Member since
12-20-2022
87
Posts
19
Kudos Received
9
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
411 | 05-08-2025 06:27 AM | |
460 | 04-02-2025 11:35 PM | |
409 | 03-23-2025 11:30 PM | |
504 | 03-06-2025 10:11 PM | |
1138 | 10-29-2024 11:53 PM |
04-23-2024
06:18 AM
Hi @DanhH , Please accept this as a solution if it helped.
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04-23-2024
06:18 AM
Hi @HadoopCommunity , If my solution. helped you Please accept it as a solution
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04-22-2024
11:27 AM
Hi @yagoaparecidoti , You dont have to run the balancer. The blocks will recognize the racks and it will be done automatically.
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04-22-2024
11:24 AM
Hi @JiHoone I think all your jobs that is running is allocated only the AM resources. Do one thing first set the "Configured Max AM limit" to 20%. Then set the Minimum user limit percent to 25% and run your jobs. Set user limit factor as 0.5.
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04-22-2024
10:24 AM
hi @AyazHussain since the problem is old, I don't remember what was done to fix it. if the problem returns, I will test. thanks!
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04-21-2024
10:02 PM
As a rule of thumb assign 80% of the node resources to YARN. Please go through this to modify the config according to your need. https://hadoop.apache.org/docs/r2.7.2/hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html#Queue_Properties
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04-16-2024
11:59 PM
1 Kudo
Hi @mike_bronson7 Please check that if the RM is working fine or is it down. Please also check your zookeeper. Please check with telnet if you can connect to RMhost from other host.
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02-15-2024
12:29 PM
1 Kudo
@Ivoz Has the reply helped resolve your issue? If so, please mark the appropriate reply as the solution, as it will make it easier for others to find the answer in the future. Thanks.
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02-08-2024
04:02 AM
2 Kudos
The application ask for container run some part in that container and then release it back. So the 28 vcores that you are seeing is due to that. Let's say your job asks for 4 containers and eack with 7 vcores so at first only two containers will run as you have limit of 15 vcores. but if one container is released then that job will take another container with 7 vcores so in total now the number of vcores used is 21.
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