In Apache Spark, efficient data management is essential for maximizing performance in distributed computing. Partitioning, repartitioning, and coalescing actively govern how data organizes and distributes across the cluster. Partitioning involves dividing datasets into smaller chunks, enabling parallel processing and optimizing operations. Repartitioning allows for the redistribution of data across partitions, adjusting the balance for more […]