Hive execute "insert into ... values ..." very slow - hadoop

Question

I build a hadoop & hive cluster and try to do some test. But it's really slow.
table
table value_count
+--------------------------------------------------------------+--+
| createtab_stmt |
+--------------------------------------------------------------+--+
| CREATE TABLE `value_count`( |
| `key` int, |
| `count` int, |
| `create_date` date COMMENT '????') |
| COMMENT 'This is a group table' |
| ROW FORMAT SERDE |
| 'org.apache.hadoop.hive.ql.io.orc.OrcSerde' |
| STORED AS INPUTFORMAT |
| 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat' |
| OUTPUTFORMAT |
| 'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat' |
| LOCATION |
| 'hdfs://avatarcluster/hive/warehouse/test.db/value_count' |
| TBLPROPERTIES ( |
| 'COLUMN_STATS_ACCURATE'='{\"BASIC_STATS\":\"true\"}', |
| 'numFiles'='7', |
| 'numRows'='7', |
| 'rawDataSize'='448', |
| 'totalSize'='2297', |
| 'transient_lastDdlTime'='1496217645') |
+--------------------------------------------------------------+--+
sql execution
insert into value_count values (5, 1, '2017-05-06');
I've execute this sql for several times, each takes about 4 or 5 mins
hadoop container log
2017-05-31 16:00:45,041 [INFO] [Dispatcher thread {Central}] |app.DAGAppMaster|: Central Dispatcher queue size after DAG completion, before cleanup: 0
2017-05-31 16:00:45,041 [INFO] [Dispatcher thread {Central}] |app.DAGAppMaster|: Waiting for next DAG to be submitted.
2017-05-31 16:00:45,042 [INFO] [Dispatcher thread {Central}] |app.DAGAppMaster|: Cleaning up DAG: name=insert into value_count valu...'2017-05-06')(Stage-1), with id=dag_1490688643958_53401_1
2017-05-31 16:00:45,042 [INFO] [Dispatcher thread {Central}] |container.AMContainerMap|: Cleaned up completed containers on dagComplete. Removed=0, Remaining=1
2017-05-31 16:00:45,044 [INFO] [Dispatcher thread {Central}] |app.DAGAppMaster|: Completed cleanup for DAG: name=insert into value_count valu...'2017-05-06')(Stage-1), with id=dag_1490688643958_53401_1
2017-05-31 16:00:50,749 [INFO] [DelayedContainerManager] |rm.YarnTaskSchedulerService|: No taskRequests. Container's idle timeout delay expired or is new. Releasing container, containerId=container_1490688643958_53401_01_000002, containerExpiryTime=1496217650577, idleTimeout=5000, taskRequestsCount=0, heldContainers=1, delayedContainers=0, isNew=false
2017-05-31 16:00:50,752 [INFO] [Dispatcher thread {Central}] |history.HistoryEventHandler|: [HISTORY][DAG:dag_1490688643958_53401_1][Event:CONTAINER_STOPPED]: containerId=container_1490688643958_53401_01_000002, stoppedTime=1496217650751, exitStatus=0
2017-05-31 16:00:50,753 [INFO] [ContainerLauncher #1] |launcher.TezContainerLauncherImpl|: Stopping container_1490688643958_53401_01_000002
2017-05-31 16:00:50,753 [INFO] [ContainerLauncher #1] |impl.ContainerManagementProtocolProxy|: Opening proxy : app08.hp.sp.tst.bmsre.com:51640
2017-05-31 16:00:51,628 [INFO] [Dispatcher thread {Central}] |container.AMContainerImpl|: Container container_1490688643958_53401_01_000002 exited with diagnostics set to Container failed, exitCode=-105. Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2017-05-31 16:01:29,678 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 51 lastPreemptionHeartbeat: 50
2017-05-31 16:02:19,740 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 101 lastPreemptionHeartbeat: 100
2017-05-31 16:03:09,801 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 151 lastPreemptionHeartbeat: 150
2017-05-31 16:03:59,858 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 201 lastPreemptionHeartbeat: 200
2017-05-31 16:04:49,915 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 251 lastPreemptionHeartbeat: 250
2017-05-31 16:05:39,971 [INFO] [AMRM Callback Handler Thread] |rm.YarnTaskSchedulerService|: Allocated: <memory:0, vCores:0> Free: <memory:6144, vCores:1> pendingRequests: 0 delayedContainers: 0 heartbeats: 301 lastPreemptionHeartbeat: 300
2017-05-31 16:06:09,581 [INFO] [DAGSubmissionTimer] |rm.TaskSchedulerManager|: TaskScheduler notified that it should unregister from RM
2017-05-31 16:06:09,581 [INFO] [DAGSubmissionTimer] |app.DAGAppMaster|: No current running DAG, shutting down the AM
2017-05-31 16:06:09,581 [INFO] [DAGSubmissionTimer] |app.DAGAppMaster|: DAGAppMasterShutdownHandler invoked
