[jira] [Commented] (MAPREDUCE-7123) AM Failed with Communication error to RM
[ https://issues.apache.org/jira/browse/MAPREDUCE-7123?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16962711#comment-16962711 ] Amithsha commented on MAPREDUCE-7123: - [~cane] we closed this since the versions are not same (version running on container and version running on RM ) May version be incompatibility. > AM Failed with Communication error to RM > > > Key: MAPREDUCE-7123 > URL: https://issues.apache.org/jira/browse/MAPREDUCE-7123 > Project: Hadoop Map/Reduce > Issue Type: Bug > Components: mrv2, yarn >Affects Versions: 2.9.0 >Reporter: Amithsha >Priority: Major > > During the restart of nodemanagers in 300 node cluster some jobs failed with > the following exceptions. > But the nodes where the AM launched is not the part of cluster. > FATAL [AsyncDispatcher event handler] > org.apache.hadoop.yarn.event.AsyncDispatcher: Error in dispatcher thread > java.lang.NullPointerException at > org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl$UpdatedNodesTransition.transition(JobImpl.java:2146) > at > org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl$UpdatedNodesTransition.transition(JobImpl.java:2139) > at > org.apache.hadoop.yarn.state.StateMachineFactory$SingleInternalArc.doTransition(StateMachineFactory.java:362) > at > org.apache.hadoop.yarn.state.StateMachineFactory.doTransition(StateMachineFactory.java:302) > at > org.apache.hadoop.yarn.state.StateMachineFactory.access$300(StateMachineFactory.java:46) > at > org.apache.hadoop.yarn.state.StateMachineFactory$InternalStateMachine.doTransition(StateMachineFactory.java:448) > at > org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl.handle(JobImpl.java:998) > at > org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl.handle(JobImpl.java:138) > at > org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobEventDispatcher.handle(MRAppMaster.java:1346) > at > org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobEventDispatcher.handle(MRAppMaster.java:1342) > at > org.apache.hadoop.yarn.event.AsyncDispatcher.dispatch(AsyncDispatcher.java:183) > at > org.apache.hadoop.yarn.event.AsyncDispatcher$1.run(AsyncDispatcher.java:109) > at java.lang.Thread.run(Thread.java:745) 2018-07-14 12:34:53,425 ERROR > [RMCommunicator Allocator] > org.apache.hadoop.mapreduce.v2.app.rm.RMCommunicator: ERROR IN CONTACTING RM. > java.lang.NullPointerException at > org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator.handleUpdatedNodes(RMContainerAllocator.java:875) > at > org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator.getResources(RMContainerAllocator.java:776) > at > org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator.heartbeat(RMContainerAllocator.java:256) > at > org.apache.hadoop.mapreduce.v2.app.rm.RMCommunicator$AllocatorRunnable.run(RMCommunicator.java:281) > at java.lang.Thread.run(Thread.java:745) 2018-07-14 12:34:53,427 INFO > [AsyncDispatcher ShutDown handler] > org.apache.hadoop.yarn.event.AsyncDispatcher: Exiting, bbye.. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: mapreduce-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: mapreduce-issues-h...@hadoop.apache.org
[jira] [Updated] (MAPREDUCE-7245) Reduce phase does not continue processing with failed SCHEDULED Map tasks
[ https://issues.apache.org/jira/browse/MAPREDUCE-7245?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sultan Alamro updated MAPREDUCE-7245: - Affects Version/s: 3.2.1 > Reduce phase does not continue processing with failed SCHEDULED Map tasks > - > > Key: MAPREDUCE-7245 > URL: https://issues.apache.org/jira/browse/MAPREDUCE-7245 > Project: Hadoop Map/Reduce > Issue Type: Bug >Affects Versions: 2.7.2, 3.2.1 >Reporter: Sultan Alamro >Priority: Major > > When we set *mapreduce.map.maxattempts* to 1, the reduce tasks should ignore > the output of failed tasks as state it in EventFetch class. However, it turns > out that this only happens when a map task transitions from RUNNING to > FAILED, not from SCHEDULED to FAILED -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: mapreduce-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: mapreduce-issues-h...@hadoop.apache.org
[jira] [Commented] (MAPREDUCE-7208) Tuning TaskRuntimeEstimator
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https://issues.apache.org/jira/browse/MAPREDUCE-7208?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16962665#comment-16962665
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Hadoop QA commented on MAPREDUCE-7208:
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| {color:green}+1{color} | {color:green} test4tests {color} | {color:green} 0m
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[jira] [Commented] (MAPREDUCE-7247) Modify HistoryServerRest.html content,change The job attempt id‘s datatype from string to int.
[
https://issues.apache.org/jira/browse/MAPREDUCE-7247?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16962571#comment-16962571
]
zhaoshengjie commented on MAPREDUCE-7247:
-
I have fixed the document error
> Modify HistoryServerRest.html content,change The job attempt id‘s datatype
> from string to int.
> --
>
> Key: MAPREDUCE-7247
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-7247
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: documentation
>Affects Versions: 3.2.1
>Reporter: zhaoshengjie
>Priority: Trivial
> Attachments: image-2019-10-29-14-46-17-354.png,
> image-2019-10-29-14-46-49-929.png
>
>
> The Job Attempts API
> http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/\{jobid}/jobattempts
> document, In
> http://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-hs/HistoryServerRest.html#Job_Attempts_API,
> change The job attempt id‘s datatype from string to int.
> !image-2019-10-29-14-46-17-354.png|width=508,height=126!
