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Brahma Reddy Battula edited comment on RANGER-3442 at 9/28/21, 9:28 AM: ------------------------------------------------------------------------ [~pavitheran] thanks for reporting and neat analysis. I do see that ranger_KMS using more memory and need to do profiling (pasting the heapdump here) , not sure it might to similar you reported but your analysis make sense to me. ( using ranger-0.7.0 with some patches.). In our cluster we've 16 keys, our heap usage is 60GB+.. How many keys present in your cluster..? {noformat} num #instances #bytes class name ---------------------------------------------- 1: 12514991 1125037584 [C 2: 3194026 629310896 [Ljava.util.HashMap$Node; 3: 4547927 421361800 [B 4: 12492061 399745952 java.lang.String 5: 7398577 355131696 java.util.HashMap$Node 6: 3189692 280692896 org.apache.zookeeper.data.Stat 7: 3197676 204651264 java.util.HashMap 8: 3207962 153982176 java.util.concurrent.ConcurrentHashMap$Node 9: 3189693 127587720 org.apache.curator.framework.recipes.cache.ChildData 10: 3190260 76566240 java.util.HashSet 11: 3189714 76553136 java.util.concurrent.atomic.AtomicReference 12: 1349 67582872 [Ljava.util.concurrent.ConcurrentHashMap$Node; 13: 1263345 40427040 org.apache.hadoop.io.Text 14: 23853 35543088 [Ljava.lang.Object; 15: 421113 33689040 org.apache.hadoop.security.token.delegation.web.DelegationTokenIdentifier 16: 421113 16844520 org.apache.hadoop.security.token.delegation.AbstractDelegationTokenSecretManager$DelegationTokenInformation num #instances #bytes class name ---------------------------------------------- 1: 12494150 1126339552 [C 2: 3189356 561492704 [Ljava.util.HashMap$Node; 3: 4627687 429962248 [B 4: 12470326 399050432 java.lang.String 5: 6811252 326940096 java.util.HashMap$Node 6: 3186259 280390792 org.apache.zookeeper.data.Stat 7: 3194119 204423616 java.util.HashMap 8: 3204325 153807600 java.util.concurrent.ConcurrentHashMap$Node 9: 3186257 127450280 org.apache.curator.framework.recipes.cache.ChildData 10: 3186819 76483656 java.util.HashSet 11: 3186279 76470696 java.util.concurrent.atomic.AtomicReference 12: 1420 67593664 [Ljava.util.concurrent.ConcurrentHashMap$Node; 13: 96175 43101976 [Ljava.lang.Object; 14: 1253046 40097472 org.apache.hadoop.io.Text 15: 417680 33414400 org.apache.hadoop.security.token.delegation.web.DelegationTokenIdentifier 16: 417680 16707200 org.apache.hadoop.security.token.delegation.AbstractDelegationTokenSecretManager$DelegationTokenInformation 17: 79595 14008720 java.net.SocksSocketImpl 18: 112616 7207424 java.lang.ref.Finalizer 19: 79591 7004008 java.net.SocketInputStream 20: 79591 7004008 java.net.SocketOutputStream 21: 414599 6633584 java.lang.Object 22: 79101 5695272 org.apache.tomcat.util.buf.ByteChunk 23: 67540 4322560 org.apache.tomcat.util.buf.CharChunk 24: 61120 3911680 org.apache.tomcat.util.buf.MessageBytes 25: 39328 3885784 [Ljava.lang.String; 26: 84221 3368840 java.util.ArrayList 27: 79610 3184400 java.io.FileDescriptor {noformat} was (Author: brahmareddy): [~pavitheran] thanks for reporting and neat analysis. I do see that ranger_KMS using more memory and need to do profiling (pasting the heapdump here) , not sure it might to similar you reported but your analysis make sense to me. ( using ranger-0.7.0 with some patches.) {noformat} num #instances #bytes class name ---------------------------------------------- 1: 12514991 1125037584 [C 2: 3194026 629310896 [Ljava.util.HashMap$Node; 3: 4547927 421361800 [B 4: 12492061 399745952 java.lang.String 5: 7398577 355131696 java.util.HashMap$Node 6: 3189692 280692896 org.apache.zookeeper.data.Stat 7: 3197676 204651264 java.util.HashMap 8: 3207962 153982176 java.util.concurrent.ConcurrentHashMap$Node 9: 3189693 127587720 org.apache.curator.framework.recipes.cache.ChildData 10: 3190260 76566240 java.util.HashSet 11: 3189714 76553136 