How does spark.python.worker.memory relate to spark.executor.memory?

Question

This diagram is quite clear on the relationship between the different YARN and Spark memory related settings, except when it comes to spark.python.worker.memory .

How does spark.python.worker.memory fit into this memory model?

Are the Python processes governed by spark.executor.memory or yarn.nodemanager.resource.memory-mb ?

Update

This question explains what the setting does, but doesn't answer the question concerning the memory governance, or how it relates to other memory settings.

Answer 1

Found this thread from the Apache-spark mailing list, and it appears that spark.python.worker.memory is a subset of the memory from spark.executor.memory.

From the thread: "spark.python.worker.memory is used for Python worker in executor"