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Dynamic PySpark ETL with MySQL and Docker | Metadata-Driven ETL Job Runner
9:06
YouTubeNihau zhang
Dynamic PySpark ETL with MySQL and Docker | Metadata-Driven ETL Job Runner
Learn how to build a dynamic ETL pipeline using PySpark and a Docker-based MySQL database. This POC shows how to create a metadata-driven job runner that executes ETL tasks (CSV or SQL source) based on control table entries. We cover Spark setup, environment variables, JDBC integration, and error fixes. 🔧 Tech stack: PySpark, MySQL, Docker ...
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SQLAlchemy Turns Python Objects Into Database Entries
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206.1K views26 Oct 2022
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