java.util.concurrent.atomic.AtomicReference 12: 1349 67582872 [Ljava.util.concurrent.ConcurrentHashMap$Node; 13: 1263345 40427040 org.apache.hadoop.io.Text 14: 23853 35543088 [Ljava.lang.Object; 15: 421113 33689040 org.apache.hadoop.security.token.delegation.web.DelegationTokenIdentifier 16: 421113 16844520 org.apache.hadoop.security.token.delegation.AbstractDelegationTokenSecretManager$DelegationTokenInformation num #instances #bytes class name ---------------------------------------------- 1: 12494150 1126339552 [C 2: 3189356 561492704 [Ljava.util.HashMap$Node; 3: 4627687 429962248 [B 4: 12470326 399050432 java.lang.String 5: 6811252 326940096 java.util.HashMap$Node 6: 3186259 280390792 org.apache.zookeeper.data.Stat 7: 3194119 204423616 java.util.HashMap 8: 3204325 153807600 java.util.concurrent.ConcurrentHashMap$Node 9: 3186257 127450280 org.apache.curator.framework.recipes.cache.ChildData 10: 3186819 76483656 java.util.HashSet 11: 3186279 76470696 java.util.concurrent.atomic.AtomicReference 12: 1420 67593664 [Ljava.util.concurrent.ConcurrentHashMap$Node; 13: 96175 43101976 [Ljava.lang.Object; 14: 1253046 40097472 org.apache.hadoop.io.Text 15: 417680 33414400 org.apache.hadoop.security.token.delegation.web.DelegationTokenIdentifier 16: 417680 16707200 org.apache.hadoop.security.token.delegation.AbstractDelegationTokenSecretManager$DelegationTokenInformation 17: 79595 14008720 java.net.SocksSocketImpl 18: 112616 7207424 java.lang.ref.Finalizer 19: 79591 7004008 java.net.SocketInputStream 20: 79591 7004008 java.net.SocketOutputStream 21: 414599 6633584 java.lang.Object 22: 79101 5695272 org.apache.tomcat.util.buf.ByteChunk 23: 67540 4322560 org.apache.tomcat.util.buf.CharChunk 24: 61120 3911680 org.apache.tomcat.util.buf.MessageBytes 25: 39328 3885784 [Ljava.lang.String; 26: 84221 3368840 java.util.ArrayList 27: 79610 3184400 java.io.FileDescriptor {noformat} > Ranger KMS DAO memory issues when many new keys are created > ----------------------------------------------------------- > > Key: RANGER-3442 > URL: https://issues.apache.org/jira/browse/RANGER-3442 > Project: Ranger > Issue Type: Bug > Components: kms > Affects Versions: 2.0.0 > Reporter: Pavi Subenderan > Priority: Major > > We have many keys created in our KMS keystore and recently we found that when > we create new keys, the KMS instances easily hit against the memory limit. > We can reproduce this with a script to call KMS createKey and then > getMetadata for new keys in a loop. Basically we restart our instances and > memory usage is approximately 1.5GB out of 8GB, but after running this script > for a bit (1-5 minutes), we hit close to the 8GB limit and the memory usage > does not go back down after that. > I did a heap dump and saw that most of the memory was being retained by > XXRangerKeystore and eclipse EntityManagerImpl. > * org.eclipse.persistence.internal.jpa.EntityManagerImpl > * org.eclipse.persistence.internal.sessions.RepeatableWriteUnitOfWork > And the largest shallow size object was char[] with 4GB+... > > *My fix* > I was ultimately able to solve this issue by adding an > getEntityManager().clear() call in BaseDao.java getAllKeys(). > After I added this fix, we can now run as many KMS CreateKey / getMetadata > calls as we want without any increase in memory usage whatsoever. Memory > usage now stays constant at <1.7GB. > My understanding is that Ranger KMS has a many instances of ThreadLocal > EntityManager (160+ according to my heap dump) which each held a cache of the > results for getAllKeys. Since we have so many keys in our KMS, this would > easily put as at the memory limit. > Not sure if there are any drawbacks to clearing EntityManager in > BaseDao.getAllKeys() but we are seeing greatly improved performance in our > case since we aren't constantly hitting the memory limit anymore. -- This message was sent by Atlassian Jira (v8.3.4#803005)