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retest this please
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> So the problem here is, when we retry a stage, Spark doesn't kill the
tasks of the old stage and just launch tasks for the new stage
I think that's something that should be fixed, but it
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Thanks for the review! I addressed the comments
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@@ -294,6 +333,16 @@ class MemorySink(val schema:
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This should go into branch-2.3 too.
I also think this is a little fragile (which is why I filed SPARK-24532),
and I've been playing with some alternative code, but it feels like a bit too
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> IMO your change is the right fix, not just a workaround
@squito, part of the problem is that the output commit coordinator -- that
ensures only one attempt of a task commits -- relies on
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As @squito suggested, we can either use taskAttemptId or combine
stageAttemptId and taskAttemptNumber together, both shall be able to represent
a unique task attempt.
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--- Diff: docs/configuration.md ---
@@ -472,15 +472,17 @@ Apart from these, the following properties are also
available, and may be useful
20
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"Other column
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@jkbradley test added. Could you please review?
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@cloud-fan, tests are passing for c8517e145b1a460a8be07164c17ce20b1db86659,
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Sorry in advance if this is the wrong place to be asking this!
Does this PR mean that we'll be able to create SparkContexts using
PySpark's
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[SPARK-24386][SS] coalesce(1) aggregates in continuous processing
## What changes were proposed in this pull request?
Provide a continuous processing implementation of coalesce(1), as
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/21389
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