Stage-Level Job Pipelining in Apache Spark: A Deep Dive

How we improved TracksETL throughput by understanding Spark s execution model Introduction Back in 2018, we migrated TracksETL (one of the largest ETL job) from Hive to Spark to handle our exploding event volumes. At that time, we processed around 2.28 billion events monthly. Fast forward to today, and we re processing over 15 billion events — Continue reading "Stage-Level Job Pipelining in Apache…