Spark1👉Difference between Transformation & Action #spark #python #programming #learning #jeenu

Key Differences:

💎Execution Trigger:

👉Transformations are lazily evaluated, and Spark waits until an action is called to execute them. They help build the RDD lineage.
👉Actions trigger the actual computation in Spark by evaluating the transformations and returning results to the driver program or writing data to external storage.

💎Return Value:

👉Transformations return new RDDs representing the transformed data but do not compute results immediately.
👉Actions return non-RDD values such as integers, lists, or write data to external storage (like files or databases).

💎Optimization Opportunities:

👉Spark optimizes transformations by applying optimizations like pipelining, lazy evaluation, and narrow transformations to reduce shuffling and improve performance.
👉Actions trigger the execution of transformations and provide opportunities for Spark to optimize the execution plan based on the actual computations required.

Understanding when to apply transformations and actions correctly is crucial for optimizing Spark jobs, reducing unnecessary computations, and improving overall performance.

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