optimizing-pyspark-jobs

Optimize slow or failing PySpark and Spark SQL jobs — partitioning and repartitioning, data skew, shuffles, broadcast joins, caching, Adaptive Query Execution, and avoiding driver collects and Python UDFs. Use when a Spark job is slow, spills, OOMs, has skewed tasks, runs a huge shuffle, or a stage hangs on a few straggler tasks.