Spark Programming in Python for Beginners with Apache Spark 3 - Working with Spark Submit - Demo

This lecture provides a demonstration of using Spark submit with YARN cluster mode. It covers the basic options available in Spark submit, such as master, deploy mode, and memory settings. The lecture also explains how to create and submit Spark applications, using a demo application to compute the approximation of π. Finally, it discusses how to monitor the application status using the Spark history server.

What is the primary use of the YARN cluster mode in Spark?

• For developing Spark applications

• For debugging Spark applications

• For executing Spark applications in production

• For testing Spark applications locally

Which of the following is NOT a basic option available in Spark submit?

• Master

• Driver memory

• Deploy mode

• Network bandwidth

Before submitting a Spark application, what must be done first?

• Download the Spark binaries

• Configure the network settings

• Install Spark on the cluster

• Create the Spark application

What is the purpose of uploading the PySpark application file to a cluster machine?

• To test the application locally

• To execute the application on the cluster

• To back up the application

• To share the application with other developers

What is the final step after submitting a Spark application to the cluster?

• Reconfigure the Spark settings

• Check the application status on the Spark history server

• Delete the application from the cluster

• Restart the cluster