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What is Executor Memory in a Spark application?

a. The memory allocated to a Spark driver
b. The memory allocated to a Spark worker node
c. The memory allocated to each Spark task
d. The total memory available in the cluster

User Jiddo
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1 Answer

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Final answer:

Executor Memory in a Spark application refers to the amount of memory allocated to each executor within a Spark cluster, which is responsible for running tasks and storing data.

Step-by-step explanation:

Executor Memory in a Spark application refers to the memory allocated to each executor in a Spark cluster. An executor is a process launched for an application on a worker node, which runs tasks and keeps data in memory or disk storage across them. Each executor has a defined amount of memory which it uses to run tasks. This memory is not to be confused with the memory allocated to the Spark driver, which coordinates the execution of tasks, or the total memory available in the cluster, which encompasses all resources across all nodes. Also, it is distinct from the memory allocated to each Spark task, as multiple tasks may be run within a single executor.

User Alexandre Catalano
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