> !image-2019-10-29-14-46-49-929.png|width=465,height=315!
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[jira] [Commented] (MAPREDUCE-7208) Tuning TaskRuntimeEstimator
[
https://issues.apache.org/jira/browse/MAPREDUCE-7208?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16962437#comment-16962437
]
Ahmed Hussein commented on MAPREDUCE-7208:
--
Thanks [~jeagles]. I looked at the test cases:
* {{hadoop.mapreduce.v2.TestSpeculativeExecutionWithMRApp}} is a related test
case and It was failing because I changed the threshold of the estimate that
triggers a new speculative task. I fixed that default behavior in the new patch.
* {{hadoop.mapred.TestLocalMRNotification}} and
{{hadoop.mapreduce.v2.TestMROldApiJobs}} seem to be a random failure. They pass
successfully on local machine.
> Tuning TaskRuntimeEstimator
>
>
> Key: MAPREDUCE-7208
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-7208
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
>Reporter: Ahmed Hussein
>Assignee: Ahmed Hussein
>Priority: Minor
> Attachments: MAPREDUCE-7208.001.patch, MAPREDUCE-7208.002.patch,
> smoothing-exponential.md
>
>
> By default, MR uses LegacyTaskRuntimeEstimator to get an estimate of the
> runtime. The estimator does not adjust dynamically to the progress rate of
> the tasks. On the other hand, the existing alternative
> "ExponentiallySmoothedTaskRuntimeEstimator" behavior in unpredictable.
>
> There are several dimensions to improve the exponential implementation:
> # Exponential shooting needs a warmup period. Otherwise, the estimate will
> be affected by the initial values.
> # Using a single smoothing factor (Lambda) does not work well for all the
> tasks. To increase the level of smoothing across the majority of tasks, we
> need to give a range of flexibility to dynamically adjust the smoothing
> factor based on the history of the task progress.
> # Design wise, it is better to separate between the statistical model and
> the MR interface. We need to have a way to evaluate estimators statistically,
> without the need to run MR. For example, an estimator can be evaluated as a
> black box by using a stream of raw data as input and testing the accuracy of
> the generated stream of estimates.
> # The exponential estimator speculates frequently and fails to detect
> slowing tasks. It does not detect slowing tasks. As a result, a taskAttempt
> that does not do any progress won't trigger a new speculation.
>
> The file [^smoothing-exponential.md] describes how Simple Exponential
> smoothing factor works.
>
>
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[jira] [Updated] (MAPREDUCE-7208) Tuning TaskRuntimeEstimator
[ https://issues.apache.org/jira/browse/MAPREDUCE-7208?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Ahmed Hussein updated MAPREDUCE-7208: - Attachment: MAPREDUCE-7208.002.patch > Tuning TaskRuntimeEstimator > > > Key: MAPREDUCE-7208 > URL: https://issues.apache.org/jira/browse/MAPREDUCE-7208 > Project: Hadoop Map/Reduce > Issue Type: Improvement >Reporter: Ahmed Hussein >Assignee: Ahmed Hussein >Priority: Minor > Attachments: MAPREDUCE-7208.001.patch, MAPREDUCE-7208.002.patch, > smoothing-exponential.md > > > By default, MR uses LegacyTaskRuntimeEstimator to get an estimate of the > runtime. The estimator does not adjust dynamically to the progress rate of > the tasks. On the other hand, the existing alternative > "ExponentiallySmoothedTaskRuntimeEstimator" behavior in unpredictable. > > There are several dimensions to improve the exponential implementation: > # Exponential shooting needs a warmup period. Otherwise, the estimate will > be affected by the initial values. > # Using a single smoothing factor (Lambda) does not work well for all the > tasks. To increase the level of smoothing across the majority of tasks, we > need to give a range of flexibility to dynamically adjust the smoothing > factor based on the history of the task progress. > # Design wise, it is better to separate between the statistical model and > the MR interface. We need to have a way to evaluate estimators statistically, > without the need to run MR. For example, an estimator can be evaluated as a > black box by using a stream of raw data as input and testing the accuracy of > the generated stream of estimates. > # The exponential estimator speculates frequently and fails to detect > slowing tasks. It does not detect slowing tasks. As a result, a taskAttempt > that does not do any progress won't trigger a new speculation. > > The file [^smoothing-exponential.md] describes how Simple Exponential > smoothing factor works. > > -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: mapreduce-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: mapreduce-issues-h...@hadoop.apache.org
[jira] [Created] (MAPREDUCE-7247) Modify HistoryServerRest.html content,change The job attempt id‘s datatype from string to int.
zhaoshengjie created MAPREDUCE-7247:
---
Summary: Modify HistoryServerRest.html content,change The job
attempt id‘s datatype from string to int.
Key: MAPREDUCE-7247
URL: https://issues.apache.org/jira/browse/MAPREDUCE-7247
Project: Hadoop Map/Reduce
Issue Type: Improvement
Components: documentation
Affects Versions: 3.2.1
Reporter: zhaoshengjie
Attachments: image-2019-10-29-14-46-17-354.png,
image-2019-10-29-14-46-49-929.png
The Job Attempts API
http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/\{jobid}/jobattempts
document, In
http://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-hs/HistoryServerRest.html#Job_Attempts_API,
change The job attempt id‘s datatype from string to int.
!image-2019-10-29-14-46-17-354.png|width=508,height=126!
!image-2019-10-29-14-46-49-929.png|width=465,height=315!
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