Introduction As datasets grow, processing them efficiently on a single machine can become challenging due to limitations in CPU capacity, memory, and storage throughput. Apache Spark addresses these challenges by providing a distributed data processing engine that can divide workloads into partitions and execute tasks in parallel across CPU cores and multiple machines. However, Spark is not simply about adding more machines. Understanding how its components work together—Drivers, Executors…