[SPARK-23147][UI] Fix task page table IndexOutOfBound Exception #20315
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jerryshao
commented
Jan 18, 2018
| @@ -676,7 +676,7 @@ private[ui] class TaskDataSource( | |||
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| private var _tasksToShow: Seq[TaskData] = null | |||
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| override def dataSize: Int = stage.numCompleteTasks + stage.numFailedTasks + stage.numKilledTasks | |||
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@vanzin I think you made this change, why not also track the running tasks? I'm not sure what is your original purpose.
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Probably just a side effect of me testing mostly with replayed logs and short-lived tasks.
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Fix seems to be in line with what Spark 2.2 did, so LGTM pending tests. |
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Test build #86341 has finished for PR 20315 at commit
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Timed out on kafka test, no reason to run tests again. |
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Merging to master / 2.3. |
asfgit
pushed a commit
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Jan 18, 2018
## What changes were proposed in this pull request?
Stage's task page table will throw an exception when there's no complete tasks. Furthermore, because the `dataSize` doesn't take running tasks into account, so sometimes UI cannot show the running tasks. Besides table will only be displayed when first task is finished according to the default sortColumn("index").
To reproduce this issue, user could try `sc.parallelize(1 to 20, 20).map { i => Thread.sleep(10000); i }.collect()` or `sc.parallelize(1 to 20, 20).map { i => Thread.sleep((20 - i) * 1000); i }.collect` to reproduce the above issue.
Here propose a solution to fix it. Not sure if it is a right fix, please help to review.
## How was this patch tested?
Manual test.
Author: jerryshao <[email protected]>
Closes #20315 from jerryshao/SPARK-23147.
(cherry picked from commit cf7ee17)
Signed-off-by: Marcelo Vanzin <[email protected]>
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What changes were proposed in this pull request?
Stage's task page table will throw an exception when there's no complete tasks. Furthermore, because the
dataSizedoesn't take running tasks into account, so sometimes UI cannot show the running tasks. Besides table will only be displayed when first task is finished according to the default sortColumn("index").To reproduce this issue, user could try
sc.parallelize(1 to 20, 20).map { i => Thread.sleep(10000); i }.collect()orsc.parallelize(1 to 20, 20).map { i => Thread.sleep((20 - i) * 1000); i }.collectto reproduce the above issue.Here propose a solution to fix it. Not sure if it is a right fix, please help to review.
How was this patch tested?
Manual test.