Spark Programming in Python for Beginners with Apache Spark 3 - Execution Methods - How to Run Spark Programs?

The video tutorial introduces Apache Spark, a distributed computing platform, and discusses how to create and execute Spark programs. It covers two main methods for running Spark programs: interactive clients and job submission. The tutorial explains the use of Spark shell and notebooks for learning and development, and the Spark Submit utility for production use. It also highlights stream and batch processing applications and mentions vendor-specific alternatives for submitting Spark jobs.

What is Apache Spark primarily used for?

• Database management

• Distributed computing

• Graphic design

• Creating web applications

Which of the following is NOT a method to execute Spark programs?

• Spark Submit

• Manual execution

• Submit a job

• Interactive clients

What is the primary use of interactive clients like Spark shell?

• Data storage

• Production deployment

• Exploration and learning

• Security management

Which type of application can be developed using Spark?

• Stream processing

• Web hosting

• Email marketing

• Graphic design

What is the main tool for submitting a Spark program to a cluster?

• Spark Submit

• Spark Shell

• Web-based notebooks

• REST APIs

Which cloud-based service allows submitting a notebook directly without packaging?

• Data Bricks Cloud

• Azure Functions

• Google Cloud Functions

• AWS Lambda

What is a universally accepted method for running Spark jobs?

• Manual execution

• Spark Submit

• Web-based interface

• REST APIs