Skip to content

palandlom/data-mart-filler

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Data-mart-filler

General description

All phases of ETL-proccess to form/update data mart are performed by the application filler which is packed in jar-file.

filler can be executed from ./app directory in the following modes:

  • all - multithread downloadind of the news from RSS-resourses to ./app/newsFiles/X_news file - command java -cp "./*" main.Main all
  • prep - categorize news from the new files appeared in ./app/newsFiles/ forder, insert news into filler-db tables news, uncategorized_news and add new "unmapped" categories to filler-db.category_mapping table as non-mapped ones file - command java -cp "./*" main.Main prep
  • uncat - try to categorize uncategorized news from filler-db.uncategorized_news by mapping from the filler-db.category_mapping table file - command java -cp "./*" main.Main uncat
  • anl - analyse filler-db.news table with recreation data-mart tables: category_stat, category_to_source_stat, days_to_category_stat - command java -cp "./*" main.Main anl

filler-jar should be placed in ./app directory with required spark-jars. ./app directory will be bind to airflow-worker-container and filler-jar will be called by airflow-DAG update-news-datamart. The Airflow-DAG update-news-datamart contains tasks for each of noted filler-modes. The DAG is started every day on 00:30.

The results of each run of the DAG:

  • new file with news in ./app/newsFiles/
  • new deduplicated and categorised news in table news
  • new deduplicated, uncategorised news in table uncategorized_news
  • created/updated tables category_stat, category_to_source_stat, days_to_category_stat

To access the filler-db use following account data:

host 127.0.0.1
port 5432
user postgres
pass pass
dbName news

Other docs (presentation, schemes etc.) can be reseived by data-mart-filler-files

Deploy

Get spark jars

Sparks jars from ./jars directory of (https://dlcdn.apache.org/spark/spark-3.2.3/spark-3.2.3-bin-hadoop3.2-scala2.13.tgz) should be placed in ./app folder. You can execute ./getSpark.sh script for this, it will download and extract jars to ./app

Build filler-jar

Filler source code (scala sbt-project) is in ./filler folder. Current version of filler can be downloaded to ./app from - link or can be build by:

  cd ./filler
  sbt assebly

Jar will be in /filler/target/scala-2.13/filler_2.13-0.1.0-SNAPSHOT.jar copy it to ./app:

  cd ..
  cp ./filler/target/scala-2.13/filler-assembly-0.1.0-SNAPSHOT.jar ./app

Run air-flow containders with filler

Create .env:

echo -e "AIRFLOW_UID=$(id -u)" > .env

In first time run airflow-init scenario:

docker compose up airflow-init

Then start airflow normally:

docker compose up

Airflow-DAG update-news-datamart can be started from DAGs list - (http://127.0.0.1:8080/home) To access airflow web-ui use user/pass: airflow/airflow

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published