2017-05-31 16:06:09,581 [INFO] [DAGSubmissionTimer] |app.DAGAppMaster|: Handling DAGAppMaster shutdown
2017-05-31 16:06:09,582 [INFO] [AMShutdownThread] |app.DAGAppMaster|: Sleeping for 5 seconds before shutting down
2017-05-31 16:06:14,582 [INFO] [AMShutdownThread] |app.DAGAppMaster|: Calling stop for all the services
2017-05-31 16:06:14,582 [INFO] [AMShutdownThread] |rm.YarnTaskSchedulerService|: Initiating stop of YarnTaskScheduler
2017-05-31 16:06:14,582 [INFO] [AMShutdownThread] |rm.YarnTaskSchedulerService|: Releasing held containers
2017-05-31 16:06:14,583 [INFO] [AMShutdownThread] |rm.YarnTaskSchedulerService|: Removing all pending taskRequests
2017-05-31 16:06:14,583 [INFO] [AMShutdownThread] |history.HistoryEventHandler|: Stopping HistoryEventHandler
2017-05-31 16:06:14,583 [INFO] [AMShutdownThread] |recovery.RecoveryService|: Stopping RecoveryService
2017-05-31 16:06:14,583 [INFO] [AMShutdownThread] |recovery.RecoveryService|: Handle the remaining events in queue, queue size=0
2017-05-31 16:06:14,584 [INFO] [RecoveryEventHandlingThread] |recovery.RecoveryService|: EventQueue take interrupted. Returning
2017-05-31 16:06:14,584 [INFO] [AMShutdownThread] |recovery.RecoveryService|: Closing Summary Stream
2017-05-31 16:06:14,611 [INFO] [AMShutdownThread] |impl.SimpleHistoryLoggingService|: Stopping SimpleHistoryLoggingService, eventQueueBacklog=0
2017-05-31 16:06:14,611 [INFO] [HistoryEventHandlingThread] |impl.SimpleHistoryLoggingService|: EventQueue take interrupted. Returning
2017-05-31 16:06:14,613 [INFO] [DelayedContainerManager] |rm.YarnTaskSchedulerService|: AllocatedContainerManager Thread interrupted
2017-05-31 16:06:14,615 [INFO] [AMShutdownThread] |rm.YarnTaskSchedulerService|: Unregistering application from RM, exitStatus=SUCCEEDED, exitMessage=Session stats:submittedDAGs=0, successfulDAGs=1, failedDAGs=0, killedDAGs=0
, trackingURL=
2017-05-31 16:06:14,620 [INFO] [AMShutdownThread] |impl.AMRMClientImpl|: Waiting for application to be successfully unregistered.
2017-05-31 16:06:14,720 [INFO] [AMShutdownThread] |rm.YarnTaskSchedulerService|: Successfully unregistered application from RM
2017-05-31 16:06:14,721 [INFO] [AMShutdownThread] |rm.TaskSchedulerManager|: Shutting down AppCallbackExecutor
2017-05-31 16:06:14,721 [INFO] [AMRM Callback Handler Thread] |impl.AMRMClientAsyncImpl|: Interrupted while waiting for queue
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.reportInterruptAfterWait(AbstractQueuedSynchronizer.java:2014)
at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2048)
at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
at org.apache.hadoop.yarn.client.api.async.impl.AMRMClientAsyncImpl$CallbackHandlerThread.run(AMRMClientAsyncImpl.java:274)
2017-05-31 16:06:14,726 [INFO] [AMShutdownThread] |mortbay.log|: Stopped HttpServer2$SelectChannelConnectorWithSafeStartup#0.0.0.0:0
2017-05-31 16:06:14,826 [INFO] [AMShutdownThread] |ipc.Server|: Stopping server on 49703
2017-05-31 16:06:14,827 [INFO] [IPC Server listener on 49703] |ipc.Server|: Stopping IPC Server listener on 49703
2017-05-31 16:06:14,827 [INFO] [AMShutdownThread] |ipc.Server|: Stopping server on 43709
2017-05-31 16:06:14,827 [INFO] [IPC Server Responder] |ipc.Server|: Stopping IPC Server Responder
2017-05-31 16:06:14,827 [INFO] [IPC Server listener on 43709] |ipc.Server|: Stopping IPC Server listener on 43709
2017-05-31 16:06:14,827 [INFO] [IPC Server Responder] |ipc.Server|: Stopping IPC Server Responder
2017-05-31 16:06:14,830 [INFO] [Thread-2] |app.DAGAppMaster|: DAGAppMasterShutdownHook invoked
2017-05-31 16:06:14,830 [INFO] [Thread-2] |app.DAGAppMaster|: The shutdown handler is still running, waiting for it to complete
2017-05-31 16:06:14,844 [INFO] [AMShutdownThread] |app.DAGAppMaster|: Completed deletion of tez scratch data dir, path=hdfs://avatarcluster/tmp/hive/hadoop/_tez_session_dir/46c45420-9bdf-40a5-83a5-c8d1d496abb8/.tez/application_1490688643958_53401
2017-05-31 16:06:14,844 [INFO] [AMShutdownThread] |app.DAGAppMaster|: Exiting DAGAppMaster..GoodBye!
2017-05-31 16:06:14,844 [INFO] [Thread-2] |app.DAGAppMaster|: The shutdown handler has completed
hadoop cluster schema
app05: NameNode/ResourceManager/JournalNode
app10: NameNode(Standby)/JournalNode
app08: DataNode/NodeManager/JournalNode
app09: DataNode/NodeManager
while app05/08/09/10 is my beta machine, each has 32 vcore and 48GB ram.
hadoop configuration
