suresh Lazy evaluation in Apache Spark refers to the optimization technique where transformations on a dataset are not executed immediately, but are instead deferred until an action is performed. This allows Spark to optimize the execution plan by combining multiple transformations and evaluating them in a single job.
Lazy evaluation is used in Apache Spark to improve performance and optimize resource utilization. By delaying the execution of transformations, Spark can avoid unnecessary computations and only perform the required operations when the final result is needed. This results in faster processing times and more efficient use of memory and disk resources.
Overall, lazy evaluation in Apache Spark helps to minimize unnecessary overhead and maximize the efficiency of data processing operations.
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