Author Archives: admin

  • 0

Select does not return any row in mr execution engine but returns in tez via beeline

When I ran a select statement via setting set hive.execution.engine=mr; then select * from table is not returning any rows in beeline but when I run it in tez then it is returning result.

0: jdbc:hive2://m1.hdp22:10001/default> select * from test_db.table1 limit 25;


| cus_id  | prx_nme  | fir_nme  | mid_1_nme  | mid_2_nme  | mid_3_nme  | lst_nme  | sfx_nme  | gen_nme  | lic_st_abr_id  | dsd_idc  |



No rows selected (0.108 seconds)

If you will check HiveServer2 logs then you will see following traces :

2017-08-31 09:02:02,239 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: parse.ParseDriver ( – Parsing command: select * from table1 limit

25 2017-08-31 09:02:02,241 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: metastore.HiveMetaStore ( – 3: get_table : db=test_db tbl=table1

2017-08-31 09:02:02,241 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: HiveMetaStore.audit ( – ugi=saurkumaip=unknown-ip-addrcmd=get_table : db=test_db tbl=table1

2017-08-31 09:02:02,260 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: metastore.HiveMetaStore ( – 3: get_table : db=test_db tbl=table1

2017-08-31 09:02:02,260 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: HiveMetaStore.audit ( – ugi=saurkumaip=unknown-ip-addrcmd=get_table : db=test_db tbl=table1

2017-08-31 09:02:02,269 INFO [HiveServer2-HttpHandler-Pool: Thread-104]: ql.Driver ( – Returning Hive schema: Schema(fieldSchemas:[FieldSchema(name:table1.cus_id, type:int, comment:null), FieldSchema(name:table1.prx_nme, type:char(15), comment:null), FieldSchema(name:table1.fir_nme, type:char(15), comment:null), FieldSchema(name:table1.mid_1_nme, type:char(15), comment:null), FieldSchema(name:table1.mid_2_nme, type:char(15), comment:null), FieldSchema(name:table1.mid_3_nme, type:char(15), comment:null), FieldSchema(name:table1.lst_nme, type:char(30), comment:null), FieldSchema(name:table1.sfx_nme, type:char(5), comment:null), FieldSchema(name:table1.gen_nme, type:char(10), comment:null), FieldSchema(name:table1.lic_st_abr_id, type:char(2), comment:null), FieldSchema(name:table1.dsd_idc, type:char(1), comment:null)], properties:null)

2017-08-31 09:02:02,271 INFO [HiveServer2-Background-Pool: Thread-161143]: ql.Driver ( – Starting command(queryId=hive_20170831090202_3dbbdf1c-c061-4289-b4dd-a2934cbec04d): select * from table1 limit 25

2017-08-31 09:02:02,278 INFO [Atlas Logger 2]: hook.HiveHook ( – Skipped query select * from table1 limit 25 for processing since it is a select query

Root Cause: Actually we ran insert overwrite which replaced all part files to same name dir and created files under those dirs. And as we are aware mr execution does not search recursively and thats why it was not returning any result in case of mr execution engine.

[s0998dnz@m1.hdp22 ~]$ hadoop fs -ls hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/
Found 50 items
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:08 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000000_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:08 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000001_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:08 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000002_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:08 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000003_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:09 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000004_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:09 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000005_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:09 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000006_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:09 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000007_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:10 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000008_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:10 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000009_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:10 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000010_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:10 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000011_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:11 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000012_0
drwxr-x— – dmcraig hdfs 0 2017-08-23 12:11 hdfs://m1.hdp22:8020/apps/hive/warehouse/test_db.db/table1/000013_0

Resolution: There are two solution we have to resolve this issue

  1. You can change the file structure by removeing dir and place file under the table dir.
  2. Or you can set following property SET mapred.input.dir.recursive=true; and then run sql. This property will tell to your engine to search recursively.

Please feel free to give your valuable suggestion or feedback.

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knox is not getting start, failing with error Gateway SSL Certificate is Expired

When you try to start knox then if it fails with following error then don’t worry, this article will help you to solve problem.

INFO hadoop.gateway ( logAndValidateCertificate(122)) – The Gateway SSL certificate is valid between:  FATAL hadoop.gateway ( (120)) – Failed to start gateway: ServiceLifecycleException: Gateway SSL Certificate is Expired.