core-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://avatarcluster</value>
</property>
<property>
<name>io.file.buffer.size</name>
<value>131072</value>
</property>
<property>
<name>hadoop.proxyuser.hadoop.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.hadoop.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/home/hadoop/hadoop-data/</value>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>app02.hp.sp.tst.bmsre.com:2181</value>
</property>
<property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
</configuration>
hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>dfs.nameservices</name>
<value>avatarcluster</value>
</property>
<property>
<name>dfs.ha.namenodes.avatarcluster</name>
<value>nn1,nn2</value>
</property>
<property>
<name>dfs.namenode.rpc-address.avatarcluster.nn1</name>
<value>app05.hp.sp.tst.bmsre.com:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.avatarcluster.nn2</name>
<value>app10.hp.sp.tst.bmsre.com:8020</value>
</property>
<property>
<name>dfs.namenode.http-address.avatarcluster.nn1</name>
<value>app05.hp.sp.tst.bmsre.com:50070</value>
</property>
<property>
<name>dfs.namenode.http-address.avatarcluster.nn2</name>
<value>app10.hp.sp.tst.bmsre.com:50070</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://app05.hp.sp.tst.bmsre.com:8485;app10.hp.sp.tst.bmsre.com:8485;app08.hp.sp.tst.bmsre.com:8485/avatarcluster
</value>
</property>
<property>
<name>dfs.client.failover.proxy.provider.avatarcluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/home/hadoop/.ssh/id_rsa</value>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/home/hadoop/hadoop/journal-data</value>
</property>
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>/home/hadoop/hadoop/namenode</value>
</property>
<property>
<name>dfs.blocksize</name>
<value>134217728</value>
</property>
<property>
<name>dfs.namenode.handler.count</name>
<value>100</value>
</property>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
</configuration>
maprd-site.xml
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>app05.hp.sp.tst.bmsre.com:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>app05.hp.sp.tst.bmsre.com:19888</value>
</property>
<property>
<name>mapreduce.jobhistory.intermediate-done-dir</name>
<value>/mr-history/tmp</value>
</property>
<property>
<name>mapreduce.jobhistory.done-dir</name>
<value>/mr-history/done</value>
</property>
<property>
<name>mapred.output.compress</name>
<value>true</value>
</property>
<property>
<name>mapred.output.compression.codec</name>
<value>org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
<property>
<name>mapred.compress.map.output</name>
<value>true</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>3048</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>3048</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx2024m</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx2024m</value>
</property>
</configuration>
tez-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>tez.lib.uris</name>
<value>${fs.defaultFS}/apps/tez-0.8.5.tar.gz</value>
</property>
<property>
<name>tez.am.resource.memory.mb</name>
<value>2048</value>
</property>
<property>
<name>tez.task.resource.memory.mb</name>
<value>2048</value>
</property>
</configuration>
yarn-site.xml
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>yarn.admin.acl</name>
<value>*</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>app05.hp.sp.tst.bmsre.com:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>app05.hp.sp.tst.bmsre.com:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>app05.hp.sp.tst.bmsre.com:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>app05.hp.sp.tst.bmsre.com:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>app05.hp.sp.tst.bmsre.com:8088</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/home/hadoop/hadoop/nodemanager-workdir</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/home/hadoop/hadoop/nodemanager-logs</value>
</property>
<property>
<name>yarn.nodemanager.log.retain-seconds</name>
<value>3600</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/home/hadoop/hadoop/nodemanager-remote-app-logs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir-suffix</name>
<value>logs</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>4096</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1024</value>
</property>
</configuration>

