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  1. Spark
  2. SPARK-9353

Standalone scheduling memory requirement incorrect if cores per executor is not set

    Details

    • Type: Bug
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 1.5.0
    • Fix Version/s: 1.4.2, 1.5.0
    • Component/s: Deploy
    • Labels:
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      Description

      I tried to come up with a more succinct title.

      The issue only happens if `spark.executor.cores` is not set. Right now if we have a worker with 8G, and we set `spark.executor.memory` to 1G, then the executor launched on the worker can have at most 8 cores, even if the worker has more cores available.

      This is caused by the fix in SPARK-8881.

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            • Assignee:
              andrewor14 Andrew Or
              Reporter:
              andrewor14 Andrew Or
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              • Created:
                Updated:
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