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  1. Spark
  2. SPARK-23243

Shuffle+Repartition on an RDD could lead to incorrect answers

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Details

    • Bug
    • Status: Resolved
    • Blocker
    • Resolution: Fixed
    • 1.6.0, 2.0.0, 2.1.0, 2.2.0, 2.3.0
    • 2.2.3, 2.3.2, 2.4.0
    • Spark Core

    Description

      The RDD repartition also uses the round-robin way to distribute data, this can also cause incorrect answers on RDD workload the similar way as in https://issues.apache.org/jira/browse/SPARK-23207

      The approach that fixes DataFrame.repartition() doesn't apply on the RDD repartition issue, as discussed in https://github.com/apache/spark/pull/20393#issuecomment-360912451

      We track for alternative solutions for this issue in this task.

      Attachments

        Issue Links

          is duplicated by

          Question - A formal question. Initially added for the Legal JIRA. SPARK-25156 Same query returns different result

          • Major - Major loss of function.
          • Closed
          is related to

          Bug - A problem which impairs or prevents the functions of the product. SPARK-28699 Cache an indeterminate RDD could lead to incorrect result while stage rerun

          • Blocker - Blocks development and/or testing work, production could not run
          • Resolved

          Improvement - An improvement or enhancement to an existing feature or task. SPARK-25342 Support rolling back a result stage

          • Major - Major loss of function.
          • In Progress

          Improvement - An improvement or enhancement to an existing feature or task. SPARK-25341 Support rolling back a shuffle map stage and re-generate the shuffle files

          • Major - Major loss of function.
          • Resolved
          relates to

          Bug - A problem which impairs or prevents the functions of the product. SPARK-23207 Shuffle+Repartition on an DataFrame could lead to incorrect answers

          • Blocker - Blocks development and/or testing work, production could not run
          • Resolved

          Bug - A problem which impairs or prevents the functions of the product. SPARK-29042 Sampling-based RDD with unordered input should be INDETERMINATE

          • Major - Major loss of function.
          • Resolved
          links to

          Pull request #20414 [Github] Pull Request #20414 (jiangxb1987)

          Pull request #21698 [Github] Pull Request #21698 (jiangxb1987)

          Pull request #22112 [Github] Pull Request #22112 (cloud-fan)

          Pull request #22354 [Github] Pull Request #22354 (cloud-fan)

          Pull request #22382 [Github] Pull Request #22382 (bersprockets)

          Web Link GitHub Pull Request #25755

          Activity

            People

              cloud_fan Wenchen Fan
              jiangxb1987 Xingbo Jiang
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              Dates

                Created:
                Updated:
                Resolved: