Github user CodingCat commented on the pull request:
https://github.com/apache/spark/pull/731#issuecomment-75468070
Hi, @andrewor14 , thanks for your review
I think I misunderstood your original point. Now, I merged two functions
(starting one/more executor(s)) .
The difference between my current approach and your proposal is that I
didn't introduce ###### spark.deploy.executorsPerWorker, instead, the executor
number on each worker is determined by the available cores/memory of the worker
at the scheduling moment.
The snapshots of running 4 executors in 2 workers were attached in my last
comment.
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