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Posted to reviews@spark.apache.org by JoshRosen <gi...@git.apache.org> on 2016/11/30 00:58:57 UTC
[GitHub] spark pull request #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskS...
GitHub user JoshRosen opened a pull request:
https://github.com/apache/spark/pull/16070
[SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManager following executor loss
## What changes were proposed in this pull request?
_This is the master branch-1.6 version of #15986; the original description follows:_
This patch fixes a critical resource leak in the TaskScheduler which could cause RDDs and ShuffleDependencies to be kept alive indefinitely if an executor with running tasks is permanently lost and the associated stage fails.
This problem was originally identified by analyzing the heap dump of a driver belonging to a cluster that had run out of shuffle space. This dump contained several `ShuffleDependency` instances that were retained by `TaskSetManager`s inside the scheduler but were not otherwise referenced. Each of these `TaskSetManager`s was considered a "zombie" but had no running tasks and therefore should have been cleaned up. However, these zombie task sets were still referenced by the `TaskSchedulerImpl.taskIdToTaskSetManager` map.
Entries are added to the `taskIdToTaskSetManager` map when tasks are launched and are removed inside of `TaskScheduler.statusUpdate()`, which is invoked by the scheduler backend while processing `StatusUpdate` messages from executors. The problem with this design is that a completely dead executor will never send a `StatusUpdate`. There is [some code](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L338) in `statusUpdate` which handles tasks that exit with the `TaskState.LOST` state (which is supposed to correspond to a task failure triggered by total executor loss), but this state only seems to be used in Mesos fine-grained mode. There doesn't seem to be any code which performs per-task state cleanup for tasks that were running on an executor that completely disappears without sending any sort of final death message. The `executorLost` and [`removeExecutor`](https://github.com/ap
ache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L527) methods don't appear to perform any cleanup of the `taskId -> *` mappings, causing the leaks observed here.
This patch's fix is to maintain a `executorId -> running task id` mapping so that these `taskId -> *` maps can be properly cleaned up following an executor loss.
There are some potential corner-case interactions that I'm concerned about here, especially some details in [the comment](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L523) in `removeExecutor`, so I'd appreciate a very careful review of these changes.
## How was this patch tested?
I added a new unit test to `TaskSchedulerImplSuite`.
/cc @kayousterhout and @markhamstra, who reviewed #15986.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/JoshRosen/spark fix-leak-following-total-executor-loss-1.6
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/16070.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #16070
----
commit 15c0489cdc5bb81695405240c879fc7cf70fc745
Author: Josh Rosen <jo...@databricks.com>
Date: 2016-11-28T21:17:24Z
[SPARK-18553][CORE][BRANCH-2.0] Fix leak of TaskSetManager following executor loss
This patch fixes a critical resource leak in the TaskScheduler which could cause RDDs and ShuffleDependencies to be kept alive indefinitely if an executor with running tasks is permanently lost and the associated stage fails.
This problem was originally identified by analyzing the heap dump of a driver belonging to a cluster that had run out of shuffle space. This dump contained several `ShuffleDependency` instances that were retained by `TaskSetManager`s inside the scheduler but were not otherwise referenced. Each of these `TaskSetManager`s was considered a "zombie" but had no running tasks and therefore should have been cleaned up. However, these zombie task sets were still referenced by the `TaskSchedulerImpl.taskIdToTaskSetManager` map.
Entries are added to the `taskIdToTaskSetManager` map when tasks are launched and are removed inside of `TaskScheduler.statusUpdate()`, which is invoked by the scheduler backend while processing `StatusUpdate` messages from executors. The problem with this design is that a completely dead executor will never send a `StatusUpdate`. There is [some code](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L338) in `statusUpdate` which handles tasks that exit with the `TaskState.LOST` state (which is supposed to correspond to a task failure triggered by total executor loss), but this state only seems to be used in Mesos fine-grained mode. There doesn't seem to be any code which performs per-task state cleanup for tasks that were running on an executor that completely disappears without sending any sort of final death message. The `executorLost` and [`removeExecutor`](https://github.com/ap
ache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L527) methods don't appear to perform any cleanup of the `taskId -> *` mappings, causing the leaks observed here.
This patch's fix is to maintain a `executorId -> running task id` mapping so that these `taskId -> *` maps can be properly cleaned up following an executor loss.
