Apache Spark RDD Transformations Pipeline

RDDs (Resilient Distributed Datasets) are Spark’s fundamental abstraction — an immutable, partitioned collection of records that can be operated on in parallel.

Transformations like map, filter, and flatMap are lazy: they build a DAG of dependencies without executing until an action (like reduce or collect) triggers computation.

This pipeline model enables Spark to optimize execution by fusing transformations, minimizing data shuffles, and recovering from failures using lineage information.