Member since
09-25-2015
109
Posts
36
Kudos Received
8
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
1948 | 04-03-2018 09:08 PM | |
2565 | 03-14-2018 04:01 PM | |
8044 | 03-14-2018 03:22 PM | |
1899 | 10-30-2017 04:29 PM | |
963 | 10-17-2017 04:49 PM |
04-03-2018
09:12 PM
1 Kudo
hi @Aishwarya Dixit you can gracefully shutdown the region server, that will trigger hbase Mater to perform a bulk assignment of all regions hosted by that region server.
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04-03-2018
09:10 PM
Hi @Anurag Mishra please accept the answer if it resolved your issue.
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04-03-2018
09:08 PM
1 Kudo
Hi @Venkata Sudheer Kumar M CPU is capable of running multiple containers if the jobs are not cpu intensive. The stack advisor is only recommending to not go beyond "CPU(s) * 2". However, there is nothing stopping you from configuring higher. if you observe your container concurrency metrics and CPU utilization, you can identify your threshold of vcores to 1 CPU and set it accordingly. Note: yarn.nodemanager.resource.cpu-vcores would only be applicable if you enable CPU Scheduling.
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03-19-2018
09:01 PM
Hi @Anurag Mishra You can use value of 'yarn.resourcemanager.cluster-id' in jobTracker. # grep -A1 'yarn.resourcemanager.cluster-id' /etc/hadoop/conf/*
jobTracker=yarn-cluster However, "Failing over to rm2" is just a "INFO" message , that indicates rm1 is Standby. Your issue with oozie spark2 action would be different.
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03-19-2018
08:43 PM
Hi @Sergey Sheypak You may require hotfix on HDP with OOZIE-2606 OOZIE-2658 OOZIE-2787 OOZIE-2802. Please open a support case.
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03-19-2018
08:41 PM
Hi @Bijay Deo You may require hotfix on HDP with OOZIE-2606 OOZIE-2658 OOZIE-2787 OOZIE-2802. Please open a support case.
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03-19-2018
08:33 PM
Hi @Gagandeep Singh Chawla Did the above response help?
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03-19-2018
06:36 PM
Hi @Aishwarya Dixit Did it work ? You can always Shutdown the Region Server process, and Hbase Master will reassign all Regions to a different Region Server host.
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03-14-2018
04:08 PM
Please accept an Answer, so that we can mark this request close.
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03-14-2018
04:01 PM
Do you have the YARN Resource Manager screenshot when you run 3 mapred job? http://<Active_RM_HOST>:8088/cluster/scheduler From what i read from screen shots, Maximum AM Resource 20% i.e. 20% of 391GB = 78GB. value of: yarn.app.mapreduce.am.resource.mb and tez.am.resource.memory.mb will determine how many AMs can fit in to run concurrently.
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