What is the difference between Spark submit client and cluster mode?

The main difference between Spark submit client and cluster mode lies in where the Spark application runs.

• Spark submit client: This mode runs the application on the machine where the spark-submit command is executed. This is suitable for small applications or for testing purposes.
• Cluster mode: This mode runs the application on a cluster of machines, such as a Hadoop cluster or a standalone Spark cluster. This mode is suitable for large applications that require more resources or for production deployments.

Here's a breakdown of the key differences:

Spark Submit Client:

• Execution: Runs on the local machine where the spark-submit command is executed.
• Resource Management: Manages resources on the local machine.
• Suitable for: Small applications, testing, or when limited resources are available.
• Example: Running a simple Spark application on your laptop for analysis.

Cluster Mode:

• Execution: Runs on a cluster of machines.
• Resource Management: Manages resources across the cluster.
• Suitable for: Large applications, production deployments, and when more resources are needed.
• Example: Running a complex machine learning model on a Hadoop cluster for real-time predictions.

Here's a table summarizing the key differences:

Understanding these differences will help you choose the appropriate mode for your Spark application based on your needs and resources.