There are few things in life that are worse then cracking open some serious PySpark pipeline code, and then realizing there isn’t a single function written to encapsulate logic … wondering if some change you are about to make will bring down the whole pipeline. When you are new to a codebase you don’t know what you don’t know, you don’t have any backstory and you are usually flying by the seat of your pants in the beginning. When you have no unit tests, usually the only other way to test changes on a Spark pipeline are to run it …. which is sometimes easier said then done in a development environment. The first line of defence should be unit testing the entire PySpark pipeline.
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