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From "Hadoop QA (Jira)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-7208) Tuning TaskRuntimeEstimator
Date Wed, 30 Oct 2019 20:43:00 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-7208?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16963414#comment-16963414
] 

Hadoop QA commented on MAPREDUCE-7208:
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| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:blue}0{color} | {color:blue} reexec {color} | {color:blue}  0m 21s{color} | {color:blue}
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| {color:green}+1{color} | {color:green} @author {color} | {color:green}  0m  0s{color} |
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| {color:green}+1{color} | {color:green} test4tests {color} | {color:green}  0m  0s{color}
| {color:green} The patch appears to include 4 new or modified test files. {color} |
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| {color:blue}0{color} | {color:blue} mvndep {color} | {color:blue}  0m 16s{color} | {color:blue}
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| {color:green}+1{color} | {color:green} mvninstall {color} | {color:green} 17m  5s{color}
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| {color:green}+1{color} | {color:green} compile {color} | {color:green}  1m 42s{color} |
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| {color:green}+1{color} | {color:green} checkstyle {color} | {color:green}  0m 53s{color}
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| {color:green}+1{color} | {color:green} mvnsite {color} | {color:green}  1m 46s{color} |
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| {color:green}+1{color} | {color:green} shadedclient {color} | {color:green} 14m 24s{color}
| {color:green} branch has no errors when building and testing our client artifacts. {color}
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| {color:green}+1{color} | {color:green} findbugs {color} | {color:green}  2m  8s{color} |
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| {color:blue}0{color} | {color:blue} mvndep {color} | {color:blue}  0m 14s{color} | {color:blue}
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| {color:green}+1{color} | {color:green} mvninstall {color} | {color:green}  1m 31s{color}
| {color:green} the patch passed {color} |
| {color:green}+1{color} | {color:green} compile {color} | {color:green}  1m 35s{color} |
{color:green} the patch passed {color} |
| {color:green}+1{color} | {color:green} javac {color} | {color:green}  1m 35s{color} | {color:green}
the patch passed {color} |
| {color:orange}-0{color} | {color:orange} checkstyle {color} | {color:orange}  0m 48s{color}
| {color:orange} hadoop-mapreduce-project/hadoop-mapreduce-client: The patch generated 2 new
+ 702 unchanged - 2 fixed = 704 total (was 704) {color} |
| {color:green}+1{color} | {color:green} mvnsite {color} | {color:green}  1m 27s{color} |
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| {color:green}+1{color} | {color:green} whitespace {color} | {color:green}  0m  0s{color}
| {color:green} The patch has no whitespace issues. {color} |
| {color:green}+1{color} | {color:green} shadedclient {color} | {color:green} 12m 30s{color}
| {color:green} patch has no errors when building and testing our client artifacts. {color}
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| {color:green}+1{color} | {color:green} findbugs {color} | {color:green}  2m 21s{color} |
{color:green} the patch passed {color} |
| {color:green}+1{color} | {color:green} javadoc {color} | {color:green}  1m  3s{color} |
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| {color:green}+1{color} | {color:green} unit {color} | {color:green}  5m  8s{color} | {color:green}
hadoop-mapreduce-client-core in the patch passed. {color} |
| {color:green}+1{color} | {color:green} unit {color} | {color:green} 10m 13s{color} | {color:green}
hadoop-mapreduce-client-app in the patch passed. {color} |
| {color:red}-1{color} | {color:red} unit {color} | {color:red}125m 28s{color} | {color:red}
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| {color:red}-1{color} | {color:red} asflicense {color} | {color:red}  0m 40s{color} | {color:red}
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| {color:black}{color} | {color:black} {color} | {color:black}202m  0s{color} | {color:black}
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|| Subsystem || Report/Notes ||
| Docker | Client=19.03.4 Server=19.03.4 Image:yetus/hadoop:104ccca9169 |
| JIRA Issue | MAPREDUCE-7208 |
| JIRA Patch URL | https://issues.apache.org/jira/secure/attachment/12984392/MAPREDUCE-7208.004.patch
|
| Optional Tests |  dupname  asflicense  compile  javac  javadoc  mvninstall  mvnsite  unit
 shadedclient  findbugs  checkstyle  |
| uname | Linux af8bb51752c8 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019
x86_64 x86_64 x86_64 GNU/Linux |
| Build tool | maven |
| Personality | /testptch/patchprocess/precommit/personality/provided.sh |
| git revision | trunk / e3e7daa |
| maven | version: Apache Maven 3.3.9 |
| Default Java | 1.8.0_222 |
| findbugs | v3.1.0-RC1 |
| checkstyle | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7681/artifact/out/diff-checkstyle-hadoop-mapreduce-project_hadoop-mapreduce-client.txt
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| unit | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7681/artifact/out/patch-unit-hadoop-mapreduce-project_hadoop-mapreduce-client_hadoop-mapreduce-client-jobclient.txt
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|  Test Results | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7681/testReport/
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| asflicense | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7681/artifact/out/patch-asflicense-problems.txt
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| Max. process+thread count | 1581 (vs. ulimit of 5500) |
| modules | C: hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core
hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient
U: hadoop-mapreduce-project/hadoop-mapreduce-client |
| Console output | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7681/console |
| Powered by | Apache Yetus 0.8.0   http://yetus.apache.org |


This message was automatically generated.



> 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, MAPREDUCE-7208.003.patch,
MAPREDUCE-7208.004.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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