What is an Executor in Spark, and what is its role?

In Spark, an Executor is a worker process running on a cluster node responsible for executing tasks in Spark applications. The main role of an Executor is to perform tasks including loading, transforming, computing, and storing data. Each Executor is allocated a certain amount of memory and CPU resources for executing tasks, and can cache data to improve performance. Tasks in a Spark application are distributed to Executors for parallel execution, achieving distributed computing. The number and resource configuration of Executors can be adjusted based on cluster size and application requirements to enhance performance and resource utilization.