Root cause: It is because of your gateway.jks file corrupted.

Resolution: So to solve this issue you need to follow given steps:

  • On the knox gateway locate the gateway.jks file — it is usually in the path /var/lib/knox/data*/security/keystores/gateway.jks

[knox@m1.hdp22 ~]$ ls -ltrh /var/lib/knox/data-*
-rw-r--r-- 1 knox knox 32 Aug 28 05:42 /var/lib/knox/data-
-rw-r--r-- 1 knox knox 1.4K Aug 28 05:42 /var/lib/knox/data-
-rw-r--r-- 1 knox knox 511 Aug 28 08:53 /var/lib/knox/data-

  • Move the original file gateway.jks to another directory as a backup copy
  • Restart the knox server

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Hive metastore critical alerts with ExecutionFailed: Execution of ‘export HIVE_CONF_DIR=’/usr/hdp/current/hive-metastore/conf

When you install Atlas and configure it then you may see following alert in Ambari Hive Service.

And once you check this alert details, you will see following error :

Metastore on m1.hdp22 failed (Traceback (most recent call last):
File “/var/lib/ambari-agent/cache/common-services/HIVE/”, line 200, in execute
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 155, in __init__
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 160, in run
self.run_action(resource, action)
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 124, in run_action
File “/usr/lib/python2.6/site-packages/resource_management/core/providers/”, line 262, in action_run
tries=self.resource.tries, try_sleep=self.resource.try_sleep)
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 72, in inner
result = function(command, **kwargs)
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 102, in checked_call
tries=tries, try_sleep=try_sleep, timeout_kill_strategy=timeout_kill_strategy)
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 150, in _call_wrapper
result = _call(command, **kwargs_copy)
File “/usr/lib/python2.6/site-packages/resource_management/core/”, line 303, in _call
raise ExecutionFailed(err_msg, code, out, err)
ExecutionFailed: Execution of ‘export HIVE_CONF_DIR=’/usr/hdp/current/hive-metastore/conf’ ; hive –hiveconf hive.metastore.uris=thrift://m1.hdp22:9083 –hiveconf hive.metastore.client.connect.retry.delay=1 –hiveconf hive.metastore.failure.retries=1 –hiveconf hive.metastore.connect.retries=1 –hiveconf hive.metastore.client.socket.timeout=14 –hiveconf hive.execution.engine=mr -e ‘show databases;” returned 1. log4j:WARN No such property [maxFileSize] in org.apache.log4j.DailyRollingFileAppender.
Logging initialized using configuration in file:/etc/hive/
Exception in thread “main” java.lang.ExceptionInInitializerError
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(
at org.apache.atlas.hive.hook.HiveHook.initialize(
at org.apache.atlas.hive.hook.HiveHook.<init>(
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(
at java.lang.reflect.Constructor.newInstance(
at java.lang.Class.newInstance(
at org.apache.hadoop.hive.ql.hooks.HookUtils.getHooks(
at org.apache.hadoop.hive.ql.Driver.getHooks(
at org.apache.hadoop.hive.ql.Driver.getHooks(
at org.apache.hadoop.hive.ql.Driver.execute(
at org.apache.hadoop.hive.ql.Driver.runInternal(
at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(
at org.apache.hadoop.hive.cli.CliDriver.processCmd(
at org.apache.hadoop.hive.cli.CliDriver.processLine(
at org.apache.hadoop.hive.cli.CliDriver.processLine(
at org.apache.hadoop.hive.cli.CliDriver.executeDriver(
at org.apache.hadoop.hive.cli.CliDriver.main(
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(
at sun.reflect.DelegatingMethodAccessorImpl.invoke(
at java.lang.reflect.Method.invoke(
at org.apache.hadoop.util.RunJar.main(
Caused by: java.lang.NullPointerException
at org.apache.atlas.hook.AtlasHook.<clinit>(
… 29 more

Root Cause: This happens when you have installed Atlas on that server where you do not have hive client. Actually you have org.apache.atlas.hive.hook.HiveHook in hive property.

Solution :  So to get rid of this alert we need to either remove this parameters from property but as we are using Atlas so we can’t delete it then another option is installed hive client on the same server where you have atlas server.


