Revision as of 18:58, 25 November 2025

ETL

ETL Flow

1: User pushes ETL code into ETL Code Repo
2: Airflow Scheduler trigger DAG (DAG is generated based on metadata)
- The ETL job is a task within an airflow DAG
3: ETL executor pulls code from ETL Code Repo into loacl disk
4: ETL executor uses dbt library to submit job to Apache Spark via JDBC interface (e.g. via Thrift Server)
5: Thrift Server take the SQL and pass it to Apache Spark to execute

Using MPP Engine

BI Tool to access Gold Tier data and Platnium Tier data via JDBC interface exposed by a MPP engine
- Why? A MPP Engine provide better interactive SQL query speed than Spark Thrift Server

Using RDBMS

Gold Tier data and Platnium Tier data are replicated to RDBMS, such as Oracle DB
BI Tool to access Gold Tier data and Platnium Tier data via JDBC interface exposed by RDBMS
This pattern does not work for very large datalake since Gold Tier and Platnium Tier are too large to be replicated to RDBMS

@@ Line 77: / Line 77: @@
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-* BI Tool to access Gold Tier data and Platnium Tier data via JDBC interface exposed by a MPP engine
+* Gold Tier data and Platnium Tier data are replicated to RDBMS, such as Oracle DB
-** Why? A MPP Engine provide better interactive SQL query speed than Spark Thrift Server
+* BI Tool to access Gold Tier data and Platnium Tier data via JDBC interface exposed by RDBMS
+* This pattern does not work for very large datalake since Gold Tier and Platnium Tier are too large to be replicated to RDBMS
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