbt Cloud support](https://docs.getdbt.com/docs/dbt-support#dbt-cloud-support) to request an extension.
+Starting in October 2024, dbt Cloud accounts on the Developer and Team plans have been migrated to release tracks from older dbt Core versions. If your account was migrated to the "Latest" release track and you notice new failures in scheduled jobs, please [contact dbt Cloud support](https://docs.getdbt.com/docs/dbt-support#dbt-cloud-support) to report the problem or request an extension.
 
 </Expandable>
 
@@ -134,8 +134,8 @@ In 2024, we've changed the way that new dbt functionality is made available for
 
 Opting into a release cadence with automated upgrades is required for accessing any new functionality that we've released in 2024, and going forward.
 
-We continue to release new minor versions of dbt Core (OSS), including v1.9 which will be available later this year. When we do, it will be a subset of the functionality that's already available to dbt Cloud customers, and always after the functionality has been available in dbt Cloud.
+We continue to release new minor versions of dbt Core (OSS). We most recently released dbt Core v1.9 on December 9, 2024. These releases always include a subset of the functionality that's already available to dbt Cloud customers, and always after the functionality has been available in dbt Cloud.
 
 </Expandable>
 
-If you have comments or concerns, we’re happy to help. If you’re an existing dbt Cloud customer, you may reach out to your account team or [contact support](/docs/dbt-support#dbt-cloud-support).
+If you have comments or concerns, we’re happy to help. If you’re an existing dbt Cloud customer, you may reach out to your account team or [contact support](/docs/dbt-support#dbt-cloud-support).

website/docs/docs/dbt-versions/compatible-track-changelog.md

@@ -4,9 +4,9 @@ sidebar_label: "Compatible Track Changelog"
 description: "The Compatible release track updates once per month, and it includes up-to-date open source versions as of the monthly release."
 ---
 
-:::info Coming soon
+:::info Preview
 
-The "Compatible" and "Extended" release tracks will be available in Preview to eligible dbt Cloud accounts in December 2024.
+The "Compatible" and "Extended" [release tracks](/docs/dbt-versions/cloud-release-tracks) are available in Preview. Access will be rolling out to dbt Cloud accounts on eligible plans during the week of December 16-20, 2024.
 
 :::
 
@@ -20,8 +20,42 @@ For more information, see [release tracks](/docs/dbt-versions/cloud-release-trac
 
 ## December 2024
 
-Planned release: December 11-13
-
-This release will include functionality from `dbt-core==1.9.0` and the most recent versions of all adapters supported in dbt Cloud. After the Compatible release is cut, we will update with:
-- exact versions of open source dbt packages
-- changelog notes concerning functionality specific to dbt Cloud
+Release date: December 12, 2024
+
+This release includes functionality from the following versions of dbt Core OSS:
+```
+dbt-core==1.9.0
+
+# shared interfaces
+dbt-adapters==1.10.4
+dbt-common==1.14.0
+dbt-semantic-interfaces==0.7.4
+
+# adapters
+dbt-athena==1.9.0
+dbt-bigquery==1.9.0
+dbt-databricks==1.9.0
+dbt-fabric==1.8.8
+dbt-postgres==1.9.0
+dbt-redshift==1.9.0
+dbt-snowflake==1.9.0
+dbt-spark==1.9.0
+dbt-synapse==1.8.2
+dbt-teradata==1.8.2
+dbt-trino==1.8.5
+```
+
+Changelogs:
+- [dbt-core 1.9.0](https://github.com/dbt-labs/dbt-core/blob/1.9.latest/CHANGELOG.md#dbt-core-190---december-09-2024)
+- [dbt-adapters 1.10.4](https://github.com/dbt-labs/dbt-adapters/blob/main/CHANGELOG.md#dbt-adapters-1104---november-11-2024)
+- [dbt-common 1.14.0](https://github.com/dbt-labs/dbt-common/blob/main/CHANGELOG.md)
+- [dbt-bigquery 1.9.0](https://github.com/dbt-labs/dbt-bigquery/blob/1.9.latest/CHANGELOG.md#dbt-bigquery-190---december-09-2024)
+- [dbt-databricks 1.9.0](https://github.com/databricks/dbt-databricks/blob/main/CHANGELOG.md#dbt-databricks-190-december-9-2024)
+- [dbt-fabric 1.8.8](https://github.com/microsoft/dbt-fabric/blob/v1.8.latest/CHANGELOG.md)
+- [dbt-postgres 1.9.0](https://github.com/dbt-labs/dbt-postgres/blob/main/CHANGELOG.md#dbt-postgres-190---december-09-2024)
+- [dbt-redshift 1.9.0](https://github.com/dbt-labs/dbt-redshift/blob/1.9.latest/CHANGELOG.md#dbt-redshift-190---december-09-2024)
+- [dbt-snowflake 1.9.0](https://github.com/dbt-labs/dbt-snowflake/blob/1.9.latest/CHANGELOG.md#dbt-snowflake-190---december-09-2024)
+- [dbt-spark 1.9.0](https://github.com/dbt-labs/dbt-spark/blob/1.9.latest/CHANGELOG.md#dbt-spark-190---december-10-2024)
+- [dbt-synapse 1.8.2](https://github.com/microsoft/dbt-synapse/blob/v1.8.latest/CHANGELOG.md)
+- [dbt-teradata 1.8.2](https://github.com/Teradata/dbt-teradata/releases/tag/v1.8.2)
+- [dbt-trino 1.8.5](https://github.com/starburstdata/dbt-trino/blob/master/CHANGELOG.md#dbt-trino-185---december-11-2024)

