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From "genericqa (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-8202) DefaultAMSProcessor should properly check units of requested custom resource types against minimum/maximum allocation
Date Wed, 09 May 2018 02:07:00 GMT

    [ https://issues.apache.org/jira/browse/YARN-8202?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16468224#comment-16468224
] 

genericqa commented on YARN-8202:
---------------------------------

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|| Vote || Subsystem || Runtime || Comment ||
| {color:blue}0{color} | {color:blue} reexec {color} | {color:blue}  0m 27s{color} | {color:blue}
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| {color:green}+1{color} | {color:green} test4tests {color} | {color:green}  0m  0s{color}
| {color:green} The patch appears to include 5 new or modified test files. {color} |
|| || || || {color:brown} trunk Compile Tests {color} ||
| {color:blue}0{color} | {color:blue} mvndep {color} | {color:blue}  0m 26s{color} | {color:blue}
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| {color:green}+1{color} | {color:green} mvninstall {color} | {color:green} 26m 26s{color}
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| {color:green}+1{color} | {color:green} findbugs {color} | {color:green}  5m 56s{color} |
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| {color:green}+1{color} | {color:green} mvninstall {color} | {color:green}  2m 55s{color}
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the patch passed {color} |
| {color:orange}-0{color} | {color:orange} checkstyle {color} | {color:orange}  5m 27s{color}
| {color:orange} root: The patch generated 6 new + 122 unchanged - 95 fixed = 128 total (was
217) {color} |
| {color:green}+1{color} | {color:green} mvnsite {color} | {color:green}  4m 56s{color} |
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| {color:green}+1{color} | {color:green} shadedclient {color} | {color:green} 11m  0s{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}  7m 49s{color} |
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| {color:green}+1{color} | {color:green} javadoc {color} | {color:green}  3m 12s{color} |
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| {color:green}+1{color} | {color:green} unit {color} | {color:green}  0m 50s{color} | {color:green}
hadoop-yarn-api in the patch passed. {color} |
| {color:green}+1{color} | {color:green} unit {color} | {color:green}  3m 17s{color} | {color:green}
hadoop-yarn-common in the patch passed. {color} |
| {color:green}+1{color} | {color:green} unit {color} | {color:green}  2m 14s{color} | {color:green}
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| {color:green}+1{color} | {color:green} unit {color} | {color:green} 70m  8s{color} | {color:green}
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| {color:green}+1{color} | {color:green} unit {color} | {color:green}  9m 26s{color} | {color:green}
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| {color:green}+1{color} | {color:green} asflicense {color} | {color:green}  1m  2s{color}
| {color:green} The patch does not generate ASF License warnings. {color} |
| {color:black}{color} | {color:black} {color} | {color:black}244m 37s{color} | {color:black}
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|| Subsystem || Report/Notes ||
| Docker | Client=17.05.0-ce Server=17.05.0-ce Image:yetus/hadoop:abb62dd |
| JIRA Issue | YARN-8202 |
| JIRA Patch URL | https://issues.apache.org/jira/secure/attachment/12922527/YARN-8202-009.patch
|
| Optional Tests |  asflicense  compile  javac  javadoc  mvninstall  mvnsite  unit  shadedclient
 findbugs  checkstyle  |
| uname | Linux 10e6d9bc6794 3.13.0-143-generic #192-Ubuntu SMP Tue Feb 27 10:45:36 UTC 2018
x86_64 x86_64 x86_64 GNU/Linux |
| Build tool | maven |
| Personality | /testptch/patchprocess/precommit/personality/provided.sh |
| git revision | trunk / 1ef0a1d |
| maven | version: Apache Maven 3.3.9 |
| Default Java | 1.8.0_162 |
| findbugs | v3.1.0-RC1 |
| checkstyle | https://builds.apache.org/job/PreCommit-YARN-Build/20649/artifact/out/diff-checkstyle-root.txt
|
|  Test Results | https://builds.apache.org/job/PreCommit-YARN-Build/20649/testReport/ |
| Max. process+thread count | 819 (vs. ulimit of 10000) |
| modules | C: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-api hadoop-yarn-project/hadoop-yarn/hadoop-yarn-common
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-common hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager
hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app U: . |
| Console output | https://builds.apache.org/job/PreCommit-YARN-Build/20649/console |
| Powered by | Apache Yetus 0.8.0-SNAPSHOT   http://yetus.apache.org |


This message was automatically generated.



