Spark Programming in Python for Beginners with Apache Spark 3 - Spark Distributed Processing Model - How Your Program Ru

This video explains how Apache Spark executes applications on a distributed cluster using a master-slave architecture. Each Spark application creates a driver (master) and executors (slaves) to process tasks. The Spark engine requests containers from the cluster manager to run these processes. The video uses examples to illustrate how multiple applications run independently, each with its own driver and executors, highlighting Spark's capability as a distributed computing platform.

What happens when multiple applications are submitted to Spark?

In what way does Spark ensure that applications run independently on the cluster?