website/docs/docs/deploy/artifacts.md

@@ -4,7 +4,7 @@ id: "artifacts"
 description: "Use artifacts to power your automated docs site and source freshness data." 
 ---
 
-When running dbt jobs, dbt Cloud generates and saves *artifacts*. You can use these artifacts, like `manifest.json`, `catalog.json`, and `sources.json` to power different aspects of dbt Cloud, namely: [dbt Explorer](/docs/collaborate/explore-projects), [dbt Docs](/docs/collaborate/build-and-view-your-docs#dbt-docs), and [source freshness reporting](/docs/build/sources#snapshotting-source-data-freshness).
+When running dbt jobs, dbt Cloud generates and saves *artifacts*. You can use these artifacts, like `manifest.json`, `catalog.json`, and `sources.json` to power different aspects of dbt Cloud, namely: [dbt Explorer](/docs/collaborate/explore-projects), [dbt Docs](/docs/collaborate/build-and-view-your-docs#dbt-docs), and [source freshness reporting](/docs/build/sources#source-data-freshness).
 
 ## Create dbt Cloud Artifacts
 

website/docs/docs/deploy/source-freshness.md

@@ -4,7 +4,7 @@ id: "source-freshness"
 description: "Validate that data freshness meets expectations and alert if stale."
 ---
 
-dbt Cloud provides a helpful interface around dbt's [source data freshness](/docs/build/sources#snapshotting-source-data-freshness) calculations. When a dbt Cloud job is configured to snapshot source data freshness, dbt Cloud will render a user interface showing you the state of the most recent snapshot. This interface is intended to help you determine if your source data freshness is meeting the service level agreement (SLA) that you've defined for your organization.
+dbt Cloud provides a helpful interface around dbt's [source data freshness](/docs/build/sources#source-data-freshness) calculations. When a dbt Cloud job is configured to snapshot source data freshness, dbt Cloud will render a user interface showing you the state of the most recent snapshot. This interface is intended to help you determine if your source data freshness is meeting the service level agreement (SLA) that you've defined for your organization.
 
 <Lightbox src="/img/docs/dbt-cloud/using-dbt-cloud/data-sources-next.png" title="Data Sources in dbt Cloud"/>
 
@@ -17,7 +17,7 @@ dbt Cloud provides a helpful interface around dbt's [source data freshness](/doc
 
 <Lightbox src="/img/docs/dbt-cloud/select-source-freshness.png" title="Selecting source freshness"/>
 
-To enable source freshness snapshots, firstly make sure to configure your sources to [snapshot freshness information](/docs/build/sources#snapshotting-source-data-freshness). You can add source freshness to the list of commands in the job run steps or enable the checkbox. However, you can expect different outcomes when you configure a job by selecting the **Run source freshness** checkbox compared to adding the command to the run steps.
+To enable source freshness snapshots, firstly make sure to configure your sources to [snapshot freshness information](/docs/build/sources#source-data-freshness). You can add source freshness to the list of commands in the job run steps or enable the checkbox. However, you can expect different outcomes when you configure a job by selecting the **Run source freshness** checkbox compared to adding the command to the run steps.
 
 Review the following options and outcomes: