[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Attachment: MR-2905.10-13-2011 Unit test included. Unit test found typo, which was fixed (assign map assign reduce, whatever) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job) --- Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Bug Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean Attachments: MR-2905.10-13-2011, MR-2905.patch, MR-2905.patch.2 We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Attachment: screenshot-1.jpg Unit test failure exposes the issue. When assignmultiple is true, a load manager might be asked to assign 3 maps in a loop, and it allows all of them. CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job) --- Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Bug Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean Attachments: MR-2905.10-13-2011, MR-2905.patch, MR-2905.patch.2, screenshot-1.jpg We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Attachment: MR-2905.patch.2 Checked grant for inclusion Fixed tab v. space issue per harsh CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job) --- Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Improvement Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean Attachments: MR-2905.patch, MR-2905.patch.2 We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Issue Type: Bug (was: Improvement) Ok. That's different from testing for regressions but maybe I can do both. I have the code it's just not in junit form. Stay tuned! CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job) --- Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Bug Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean Attachments: MR-2905.patch, MR-2905.patch.2 We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager cannot access running tasks (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Attachment: MR-2905.patch Please review and validate the approach. The problem is that when AssignMultiple is turned on, canAssignMap and canAssignReduce gets called in a loop which causes the task tracker status to go out of date as new tasks are marked for assignment. Tasks get added to the list, but don't actually get assigned until AssignTasks exits. Hence, the task tracker status falls out of date. Patch modifies CapBasedLoadManager to track the number of times canAssignMap and canAssignReduce returns true to the same task tracker. It assumes that when it returns true, there's potentially another running task that needs to be considered when deciding whether we can assign a new task to this tracker. CapBasedLoadManager cannot access running tasks (was: assignmultiple per job) - Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Improvement Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean Attachments: MR-2905.patch We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MAPREDUCE-2905) CapBasedLoadManager cannot access running tasks (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jeff Bean updated MAPREDUCE-2905: - Summary: CapBasedLoadManager cannot access running tasks (was: assignmultiple per job) (was: Allow mapred.fairscheduler.assignmultple to be set per job) CapBasedLoadManager cannot access running tasks (was: assignmultiple per job) - Key: MAPREDUCE-2905 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905 Project: Hadoop Map/Reduce Issue Type: Improvement Components: contrib/fair-share Affects Versions: 0.20.2 Reporter: Jeff Bean We encountered a situation where in the same cluster, large jobs benefit from mapred.fairscheduler.assignmultiple, but small jobs with small numbers of mappers do not: the mappers all clump to fully occupy just a few nodes, which causes those nodes to saturate and bottleneck. The desired behavior is to spread the job across more nodes so that a relatively small job doesn't saturate any node in the cluster. Testing has shown that setting mapred.fairscheduler.assignmultiple to false gives the desired behavior for small jobs, but is unnecessary for large jobs. However, since this is a cluster-wide setting, we can't properly tune. It'd be nice if jobs can set a param similar to mapred.fairscheduler.assignmultiple on submission to better control the task distribution of a particular job. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
