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[SPARK-18905][STREAMING] Fix the issue of removing a failed jobset fr…
…om JobScheduler.jobSets ## What changes were proposed in this pull request? the current implementation of Spark streaming considers a batch is completed no matter the results of the jobs (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L203) Let's consider the following case: A micro batch contains 2 jobs and they read from two different kafka topics respectively. One of these jobs is failed due to some problem in the user defined logic, after the other one is finished successfully. 1. The main thread in the Spark streaming application will execute the line mentioned above, 2. and another thread (checkpoint writer) will make a checkpoint file immediately after this line is executed. 3. Then due to the current error handling mechanism in Spark Streaming, StreamingContext will be closed (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L214) the user recovers from the checkpoint file, and because the JobSet containing the failed job has been removed (taken as completed) before the checkpoint is constructed, the data being processed by the failed job would never be reprocessed This PR fix it by removing jobset from JobScheduler.jobSets only when all jobs in a jobset are successfully finished ## How was this patch tested? existing tests Author: CodingCat <[email protected]> Author: Nan Zhu <[email protected]> Closes #16542 from CodingCat/SPARK-18905. (cherry picked from commit f8db894) Signed-off-by: Shixiong Zhu <[email protected]>
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