Please feel free to give your valuable feedback to improve articles.

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Sqoop import is failing after enabling atlas with ERROR security.InMemoryJAASConfiguration: Unable to add JAAS configuration

When you run Sqoop import with teradata or mysql/oracle then it might fail after installing and enabling atlas in your cluster with following error.
17/08/10 04:31:56 ERROR security.InMemoryJAASConfiguration: Unable to add JAAS configuration for client [KafkaClient] as it is missing param [atlas.jaas.KafkaClient.loginModuleName]. Skipping JAAS config for [KafkaClient]
17/08/10 04:31:58 INFO checking on the exit code
17/08/10 04:31:58 ERROR:Error with sqoop command :17/08/10 04:31:56 ERROR security.InMemoryJAASConfiguration: Unable to add JAAS configuration for client [KafkaClient] as it is missing param [atlas.jaas.KafkaClient.loginModuleName]. Skipping JAAS config for [KafkaClient]

Root Cause:

This issue is caused by authentication problems in atlas in case you have not enabled kerberos. Following parameters are set true causing the problem,You can check these parameters in /etc/sqoop/

[s0998dnz@m1.hdp22 ~]$ cat /etc/sqoop/
# Generated by Apache Ambari. Tue Aug 22 06:00:47 2017


Solution : If you do not have kerberos enabled in your cluster then you need to set them false or sometime setting them false does not work then you have to delete these properties from ambari with following method. 

Option 1. you manually need to edit the file and change the above mentioned properties to false.


But if still it is failing then you need to remove these properties from ambari like below:

Option 2: Login to ambari server and remove both parameters by running the below commands 

/var/lib/ambari-server/resources/scripts/ -u admin -p admin delete localhost <Your cluster Name> atlas.jaas.KafkaClient.option.renewTicket 

/var/lib/ambari-server/resources/scripts/ -u admin -p admin delete localhost <Your cluster Name> atlas.jaas.KafkaClient.option.useTicketCache

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/usr/hdp/ is failing with Exception in thread “main” java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/util/Bytes

When you have installed atlas on top of your cluster and you want to sync your hive data to atlas via following method then you may see following error after sometime(~20-30 mins) running your command.

[hive@m1.hdp22 ~]$ export HADOOP_CLASSPATH=`hadoop classpath`
[hive@m1.hdp22 ~]$ export HIVE_CONF_DIR=/etc/hive/conf
[hive@m1.hdp22 ~]$ /usr/hdp/
Using Hive configuration directory [/etc/hive/conf]
Log file for import is /usr/hdp/
Enter username for atlas :- saurkuma
Enter password for atlas :-

Exception in thread “main” java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/util/Bytes
at org.apache.hadoop.hive.hbase.HBaseSerDe.parseColumnsMapping(
at org.apache.hadoop.hive.hbase.HBaseSerDeParameters.<init>(
at org.apache.hadoop.hive.hbase.HBaseSerDe.initialize(
at org.apache.hadoop.hive.serde2.AbstractSerDe.initialize(
at org.apache.hadoop.hive.serde2.SerDeUtils.initializeSerDe(
at org.apache.hadoop.hive.metastore.MetaStoreUtils.getDeserializer(
at org.apache.hadoop.hive.metastore.MetaStoreUtils.getDeserializer(
at org.apache.hadoop.hive.ql.metadata.Table.getDeserializerFromMetaStore(
at org.apache.hadoop.hive.ql.metadata.Table.getDeserializer(
at org.apache.hadoop.hive.ql.metadata.Table.getColsInternal(
at org.apache.hadoop.hive.ql.metadata.Table.getCols(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.createOrUpdateTableInstance(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.createTableInstance(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.registerTable(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.importTable(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.importTables(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.importDatabases(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.importHiveMetadata(
at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.main(
Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.hbase.util.Bytes
at java.lang.ClassLoader.loadClass(
at sun.misc.Launcher$AppClassLoader.loadClass(
at java.lang.ClassLoader.loadClass(
… 19 more
Failed to import Hive Data Model!!!


Root Cause : This issue seems to be a bug . So, you need to apply hot fix on hive side. 

Resolution : To apply hot fix you can can download attached jar file ( hive-metastore-1.2.1000. from given URl for this issue, please follow below steps to replace the jar.