> DefaultAMSProcessor should properly check units of requested custom resource types against
minimum/maximum allocation
> ---------------------------------------------------------------------------------------------------------------------
>
>                 Key: YARN-8202
>                 URL: https://issues.apache.org/jira/browse/YARN-8202
>             Project: Hadoop YARN
>          Issue Type: Bug
>            Reporter: Szilard Nemeth
>            Assignee: Szilard Nemeth
>            Priority: Blocker
>         Attachments: YARN-8202-001.patch, YARN-8202-002.patch, YARN-8202-003.patch, YARN-8202-004.patch,
YARN-8202-005.patch, YARN-8202-006.patch, YARN-8202-007.patch, YARN-8202-008.patch, YARN-8202-009.patch
>
>
>  
> When I execute a pi job with arguments: 
> {code:java}
> -Dmapreduce.map.resource.memory-mb=200 -Dmapreduce.map.resource.resource1=500M 1 1000{code}
> and I have one node with 5GB of resource1, I get the following exception on every second
and the job hangs:
> {code:java}
> 2018-04-24 08:42:03,694 INFO org.apache.hadoop.ipc.Server: IPC Server handler 20 on 8030,
call Call#386 Retry#0 org.apache.hadoop.yarn.api.ApplicationMasterProtocolPB.allocate from
172.31.119.172:58138
> org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid resource request,
requested resource type=[resource1] < 0 or greater than maximum allowed allocation. Requested
resource=<memory:200, vCores:1, resource1: 500M>, maximum allowed allocation=<memory:6144,
vCores:8, resource1: 5G>, please note that maximum allowed allocation is calculated by
scheduler based on maximum resource of registered NodeManagers, which might be less than configured
maximum allocation=<memory:8192, vCores:8192, resource1: 9223372036854775807G>
>         at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.validateResourceRequest(SchedulerUtils.java:286)
>         at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndValidateRequest(SchedulerUtils.java:242)
>         at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndvalidateRequest(SchedulerUtils.java:258)
>         at org.apache.hadoop.yarn.server.resourcemanager.RMServerUtils.normalizeAndValidateRequests(RMServerUtils.java:249)
>         at org.apache.hadoop.yarn.server.resourcemanager.DefaultAMSProcessor.allocate(DefaultAMSProcessor.java:230)
>         at org.apache.hadoop.yarn.server.resourcemanager.scheduler.constraint.processor.DisabledPlacementProcessor.allocate(DisabledPlacementProcessor.java:75)
>         at org.apache.hadoop.yarn.server.resourcemanager.AMSProcessingChain.allocate(AMSProcessingChain.java:92)
>         at org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:433)
>         at org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60)
>         at org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99)
>         at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:523)
>         at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:991)
>         at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:872)
>         at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:818)
>         at java.security.AccessController.doPrivileged(Native Method)
>         at javax.security.auth.Subject.doAs(Subject.java:422)
>         at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1682)
>         at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2678)
> {code}
> *This is because org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils#validateResourceRequest
does not take resource units into account.*
>  
> However, if I start a job with arguments: 
> {code:java}
> -Dmapreduce.map.resource.memory-mb=200 -Dmapreduce.map.resource.resource1=1G 1 1000{code}
> and I still have 5GB of resource1 on one node then the job runs successfully.
>  
> I also tried a third job run, when I request 1GB of resource1 and I have no nodes with
any amount of resource1, then I restart the node with 5GBs of resource1, the job ultimately
completes, but just after the node with enough resources registered in RM, which is the desired
behaviour.
>  



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