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| Title | Views | Posted |
|---|---|---|
| 487 | 02-03-2020 05:52 AM |
02-03-2020
05:52 AM
1 Kudo
Ok, it seems I have fixed the issue myself: Somehow after the HDFS HA setup there have been two Hive metastore processes running on the same host. I stopped Spark2 and Hive services through Ambari, killed (SIGTERMED) the additional Metastore process, which was still running and started Hive and Spark2 services again.
... View more
01-31-2020
02:42 AM
Hi,
I configured HDFS HA on our HDP 3.1 cluster and since then the Spark2 Thrift server fails to start.
Our Spark setup still uses the Hive metastore (MySql database)
I did the HA configuration process according to the HDP / Cloudera documentation through Ambari and also ran
hive --config /etc/hive/conf/conf.server --service metatool -updateLocation hdfs://<nameservice-id>/apps/hive/warehouse hdfs://<namenode>:8020/apps/hive/warehouse
and
hive --config /etc/hive/conf/conf.server --service metatool -updateLocation hdfs://<nameservice-id>/apps/spark/warehouse hdfs://<namenode>:8020/apps/spark/warehouse
I suspect that the new namenode-id is still missing in some configuration entry somewhere.
The file /var/log/spark2/spark-spark-org.apache.spark.sql.hive.thriftserver.HiveThriftServer2-1...log contains the following exceptions:
20/01/31 11:27:13 INFO HiveClientImpl: Warehouse location for Hive client (versi
on 3.0.0) is /apps/spark/warehouse
20/01/31 11:27:13 INFO HiveMetaStoreClient: Trying to connect to metastore with
URI thrift://annamaster.lan.riscsw.shp:9083
20/01/31 11:27:13 INFO HiveMetaStoreClient: Opened a connection to metastore, cu
rrent connections: 1
20/01/31 11:27:13 INFO HiveMetaStoreClient: Connected to metastore.
20/01/31 11:27:13 INFO RetryingMetaStoreClient: RetryingMetaStoreClient proxy=cl
ass org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient ugi=spark (auth:SIMPLE) retries=1 delay=5 lifetime=0
20/01/31 11:27:13 WARN RetryingMetaStoreClient: MetaStoreClient lost connection. Attempting to reconnect (1 of 1) after 5s. getDatabase
org.apache.thrift.transport.TTransportException
at org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132)
at org.apache.thrift.transport.TTransport.readAll(TTransport.java:86)
at org.apache.thrift.protocol.TBinaryProtocol.readAll(TBinaryProtocol.java:429)
at org.apache.thrift.protocol.TBinaryProtocol.readI32(TBinaryProtocol.java:318)
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:219)
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:77)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_database(ThriftHiveMetastore.java:1163)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_database(ThriftHiveMetastore.java:1150)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1607)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1602)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:212)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient$SynchronizedHandler.invoke(HiveMetaStoreClient.java:2956)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at org.apache.hadoop.hive.ql.metadata.Hive.getDatabase(Hive.java:1875)
at org.apache.hadoop.hive.ql.metadata.Hive.databaseExists(Hive.java:1864)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply$mcZ$sp(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:278)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:216)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:215)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:261)
at org.apache.spark.sql.hive.client.HiveClientImpl.databaseExists(HiveClientImpl.scala:345)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply$mcZ$sp(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
at org.apache.spark.sql.hive.thriftserver.SparkSQLEnv$.init(SparkSQLEnv.scala:53)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.org$apache$spark$sql$hive$thriftserver$HiveThriftServer2$$startHiveThriftServer2(HiveThriftServer2.scala:106)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.main(HiveThriftServer2.scala:100)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2.main(HiveThriftServer2.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:904)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
20/01/31 11:27:18 INFO RetryingMetaStoreClient: RetryingMetaStoreClient trying reconnect as spark (auth:SIMPLE)
20/01/31 11:27:18 INFO HiveMetaStoreClient: Closed a connection to metastore, current connections: 0
20/01/31 11:27:18 INFO HiveMetaStoreClient: Trying to connect to metastore with URI thrift://annamaster.lan.riscsw.shp:9083
20/01/31 11:27:18 INFO HiveMetaStoreClient: Opened a connection to metastore, current connections: 1
20/01/31 11:27:18 INFO HiveMetaStoreClient: Connected to metastore.