Answer 1

I am not sure about your cluster configuration (nodes, memory, cpus), it would be useful if you can update the post with that information. In the meantime, the first guess is that your Tez configuration is wrong, so I would suggest decrease the MB to something smaller (few mbs should be enough for tiny data). Also, try to run the same command using the mapred engine in order to limit the problem
hive.execution.engine=mr

Answer 2

Hive can use the Apache Tez execution engine instead of the venerable Map-reduce engine. I won’t go into details about the many benefits of using Tez which are mentioned here; instead, I want to make a simple recommendation: if it’s not turned on by default in your environment, use Tez by setting to ‘true’ the following in the beginning of your Hive query:
set hive.execution.engine=tez;

Answer 3

In general, when you use
insert into values
it tends to create small files everytime you execute a statement. Since Hive does not created any constraints and indices, the statements keep on adding the small files.
In case ACID properties are enabled for the table, it also tries to do compaction in periodic times where it tries to combine all small-delta file into one big file. This process sometimes can be time-consuming.
Hence it is better to create a file on local use
LOAD DATA LOCAL INPATH '/FILE/PATH' INTO TABLE TABLE_NAME ;
Hope this helps.

Answer 4

I know this is two year old posting, but leaving answer for sharing, and incase I forget myself in the future.
In your log, Tez session is waiting for next DAG (or query) to be submitted until the session times out.
Tez tends to reuse Application Master and Containers for speeding up job execution, so it's waiting for next job.
For me this happened when submitting queries through Hue interface. Since Hue web session is still open, it make sense to keep AM alive during session.
You can disable or reduce wait time using tez.session.am.dag.submit.timeout.secs. Default is 300 secs, which is exactly how long your job took to finish.
You wouldn't see this problem if query is submitted through script (python, java) since the script will execute and just exit after the query is complete.