Spark Checkpointing: Proper Usage and Differences from Caching
Checkpointing materializes critical intermediate results to a fault-toleratn store and cuts off lineage, preventing expensive re-computation across deep DAGs when failures occur. Caching (or persisting) keeps data in memory/disk for faster reuse but retains dependencies, so data loss may still trigg...