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mike_bronson7
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Re: from where we get the Yarn memory value from t...

by Guru in Support Questions
‎10-26-2017 05:52 PM
‎10-26-2017 05:52 PM
I am little confuse in the value from yarn.nodemanager.resource.memory-mb is more then 120G and each worker machine only 32G , so how it can be that yarn.nodemanager.resource.memory-mb value much more the memory size of the worker machine ? ... View more

from where we get the Yarn memory value from the d...

by Guru in Support Questions
‎10-26-2017 04:18 PM
‎10-26-2017 04:18 PM
we have Ambari cluster with 5 workers machines ( each worker have 32G memory ) in the dashboard we see the yarn memory like this: 77% used 575G of 746G seems that the running application take 575G but how 575G if total workers have 32X5=160G and how the calculte is 746G ? on total ? ... View more

Re: Failed to start namenode. java.net.BindExcepti...

by Guru in Support Questions
‎10-26-2017 01:49 PM
‎10-26-2017 01:49 PM
Jay can you please help with the case - https://community.hortonworks.com/questions/142356/how-to-recover-the-standby-name-node-in-ambari-clu.html ... View more

Re: Failed to start namenode. java.net.BindExcepti...

by Guru in Support Questions
‎10-26-2017 01:46 PM
‎10-26-2017 01:46 PM
sorry you right ... View more

Failed to start namenode. java.net.BindException ...

by Guru in Support Questions
‎10-26-2017 01:33 PM
‎10-26-2017 01:33 PM
hi, when we start the namenode we get Port in use how to know which port is in use ? ERROR namenode.NameNode (NameNode.java:main(1774)) - Failed to start namenode. java.net.BindException: Port in use: master01.pp.com:50070 at org.apache.hadoop.http.HttpServer2.constructBindException(HttpServer2.java:983) at org.apache.hadoop.http.HttpServer2.bindForSinglePort(HttpServer2.java:1006) at org.apache.hadoop.http.HttpServer2.openListeners(HttpServer2.java:1063) at org.apache.hadoop.http.HttpServer2.start(HttpServer2.java:920) at org.apache.hadoop.hdfs.server.namenode.NameNodeHttpServer.start(NameNodeHttpServer.java:170) at org.apache.hadoop.hdfs.server.namenode.NameNode.startHttpServer(NameNode.java:933) at org.apache.hadoop.hdfs.server.namenode.NameNode.initialize(NameNode.java:746) at org.apache.hadoop.hdfs.server.namenode.NameNode.<init>(NameNode.java:992) at org.apache.hadoop.hdfs.server.namenode.NameNode.<init>(NameNode.java:976) at org.apache.hadoop.hdfs.server.namenode.NameNode.createNameNode(NameNode.java:1701) at org.apache.hadoop.hdfs.server.namenode.NameNode.main(NameNode.java:1769) Caused by: java.net.BindException: Address already in use at sun.nio.ch.Net.bind0(Native Method) at sun.nio.ch.Net.bind(Net.java:433) at sun.nio.ch.Net.bind(Net.java:425) at sun.nio.ch.ServerSocketChannelImpl.bind(ServerSocketChannelImpl.java:223) at sun.nio.ch.ServerSocketAdaptor.bind(ServerSocketAdaptor.java:74) at org.mortbay.jetty.nio.SelectChannelConnector.open(SelectChannelConnector.java:216) at org.apache.hadoop.http.HttpServer2.bindListener(HttpServer2.java:971) at org.apache.hadoop.http.HttpServer2.bindForSinglePort(HttpServer2.java:1002) ... 9 more ... View more
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Re: how to know who eat yarn memory

by Guru in Support Questions
‎10-25-2017 07:19 PM
‎10-25-2017 07:19 PM
thx for this details , I opened the page and I see many spark app opened , so do you think if I will restart the spark it will solved this isshue ... View more

how to know who eat yarn memory

by Guru in Support Questions
‎10-25-2017 11:02 AM
‎10-25-2017 11:02 AM
how to know who eat yarn memory ? I ask because we have exactly two ambari cluster on one ambari cluster yarn memory is almost 100% on the second yarn memory is 50% so how to know who eat the yarn memory on the first cluster? ... View more

Re: problem with yarn from ambari dashboard

by Guru in Support Questions
‎10-25-2017 09:58 AM
‎10-25-2017 09:58 AM
Jay not in this issue , but I will happy to get tour answer about my quastion from - https://community.hortonworks.com/questions/142356/how-to-recover-the-standby-name-node-in-ambari-clu.html ... View more

Re: problem with yarn from ambari dashboard

by Guru in Support Questions
‎10-25-2017 09:27 AM
‎10-25-2017 09:27 AM
so on each worker machine we have 32G ( lets say we allocate 7 to the OS ) so we have 25G , in my system we have 5 workers so this mean 25*5=125 , and this is actually what configured , am I corect ? ( we have in the cluster 3 master machines , 5 workers machines ) , in that case we need to increase each worker memory to at least 50G - am I correct ? and after that set the value of yarn.nodemanager.resource.memory-mb to 260G for example ... View more

Re: problem with yarn from ambari dashboard

by Guru in Support Questions
‎10-25-2017 09:18 AM
‎10-25-2017 09:18 AM
I update the question with more info ( like which application are runing under yarn and machine memory ) ... View more
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