Github user cloud-fan commented on the issue:
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LGTM, merging to master!
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Github user jiangxb1987 commented on the issue:
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@10110346 Could you update the PR as @jerryshao suggested? Thanks!
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@JoshRosen @cloud-fan Could you help to review it ? thanks
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Github user jiangxb1987 commented on the issue:
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In the past days we often assume that in standalone mode, if we don't set
the "spark.executor.cores" property, then we should have no more than one
executor per host, but this PR explains a
Github user jerryshao commented on the issue:
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@srowen due to the current design of standalone cluster manager, if we
don't set `--total-executor-cores`, then Spark application will try to acquire
all the free cores on this cluster, and it
Github user srowen commented on the issue:
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I don't object to this but I suppose I'm not clear if this was a point of
confusion that needed a fix.
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retest this please
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Github user jiangxb1987 commented on the issue:
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yea, I understand the issue now. Thank you for clarify!
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If the other application is finished, it will release cores
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How can we wait for new free cores on the same worker, if we only start one
executor for each worker initially?
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@jiangxb1987 If `app.coresLeft` is not zero and there is no more free
cores left, it is not ending.Waiting for some workers have free cores, this
app will be assigned cores continue, and this
Github user jiangxb1987 commented on the issue:
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AFAIK when `spark.executor.cores` is not set, we would keep assigning free
cores to the executor until `app.coresLeft` is zero or there is no more free
cores left. So I'm not convinced the
Github user srowen commented on the issue:
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I'm not sure this is an improvement, though not really against it.
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