20/01/31 11:27:18 WARN HiveClientImpl: HiveClient got thrift exception, destroying client and retrying (0 tries remaining)
org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.transport.TTransportException
at org.apache.hadoop.hive.ql.metadata.Hive.getDatabase(Hive.java:1879)
at org.apache.hadoop.hive.ql.metadata.Hive.databaseExists(Hive.java:1864)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply$mcZ$sp(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:278)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:216)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:215)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:261)
at org.apache.spark.sql.hive.client.HiveClientImpl.databaseExists(HiveClientImpl.scala:345)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply$mcZ$sp(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
at org.apache.spark.sql.hive.thriftserver.SparkSQLEnv$.init(SparkSQLEnv.scala:53)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.org$apache$spark$sql$hive$thriftserver$HiveThriftServer2$$startHiveThriftServer2(HiveThriftServer2.scala:106)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.main(HiveThriftServer2.scala:100)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2.main(HiveThriftServer2.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:904)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.thrift.transport.TTransportException
at org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132)
at org.apache.thrift.transport.TTransport.readAll(TTransport.java:86)
at org.apache.thrift.protocol.TBinaryProtocol.readAll(TBinaryProtocol.java:429)
at org.apache.thrift.protocol.TBinaryProtocol.readI32(TBinaryProtocol.java:318)
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:219)
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:77)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_database(ThriftHiveMetastore.java:1163)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_database(ThriftHiveMetastore.java:1150)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1607)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1602)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:212)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient$SynchronizedHandler.invoke(HiveMetaStoreClient.java:2956)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at org.apache.hadoop.hive.ql.metadata.Hive.getDatabase(Hive.java:1875)
... 30 more
20/01/31 11:27:23 WARN HiveClientImpl: Deadline exceeded
Exception in thread "main" org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.transport.TTransportException;
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:106)
at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
at org.apache.spark.sql.hive.thriftserver.SparkSQLEnv$.init(SparkSQLEnv.scala:53)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.org$apache$spark$sql$hive$thriftserver$HiveThriftServer2$$startHiveThriftServer2(HiveThriftServer2.scala:106)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2$.main(HiveThriftServer2.scala:100)
at org.apache.spark.sql.hive.thriftserver.HiveThriftServer2.main(HiveThriftServer2.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:904)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.transport.TTransportException
at org.apache.hadoop.hive.ql.metadata.Hive.getDatabase(Hive.java:1879)
at org.apache.hadoop.hive.ql.metadata.Hive.databaseExists(Hive.java:1864)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply$mcZ$sp(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$databaseExists$1.apply(HiveClientImpl.scala:346)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:278)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:216)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:215)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:261)
at org.apache.spark.sql.hive.client.HiveClientImpl.databaseExists(HiveClientImpl.scala:345)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply$mcZ$sp(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
... 17 more
Caused by: org.apache.thrift.transport.TTransportException
at org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132)
at org.apache.thrift.transport.TTransport.readAll(TTransport.java:86)
at org.apache.thrift.protocol.TBinaryProtocol.readAll(TBinaryProtocol.java:429)
at org.apache.thrift.protocol.TBinaryProtocol.readI32(TBinaryProtocol.java:318)
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:219)
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:77)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_database(ThriftHiveMetastore.java:1163)
at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_database(ThriftHiveMetastore.java:1150)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1607)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDatabase(HiveMetaStoreClient.java:1602)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:212)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient$SynchronizedHandler.invoke(HiveMetaStoreClient.java:2956)
at com.sun.proxy.$Proxy28.getDatabase(Unknown Source)
at org.apache.hadoop.hive.ql.metadata.Hive.getDatabase(Hive.java:1875)
... 30 more
