How to Use AWS Glue PySpark for Table Updates and File Transformation

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When working with PySpark and AWS Glue to update your data tables and create transformed files, it’s important to do so without generating duplicate files. Here are two straightforward methods to get this done efficiently.

First, you can use the getSink function with the enableUpdateCatalog setting turned on. This allows you to write your data and update the data catalog at the same time. You just need to define your sink, specify the path, set the desired format (like Parquet), and include your catalog database and table names. This method ensures your table gets updated directly when new data is processed.

The second method involves configuring job bookmarks properly. Job bookmarks help keep track of what data has already been processed, preventing the same files from being written multiple times. To do this, you should initialize your Glue job with bookmarking enabled, read your data with the create_dynamic_frame method, and assign a unique transformation context for each step. When writing the data back to S3, maintain this unique context and ensure your job runs with a maximum of one concurrent run. Don’t change the transformation context between runs, or you might lose the bookmark’s effectiveness.

Here are some tips to keep in mind:

– Use the DynamicFrame API for reading and writing data, not Spark DataFrames or SQL.
– Assign a unique transformation context during each step.
– Keep the transformation context the same across multiple job runs.
– Limit your Glue job to run only one instance at a time to maintain bookmark integrity.

If you notice duplicate files even after following these steps, double-check your job bookmark settings. Proper configuration of job bookmarks is key to avoiding repeated data processing.

By combining these approaches, you can handle both catalog updates and data transformations in a single job without creating duplicate files. This not only saves time but also keeps your data organized and consistent.

For more detailed guidance, you can refer to the official AWS Glue documentation on updating tables from jobs and troubleshooting bookmarks.