Steps to apply this hot fix:
1. Back up the hive-metastore jar from /usr/hdp/ to some place on hiveserver 2 and hive-metastor servers.
2. Download and copy the jar at same location .
3. restart hive-metastore,hive-server2.


Please feel free to give your valuable feedback or suggestion to improve article.

  • 0

Spark job run successfully in client mode but failing in cluster mode

If you build a pyspark application which can run successfully  in both the local and yarn-client modes.  However, when you try to run in cluster mode, then you may receive following errors :

  1. Error 1:  Exception: (“You must build Spark with Hive. Export ‘SPARK_HIVE=true’ and run build/sbt assembly”, Py4JJavaError(u’An error occurred while calling\n’, JavaObject id=o52))
  2. Error 2: INFO Client: Deleting staging directory .sparkStaging/application_1476997468030_139760
    Exception in thread “main” org.apache.spark.SparkException: Application application_1476997468030_139760 finished at
  3. Error 3: ERROR yarn.ApplicationMaster: User class threw exception: java.lang.RuntimeException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.metastore.HiveMetaStoreClient
    java.lang.RuntimeException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.metastore.HiveMetaStoreClient Caused by: java.lang.ClassNotFoundException: org.datanucleus.api.jdo.JDOPersistenceManagerFactory
  4. Error 4: INFO ApplicationMaster: Final app status: FAILED, exitCode: 1, (reason: User application exited with status 1)
    17/08/22 04:56:19 ERROR ApplicationMaster: Uncaught exception:
    org.apache.spark.SparkException: Exception thrown in awaitResult:
    at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:194)
    at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:401)
    at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$main$1.apply$mcV$sp(ApplicationMaster.scala:766)
    at org.apache.spark.deploy.SparkHadoopUtil$$anon$
    at org.apache.spark.deploy.SparkHadoopUtil$$anon$
    at Method)
    at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:66)
    at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:764)
    at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
    Caused by: org.apache.spark.SparkUserAppException: User application exited with 1

Root Cause : If you are using HDP stack then you might be hitting a bug with HDP 2.3.2 with Ambari 2.2.1 : where starting from Ambari 2.2.1 , it does not manage the spark version if HDP stack is < HDP 2.3.4.

If not then you are missing some drivers and hive parameters which you need to pass in command line during spark-submit in cluster mode.

Resolution : You can use following steps to solve this issue :

  • Check the hive-site.xml contents. Should be like as below for spark.
  • Add hive-site.xml to the driver-classpath so that spark can read hive configuration. Make sure —files must come before you .jar file.
  • Add the datanucleus jars using –jars option when you submit
  • Check the contents of hive-site.xml
  • The Seq. of command
    spark-submit \
    –class <> \
    –master yarn-cluster \
    –num-executors 1 \
    –driver-memory 1g \
    –executor-memory 1g \
    –executor-cores 1 \
    –files /usr/hdp/current/spark-client/conf/hive-site.xml \
    –jars /usr/hdp/current/spark-client/lib/datanucleus-api-jdo-3.2.6.jar,/usr/hdp/current/spark-client/lib/datanucleus-rdbms-3.2.9.jar,/usr/hdp/current/spark-client/lib/datanucleus-core-3.2.10.jar \
    target/YOUR_JAR-1.0.0-SNAPSHOT.jar “show tables”

Or complete command can be :

