概要
This skill provides specialized patterns for tuning Apache Spark performance across large-scale data pipelines. It encompasses critical strategies such as optimal partitioning, sophisticated join optimizations including broadcast and salt joins, memory and executor configuration, and shuffle reduction. By implementing these production-ready patterns, developers can significantly reduce job latency, prevent out-of-memory errors, and minimize cloud infrastructure costs for massive big data workloads.
