Github user CodingCat commented on the pull request:
https://github.com/apache/spark/pull/731#issuecomment-86787320
@andrewor14 I think in spreadApp mode, grabing all cores when
`spark.deploy.maxCoresPerExecutor` is not defined is *not* the right approach...
if we grab all cores, it is exactly equivalent to `non-spreadApp mode` in
the implementation in current master branch. Instead, we should traverse all
workers one by one, for each visit, we allocate 1 free core to the executor
when `spark.deploy.maxCoresPerExecutor == None`; otherwise, for each visit, we
assign at most `spark.deploy.maxCoresPerExecutor` cores
am I right?
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