There are some potential corner-case interactions that I'm concerned about here, especially some details in [the comment](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L523) in `removeExecutor`, so I'd appreciate a very careful review of these changes.
This PR is opened against branch-2.0, where I first observed this problem, but will also need to be fixed in master, branch-2.1, and branch-1.6 (which I'll do in followup PRs after this fix is reviewed and merged).
I added a new unit test to `TaskSchedulerImplSuite`. You can check out this PR as of 25e455e711b978cd331ee0f484f70fde31307634 to see the failing test.
cc kayousterhout, markhamstra, rxin for review.
Author: Josh Rosen <jo...@databricks.com>
Closes #15986 from JoshRosen/fix-leak-following-total-executor-loss.
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/16070
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/16070
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/16070
**[Test build #69414 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/69414/consoleFull)** for PR 16070 at commit [`776269f`](https://github.com/apache/spark/commit/776269ffeb7f2324a0a00899658e712621b3ff56).
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/16070
**[Test build #69366 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/69366/consoleFull)** for PR 16070 at commit [`776269f`](https://github.com/apache/spark/commit/776269ffeb7f2324a0a00899658e712621b3ff56).
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/16070
**[Test build #69366 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/69366/consoleFull)** for PR 16070 at commit [`776269f`](https://github.com/apache/spark/commit/776269ffeb7f2324a0a00899658e712621b3ff56).
* This patch **fails to build**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskS...
Posted by JoshRosen <gi...@git.apache.org>.
GitHub user JoshRosen reopened a pull request:
https://github.com/apache/spark/pull/16070
[SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManager following executor loss
## What changes were proposed in this pull request?
_This is the master branch-1.6 version of #15986; the original description follows:_
This patch fixes a critical resource leak in the TaskScheduler which could cause RDDs and ShuffleDependencies to be kept alive indefinitely if an executor with running tasks is permanently lost and the associated stage fails.
This problem was originally identified by analyzing the heap dump of a driver belonging to a cluster that had run out of shuffle space. This dump contained several `ShuffleDependency` instances that were retained by `TaskSetManager`s inside the scheduler but were not otherwise referenced. Each of these `TaskSetManager`s was considered a "zombie" but had no running tasks and therefore should have been cleaned up. However, these zombie task sets were still referenced by the `TaskSchedulerImpl.taskIdToTaskSetManager` map.
Entries are added to the `taskIdToTaskSetManager` map when tasks are launched and are removed inside of `TaskScheduler.statusUpdate()`, which is invoked by the scheduler backend while processing `StatusUpdate` messages from executors. The problem with this design is that a completely dead executor will never send a `StatusUpdate`. There is [some code](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L338) in `statusUpdate` which handles tasks that exit with the `TaskState.LOST` state (which is supposed to correspond to a task failure triggered by total executor loss), but this state only seems to be used in Mesos fine-grained mode. There doesn't seem to be any code which performs per-task state cleanup for tasks that were running on an executor that completely disappears without sending any sort of final death message. The `executorLost` and [`removeExecutor`](https://github.com/ap
ache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L527) methods don't appear to perform any cleanup of the `taskId -> *` mappings, causing the leaks observed here.
This patch's fix is to maintain a `executorId -> running task id` mapping so that these `taskId -> *` maps can be properly cleaned up following an executor loss.
There are some potential corner-case interactions that I'm concerned about here, especially some details in [the comment](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L523) in `removeExecutor`, so I'd appreciate a very careful review of these changes.
## How was this patch tested?
I added a new unit test to `TaskSchedulerImplSuite`.
/cc @kayousterhout and @markhamstra, who reviewed #15986.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/JoshRosen/spark fix-leak-following-total-executor-loss-1.6
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/16070.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #16070
----
commit 15c0489cdc5bb81695405240c879fc7cf70fc745
Author: Josh Rosen <jo...@databricks.com>
Date: 2016-11-28T21:17:24Z
[SPARK-18553][CORE][BRANCH-2.0] Fix leak of TaskSetManager following executor loss
This patch fixes a critical resource leak in the TaskScheduler which could cause RDDs and ShuffleDependencies to be kept alive indefinitely if an executor with running tasks is permanently lost and the associated stage fails.
