A PySpark job reads a large Delta table that was written as many small files. The read stage schedules over 4,000 tasks that each finish in a fraction of a second, and most of the stage time goes to scheduling overhead. Which setting controls how much data each read task processes, so the small files can be packed into fewer tasks?
Reveal answer
Correct answer: `spark.sql.files.maxPartitionBytes`, which sets how many bytes are packed into a single read partition (128 MB by default)
Reference: https://docs.databricks.com/aws/en/optimizations/spark-ui-guide/
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Official Answer (D): `spark.sql.files.maxPartitionBytes`, which sets how many bytes are packed into a single read partition (128 MB by default)
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