Electron microscopy
  
PythonML
Deploy Modes for Driver Process in Apache Spark: Client and Cluster Modes
- Python Automation and Machine Learning for ICs -
- An Online Book: Python Automation and Machine Learning for ICs by Yougui Liao -
Python Automation and Machine Learning for ICs                                                           http://www.globalsino.com/ICs/        


Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix

=================================================================================

In Apache Spark, there are two deploy modes for the driver process: client mode and cluster mode:

  • Client Mode: In client mode, the driver process runs on the machine where the Spark application was submitted (typically the user's machine or a client machine). The client submits the application to the cluster manager (e.g., YARN, Mesos, or Spark Standalone), and the driver communicates directly with the cluster manager to request resources and coordinate the execution of tasks on the cluster's worker nodes.
  • Cluster Mode: In cluster mode, the driver process runs within the cluster itself. The application is submitted to the cluster manager, which launches the driver process on one of the cluster nodes. The driver then communicates with the cluster manager to request resources and manage the execution of tasks on the worker nodes.

===========================================

         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         

 

 

 

 

 



















































 

 

 

 

 
=================================================================================