This problem was originally identified by analyzing the heap dump of a driver belonging to a cluster that had run out of shuffle space. This dump contained several `ShuffleDependency` instances that were retained by `TaskSetManager`s inside the scheduler but were not otherwise referenced. Each of these `TaskSetManager`s was considered a "zombie" but had no running tasks and therefore should have been cleaned up. However, these zombie task sets were still referenced by the `TaskSchedulerImpl.taskIdToTaskSetManager` map.
Entries are added to the `taskIdToTaskSetManager` map when tasks are launched and are removed inside of `TaskScheduler.statusUpdate()`, which is invoked by the scheduler backend while processing `StatusUpdate` messages from executors. The problem with this design is that a completely dead executor will never send a `StatusUpdate`. There is [some code](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L338) in `statusUpdate` which handles tasks that exit with the `TaskState.LOST` state (which is supposed to correspond to a task failure triggered by total executor loss), but this state only seems to be used in Mesos fine-grained mode. There doesn't seem to be any code which performs per-task state cleanup for tasks that were running on an executor that completely disappears without sending any sort of final death message. The `executorLost` and [`removeExecutor`](https://github.com/ap
ache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L527) methods don't appear to perform any cleanup of the `taskId -> *` mappings, causing the leaks observed here.
This patch's fix is to maintain a `executorId -> running task id` mapping so that these `taskId -> *` maps can be properly cleaned up following an executor loss.
There are some potential corner-case interactions that I'm concerned about here, especially some details in [the comment](https://github.com/apache/spark/blob/072f4c518cdc57d705beec6bcc3113d9a6740819/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L523) in `removeExecutor`, so I'd appreciate a very careful review of these changes.
This PR is opened against branch-2.0, where I first observed this problem, but will also need to be fixed in master, branch-2.1, and branch-1.6 (which I'll do in followup PRs after this fix is reviewed and merged).
I added a new unit test to `TaskSchedulerImplSuite`. You can check out this PR as of 25e455e711b978cd331ee0f484f70fde31307634 to see the failing test.
cc kayousterhout, markhamstra, rxin for review.
Author: Josh Rosen <jo...@databricks.com>
Closes #15986 from JoshRosen/fix-leak-following-total-executor-loss.
commit 776269ffeb7f2324a0a00899658e712621b3ff56
Author: Josh Rosen <jo...@databricks.com>
Date: 2016-11-30T00:59:47Z
Update TaskSchedulerImpl.scala
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/16070
Merged build finished. Test FAILed.
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/16070
**[Test build #69414 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/69414/consoleFull)** for PR 16070 at commit [`776269f`](https://github.com/apache/spark/commit/776269ffeb7f2324a0a00899658e712621b3ff56).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by kayousterhout <gi...@git.apache.org>.
Github user kayousterhout commented on the issue:
https://github.com/apache/spark/pull/16070
LGTM
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[GitHub] spark pull request #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskS...
Posted by JoshRosen <gi...@git.apache.org>.
Github user JoshRosen closed the pull request at:
https://github.com/apache/spark/pull/16070
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/16070
Test PASSed.
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[GitHub] spark pull request #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskS...
Posted by JoshRosen <gi...@git.apache.org>.
Github user JoshRosen closed the pull request at:
https://github.com/apache/spark/pull/16070
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[GitHub] spark pull request #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskS...
Posted by kayousterhout <gi...@git.apache.org>.
Github user kayousterhout commented on a diff in the pull request:
https://github.com/apache/spark/pull/16070#discussion_r90150849
--- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala ---
@@ -332,7 +332,7 @@ private[spark] class TaskSchedulerImpl(
taskIdToTaskSetManager.get(tid) match {
case Some(taskSet) =>
if (state == TaskState.LOST) {
- // TaskState.LOST is only used by the deprecated Mesos fine-grained scheduling mode,
+ // TaskState.LOST is only used by the Mesos fine-grained scheduling mode,
--- End diff --
nice catch on the comment here!
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by JoshRosen <gi...@git.apache.org>.
Github user JoshRosen commented on the issue:
https://github.com/apache/spark/pull/16070
I'm going to merge this to branch-1.6 now. Thanks for reviewing!
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[GitHub] spark issue #16070: [SPARK-18553][CORE][BRANCH-1.6] Fix leak of TaskSetManag...
Posted by JoshRosen <gi...@git.apache.org>.
Github user JoshRosen commented on the issue:
https://github.com/apache/spark/pull/16070
Jenkins, retest this please
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