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https://issues.apache.org/jira/browse/YARN-7732?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16350853#comment-16350853
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Young Chen commented on YARN-7732:
----------------------------------

Added back compatibility with JobStory and JobStoryProducer interfaces for 
gridmix integration in [^YARN-7732.04.patch]

> Support Generic AM Simulator from SynthGenerator
> ------------------------------------------------
>
>                 Key: YARN-7732
>                 URL: https://issues.apache.org/jira/browse/YARN-7732
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>          Components: scheduler-load-simulator
>            Reporter: Young Chen
>            Assignee: Young Chen
>            Priority: Minor
>         Attachments: YARN-7732-YARN-7798.01.patch, 
> YARN-7732-YARN-7798.02.patch, YARN-7732.01.patch, YARN-7732.02.patch, 
> YARN-7732.03.patch, YARN-7732.04.patch
>
>
> Extract the MapReduce specific set-up in the SLSRunner into the 
> MRAMSimulator, and enable support for pluggable AMSimulators.
> Previously, the AM set up in SLSRunner had the MRAMSimulator type hard coded, 
> for example startAMFromSynthGenerator() calls this:
>  
> {code:java}
> runNewAM(SLSUtils.DEFAULT_JOB_TYPE, user, jobQueue, oldJobId,
>             jobStartTimeMS, jobFinishTimeMS, containerList, reservationId,
>             job.getDeadline(), getAMContainerResource(null));
> {code}
> where SLSUtils.DEFAULT_JOB_TYPE = "mapreduce"
> The container set up was also only suitable for mapreduce: 
>  
> {code:java}
> Version:1.0 StartHTML:000000286 EndHTML:000012564 StartFragment:000003634 
> EndFragment:000012474 StartSelection:000003700 EndSelection:000012464 
> SourceURL:https://github.com/apache/hadoop/blob/trunk/hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/SLSRunner.java
>  
> // map tasks
> for (int i = 0; i < job.getNumberMaps(); i++) {
>       TaskAttemptInfo tai = job.getTaskAttemptInfo(TaskType.MAP, i, 0);
>       RMNode node =
>               nmMap.get(keyAsArray.get(rand.nextInt(keyAsArray.size())))
>                       .getNode();
>       String hostname = "/" + node.getRackName() + "/" + node.getHostName();
>       long containerLifeTime = tai.getRuntime();
>       Resource containerResource =
>               Resource.newInstance((int) tai.getTaskInfo().getTaskMemory(),
>                       (int) tai.getTaskInfo().getTaskVCores());
>       containerList.add(new ContainerSimulator(containerResource,
>               containerLifeTime, hostname, DEFAULT_MAPPER_PRIORITY, "map"));
> }
> // reduce tasks
> for (int i = 0; i < job.getNumberReduces(); i++) {
>       TaskAttemptInfo tai = job.getTaskAttemptInfo(TaskType.REDUCE, i, 0);
>       RMNode node =
>               nmMap.get(keyAsArray.get(rand.nextInt(keyAsArray.size())))
>                       .getNode();
>       String hostname = "/" + node.getRackName() + "/" + node.getHostName();
>       long containerLifeTime = tai.getRuntime();
>       Resource containerResource =
>               Resource.newInstance((int) tai.getTaskInfo().getTaskMemory(),
>                       (int) tai.getTaskInfo().getTaskVCores());
>       containerList.add(
>               new ContainerSimulator(containerResource, containerLifeTime,
>               hostname, DEFAULT_REDUCER_PRIORITY, "reduce"));
> }
> {code}
>  
> In addition, the syn.json format supported only mapreduce (the parameters 
> were very specific: mtime, rtime, mtasks, rtasks, etc..).
> This patch aims to introduce a new syn.json format that can describe generic 
> jobs, and the SLS setup required to support the synth generation of generic 
> jobs.
> See syn_generic.json for an equivalent of the previous syn.json in the new 
> format.
> Using the new generic format, we describe a StreamAMSimulator simulates a 
> long running streaming service that maintains N number of containers for the 
> lifetime of the AM. See syn_stream.json.
>  



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