20/01/31 11:27:23 INFO SparkContext: Invoking stop() from shutdown hook
... View more
06-04-2019
12:34 PM
I am currently doing an upgrade from HDP-2.6.0.3 to HDP-3.1.0.0 on a HDP Cluster Previously I installed HDF management pack for ambari (HDF version 3.1.0.0-564) and Nifi through the mpack MongoDB management pack from https://github.com/nikunjness/mongo-ambari Unfortunately did not read upgrade Guide for HDF before staring the upgrade. For the upgrade process I upgraded ambari to version 2.7.3.0 (without touching the mpacks) Before starting the HDP upgrade there was the warning that MongoDB and Nifi would be uninstalled because they don't belong to the HDP stack, which was fine for me. The HDP Upgrade, which I started after the ambari upgrade at first halted / failed in the step Remove unsupported services and components due to MongoDB and HDF. I paused the upgrade and uninstalled the MongoDB and Nifi Services through ambari as well as uninstalling the mongodb mpack and upgrading the hdp mpack to version 3.4.0.0-155. Then the HDP upgrade proceeded but failed at Update Target Repositories with a stdout of Updating the desired repository version to 3.1.0.0-78 for all cluster services. and a stderr of org.apache.ambari.server.ServiceNotFoundException: Service not found, clusterName=itpp, serviceName=MONGODB
at org.apache.ambari.server.state.cluster.ClusterImpl.getService(ClusterImpl.java:888)
at org.apache.ambari.server.state.UpgradeHelper.setDesiredRepositories(UpgradeHelper.java:922)
at org.apache.ambari.server.state.UpgradeHelper.updateDesiredRepositoriesAndConfigs(UpgradeHelper.java:894)
at org.apache.ambari.server.orm.AmbariJpaLocalTxnInterceptor.invoke(AmbariJpaLocalTxnInterceptor.java:118)
at org.apache.ambari.server.serveraction.upgrades.UpdateDesiredRepositoryAction.updateDesiredRepositoryVersion(UpdateDesiredRepositoryAction.java:160)
at org.apache.ambari.server.orm.AmbariJpaLocalTxnInterceptor.invoke(AmbariJpaLocalTxnInterceptor.java:128)
at org.apache.ambari.server.serveraction.upgrades.UpdateDesiredRepositoryAction.execute(UpdateDesiredRepositoryAction.java:96)
at org.apache.ambari.server.serveraction.ServerActionExecutor$Worker.execute(ServerActionExecutor.java:550)
at org.apache.ambari.server.serveraction.ServerActionExecutor$Worker.run(ServerActionExecutor.java:466)
at java.lang.Thread.run(Thread.java:745) I checked https://community.hortonworks.com/questions/202455/upgrade-from-hdp-264-to-300-fails-at-update-target.html but unfortunately the answers provided there where either not helpful for me or missing some details. I did check for MONGODB and NIFI in the tables servicecomponentdesiredstate
hostcomponentstate
hostcomponentdesiredstate
servicedesiredstate
clusterservices and did not find any related entries. It seems that there are still some references to Nifi and/or Mongodb somewhere the in ambari database. In the ambari-server.log there is also the error: Failed to obtain service info for stack HDP-2.6, service name NIFI
org.apache.ambari.server.StackAccessException: Stack data, stackName=HDP, stackVersion=2.6, serviceName=NIFI Any advice how to proceed or how to restart the upgrade (if advisable)?
... View more
05-29-2019
01:27 PM
We have the same issue with upgrading from HDP 2.6.0.3 to HDP 3.1.0.0. I had installed NIFI (from HDF) and MongoDB somewhen before the upgrade through Ambari management packs. The remove unsupported services step failed for these components, so we paused the upgrade and removed MongoDB and Nifi through ambari. After continuing the upgrade it fails again. Failed on: Update Target Repositories org.apache.ambari.server.ServiceNotFoundException: Service not found, clusterName=itpp, serviceName=MONGODB
at org.apache.ambari.server.state.cluster.ClusterImpl.getService(ClusterImpl.java:888)
at org.apache.ambari.server.state.UpgradeHelper.setDesiredRepositories(UpgradeHelper.java:922)
at org.apache.ambari.server.state.UpgradeHelper.updateDesiredRepositoriesAndConfigs(UpgradeHelper.java:894)
at org.apache.ambari.server.orm.AmbariJpaLocalTxnInterceptor.invoke(AmbariJpaLocalTxnInterceptor.java:118)
at org.apache.ambari.server.serveraction.upgrades.UpdateDesiredRepositoryAction.updateDesiredRepositoryVersion(UpdateDesiredRepositoryAction.java:160)
at org.apache.ambari.server.orm.AmbariJpaLocalTxnInterceptor.invoke(AmbariJpaLocalTxnInterceptor.java:128)
at org.apache.ambari.server.serveraction.upgrades.UpdateDesiredRepositoryAction.execute(UpdateDesiredRepositoryAction.java:96)
at org.apache.ambari.server.serveraction.ServerActionExecutor$Worker.execute(ServerActionExecutor.java:550)
at org.apache.ambari.server.serveraction.ServerActionExecutor$Worker.run(ServerActionExecutor.java:466)
at java.lang.Thread.run(Thread.java:745) We checked in the ambari database as @rguruvannagari suggested, but there are no entries for NIFI or MONGODB. It seems that the upgrade process still remembers the components. Is there a way to restart the upgrade process (possibly after reverting to 2.6 only if needed?) or to remove stale references to the services from the Ambari database or somewhere else?
... View more
03-15-2019
08:10 AM
Hi, thanks very much that resolved the issue.
