Executors and cores in Apache Spark

Question

I'm bit new to Spark and trying to understand few term. (Couldn't understand using online resources)

Please validate me first with below terms:

Executor: Its container or JVM process which will be running on worker node or data node . We can have multiple Executors per node.

Core: Its a thread within a container or JVM process running on worker node or data node . We can have multiple cores or threads per executor.

Please correct me If am wrong in above two concepts.

Questions:

1. When ever we submit spark job, What does it means ? Are we handing over our job to Yarn or resource manager which will assigning resources to my application or job in cluster and execute that ? Its it correct understanding .. ?

2. In command used to submit job in spark cluster, there is an option to set number of executors.

   spark-submit --class <CLASS_NAME> --num-executors ? --executor-cores ? --executor-memory ? ....

So these number of executors + cores will be setting up per-node? If not then how can we set specific number of cores per node?

Answer 1

All of your assumptions are correct. For in a detailed explanation regarding cluster architecture please go through this link. You'll get a clear picture. Regarding your second question, num-of-executors is for the entire cluster. It is calculated as below:

num-cores-per-node * total-nodes-in-cluster

For example, suppose that you have a 20-node cluster with 4-core machines, and you submit an application with -executor-memory 1G and --total-executor-cores 8. Then Spark will launch eight executors, each with 1 GB of RAM, on different machines. Spark does this by default to give applications a chance to achieve data locality for distributed filesystems running on the same machines (eg, HDFS) because these systems typically have data spread out across all nodes.

I hope it helps!