Which Spark component is responsible for executing tasks on a worker node?

The component responsible for executing tasks on a worker node in Apache Spark is the executor. Executors run on the worker nodes of the cluster and are tasked with executing the stages of a Spark application as directed by the driver. They are essential for parallel processing as they perform the computations and manage the storage for their data. Each executor acts as a separate Java process and can run multiple tasks concurrently, depending on the resources available and the configuration of the Spark application.

The driver is responsible for managing the execution of the application, including the orchestration of task scheduling, but does not execute tasks itself. Tasks are the individual units of work sent to executors; however, they do not execute anything independently. The scheduler, on the other hand, is a component that determines how tasks are distributed and scheduled across executors, but again, it does not perform the execution of tasks. Hence, the executor is the correct choice since it is the actual entity that performs the work on the data.