... View more
03-14-2019
04:28 PM
I did shutdown all HDP Services and subsequently ambari-agents and ambari-server on a cluster due to some scheduled network maintainance. When starting the ambari-server and ambari-agents again, the ambari-agent on the headnode (also running ambari-server) did not register with the ambari-server (the server is not getting a request at all). The ambari-agent on the slavenode registers fine. Ambari version is 2.6.1.0 (recently upgraded according to HDP documentation, did work after that), HDP version 2.6.0.3 Python 2.7.5 / CentOS7 on headnode (ambari running as root): ambari-agent start produces Verifying Python version compatibility... Using python /usr/bin/python Checking for previously running Ambari Agent... Checking ambari-common dir... Starting ambari-agent Verifying ambari-agent process status... Ambari Agent successfully started Agent PID at: /run/ambari-agent/ambari-agent.pid Agent out at: /var/log/ambari-agent/ambari-agent.out Agent log at: /var/log/ambari-agent/ambari-agent.log ambari-agent status ambari-agent currently not running ps aux | grep ambari_agent root 15892 0.0 0.0 238584 17624 pts/4 S 11:29 0:00 /usr/bin/python /usr/lib/python2.6/site-packages/ambari_agent/AmbariAgent.py start root 15900 0.0 0.0 312740 18292 pts/4 Sl 11:29 0:00 /usr/bin/python /usr/lib/python2.6/site-packages/ambari_agent/main.py start There is no pid-file for ambari-agent, the directory /run/ambari-agent exists and the permissions (root:root 755) are fine, no stale pid file cat /var/log/ambari-agent/ambari-agent.log .... INFO 2019-03-14 13:09:26,515 main.py:145 - loglevel=logging.INFO INFO 2019-03-14 13:09:26,516 main.py:145 - loglevel=logging.INFO INFO 2019-03-14 13:09:26,516 main.py:145 - loglevel=logging.INFO INFO 2019-03-14 13:09:26,517 DataCleaner.py:39 - Data cleanup thread started INFO 2019-03-14 13:09:26,518 DataCleaner.py:120 - Data cleanup started INFO 2019-03-14 13:09:26,523 DataCleaner.py:122 - Data cleanup finished However, the loglevel of ambari-agent should be DEBUG: cat /etc/ambari-agent/conf/ambari-agent.ini ... loglevel=DEBUG ... - How can I increase the log-level of ambari-agent? - ambari-agent seems to be running, but not creating a PID file. - according to the ambari-server log, there seems to be no connection attempt from the ambari-agent. I did reinstall the ambari-agent, but that did not help. Any help appreciated.
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07-03-2018
08:29 AM
Hi,
We have setup a Phoenix table which we access through an external Hive
table using the org.apache.phoenix.hive.PhoenixStorageHandler.
We are using HBase version 1.1.2.2.6 and Hive version 1.2.1.2.6 (HDP 2.6.0.3).
When we are accessing the data in data_table (through Hive or Phoenix (sqlline))
using a sql statement with the first element of the Phoenix composite
row-key (mk0) in the where clause (mk0 = 12345) the performance is fine.
However we got an additional requirement for queries based on a different column (mk1), which is not part of the composite phoenix row key.
Therefore we created a lookup table (lookup_table) in Phoenix (also exposed though an external Hive table) with only a composite row key consisting of mk1 and mk0, in that order.
Using that lookup table the query in the phoenix shell select <md1> from <data_table> where <mk0> in (select <mk0> from <lookup_table> where <mk1> = 12345);
has an acceptable performance which is not really surprising since the
queries should access the the phoenix / hbase tables using a known
row-key prefix. The Phoenix query plan: CLIENT 22955-CHUNK 12756848943 ROWS 7200887136211 BYTES PARALLEL 1-WAY ROUND ROBIN FULL SCAN OVER
<data_table>
SKIP-SCAN-JOIN TABLE 0 CLIENT 1-CHUNK 0 ROWS 0 BYTES PARALLEL 1-WAY RANGE SCAN OVER <lookup_table> [12345]
SERVER FILTER BY FIRST KEY ONLY SERVER AGGREGATE INTO ORDERED DISTINCT ROWS BY [<mk0>] CLIENT MERGE SORT DYNAMIC SERVER FILTER BY <data_table>.<mk0> IN ($1.$3)
However when we use the same table setup through hive and
hive.PhoenixStorageHandler the query gets executed as map-reduce job
which takes way too long (using DISTINCT and ORDER BY does not change query performance in a noticeable fashion). Hive query: select b.<md1> from <data_table> as b where <mk0> in (select distinct t.<mk0> from <lookup_table> as t where t.<mk1> = 12345 order by mk0);
The Hive query plan: Plan not optimized by CBO.
Vertex dependency in root stage
Map 1 <- Reducer 4 (BROADCAST_EDGE)
Reducer 3 <- Map 2 (SIMPLE_EDGE)
Reducer 4 <- Reducer 3 (SIMPLE_EDGE)
Stage-0
Fetch Operator
limit:-1
Stage-1
Map 1
File Output Operator [FS_19]
compressed:false
Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
table:{"input format:":"org.apache.hadoop.mapred.TextInputFormat","output format:":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat","serde:":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"}
Select Operator [SEL_18]
outputColumnNames:["_col0"]
Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
Map Join Operator [MAPJOIN_24]
| condition map:[{"":"Left Semi Join 0 to 1"}]
| HybridGraceHashJoin:true
| keys:{"Map 1":"<mk0> (type: int)","Reducer 4":"_col0 (type: int)"}
| outputColumnNames:["_col11"]
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
|<-Reducer 4 [BROADCAST_EDGE]
| Reduce Output Operator [RS_15]
| key expressions:_col0 (type: int)
| Map-reduce partition columns:_col0 (type: int)
| sort order:+
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| Group By Operator [GBY_11]
| keys:_col0 (type: int)
| outputColumnNames:["_col0"]
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| Select Operator [SEL_9]
| | outputColumnNames:["_col0"]
| | Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| |<-Reducer 3 [SIMPLE_EDGE] vectorized
| Reduce Output Operator [RS_27]
| key expressions:_col0 (type: int)
| sort order:+
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| Group By Operator [OP_26]
| | keys:KEY._col0 (type: int)
| | outputColumnNames:["_col0"]
| | Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| |<-Map 2 [SIMPLE_EDGE]
| Reduce Output Operator [RS_5]
| key expressions:_col0 (type: int)
| Map-reduce partition columns:_col0 (type: int)
| sort order:+
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| Group By Operator [GBY_4]
| keys:<mk0> (type: int)
| outputColumnNames:["_col0"]
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| Filter Operator [FIL_23]
| predicate:<mk0> is not null (type: boolean)
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
| TableScan [TS_1]
| alias:t
| Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
|<-Filter Operator [FIL_22]
predicate:<mk0> is not null (type: boolean)
Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
TableScan [TS_0]
alias:b
Statistics:Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
Since the hive table sits on top of the phoenix table I had expected
hive to directly hand over the query to phoenix for execution and not
running a map-reduce job. Also according to the hive query plan, the equals condition in th e where clause is not used as filter for HBase.
We have set TEZ as execution engine and enabled CBO.
Is there a way to speed up the Hive query using basically data_table(lookup_table(rowKey)) instead of runnning a map-reduce job? Maybe indexing is another option, but would queries from hive actually use a Phoenix index? Maybe an index in Hive would be another option.
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03-09-2018
07:44 PM
Using HDP-2.6.0.3 I ran hbase org.apache.hadoop.hbase.util.LoadTestTool -compression NONE -write 8:8 -num_keys 1048576 generating an HBase table with the following characteristics: 1048576 rows row key length 39 bytes 8 columns/row with a mean size of 8 bytes each that should sum up to a storage requirement of approximately 1048576*(39+8*8) = 108003328 bytes =~ 103 MB When I check the storage usage for that HBase table in HDFS: hdfs dfs -du -h -s /apps/hbase/data/data/default/cluster_test gives 853.7 M /apps/hbase/data/data/default/cluster_test I have a HDFS replication factor of 3, however hdfs dfs -du should give the disk usage "before" replication anyways. HBase Region replication for the table is 1: hbase(main):001:0> describe 'cluster_test' Table cluster_test is ENABLED cluster_test, {TABLE_ATTRIBUTES => {DURABILITY => 'USE_DEFAULT', REGION_REPLICAT ION => '1'} COLUMN FAMILIES DESCRIPTION {NAME => 'test_cf', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'} 1 row(s) in 0.2240 seconds https://community.hortonworks.com/questions/46350/how-much-actual-space-required-to-store-10gb-to-hd.html mentiones higher disk usage in hbase. http://blog.cloudera.com/blog/2010/08/hadoophbase-capacity-planning/ mentiones doubling of disk usage during compactions. Could someone please clarify why the HBase table data is using nearly 9x the space in HDFS compared to the actual data being stored in the table? What do I miss here?
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