spark-submit --master yarn --deploy-mode cluster --queue di --jars /usr/hdp/current/spark-client/lib/datanucleus-rdbms-3.2.9.jar,/usr/hdp/current/spark-client/lib/datanucleus-core-3.2.10.jar,/usr/hdp/current/spark-client/lib/datanucleus-api-jdo-3.2.6.jar --conf "spark.yarn.appMasterEnv.PATH=/opt/rh/rh-python34/root/usr/bin${PATH:+:${PATH}}" --conf "spark.yarn.appMasterEnv.PATH=/opt/rh/rh-python34/root/usr/bin${PATH:+:${PATH}}" --conf "spark.yarn.appMasterEnv.LD_LIBRARY_PATH=/opt/rh/rh-python34/root/usr/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}" --conf "spark.yarn.appMasterEnv.MANPATH=/opt/rh/rh-python34/root/usr/share/man:${MANPATH}" --conf "spark.yarn.appMasterEnv.XDG_DATA_DIRS=/opt/rh/rh-python34/root/usr/share${XDG_DATA_DIRS:+:${XDG_DATA_DIRS}}" --conf "spark.yarn.appMasterEnv.PKG_CONFIG_PATH=/opt/rh/rh-python34/root/usr/lib64/pkgconfig${PKG_CONFIG_PATH:+:${PKG_CONFIG_PATH}}" --conf "spark.executorEnv.PATH=/opt/rh/rh-python34/root/usr/bin${PATH:+:${PATH}}" --conf "spark.executorEnv.PATH=/opt/rh/rh-python34/root/usr/bin${PATH:+:${PATH}}" --conf "spark.executorEnv.LD_LIBRARY_PATH=/opt/rh/rh-python34/root/usr/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}" --conf "spark.executorEnv.MANPATH=/opt/rh/rh-python34/root/usr/share/man:${MANPATH}" --conf "spark.executorEnv.XDG_DATA_DIRS=/opt/rh/rh-python34/root/usr/share${XDG_DATA_DIRS:+:${XDG_DATA_DIRS}}" --conf "spark.executorEnv.PKG_CONFIG_PATH=/opt/rh/rh-python34/root/usr/lib64/pkgconfig${PKG_CONFIG_PATH:+:${PKG_CONFIG_PATH}}"

where has following value :

[adebatch@server1 ~]$ cat 
from pyspark import SparkContext,SparkConf
from pyspark.sql import HiveContext
import json
import sys
conf = SparkConf()
sc = SparkContext(conf=conf)
hiveCtx = HiveContext(sc)
result = hiveCtx.sql('show databases')
#result = hiveCtx.sql('select * from default.table1 limit 1')'/tmp/pyspark', format='text', mode='overwrite')

Please feel free to give your valuable feedback.

  • 0

Unable to view OS Host information in the Ambari Dashboard(No data Available)

On the Ambari dashboard, the memory usage, Network Usage, CPU usage and Cluster Load information are missing.The dashboard displays the following error:

No data Available

Root Cause :
This issue occurs when there are some temporary files present in the AMS collector folder.


You need to stop ams service vi ambari and then remove all temp files.

mv /var/lib/ambari-metrics-collector /tmp/ambari-metrics-collector_OLD

Now you can restart ams service again and now you should be good with Ambari dashboard, the memory usage, Network Usage, CPU usage and Cluster Load information.


  • 0

Beeline java.lang.OutOfMemoryError: Requested array size exceeds VM limit

When we run beeline jobs very heavily then sometime we can see following error :

WARNING: Use "yarn jar" to launch YARN applications.
issuing: !connect jdbc:hive2://;transportMode=http;httpPath=gateway/default/hive?hive.execution.engine=tez;;hive.exec.parallel=true;hive.vectorized.execution.enabled=true;hive.vectorized.execution.reduce.enabled hdpdib [pass$
Connecting to jdbc:hive2://;transportMode=http;httpPath=gateway/default/hive?hive.execution.engine=tez;;hive.exec.parallel=true;hive.vectorized.execution.enabled=true;hive.vectorized.execution.reduce.enabled
17/07/01 20:00:05 [main]: INFO jdbc.Utils: Supplied authorities:
17/07/01 20:00:05 [main]: INFO jdbc.Utils: Resolved authority:
Connected to: Apache Hive (version
Driver: Hive JDBC (version
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
 at java.util.Arrays.copyOf(
 at org.apache.hive.beeline.BeeLine.getConsoleReader(
 at org.apache.hive.beeline.BeeLine.executeFile(
 at org.apache.hive.beeline.BeeLine.begin(
 at org.apache.hive.beeline.BeeLine.mainWithInputRedirection(
 at org.apache.hive.beeline.BeeLine.main(
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at sun.reflect.NativeMethodAccessorImpl.invoke(
 at sun.reflect.DelegatingMethodAccessorImpl.invoke(
 at java.lang.reflect.Method.invoke(
 at org.apache.hadoop.util.RunJar.main(

Root Cause : By default, the history file is located under ~/.beeline/history for that user who is facing this issue and beeline will load the latest 500 rows into memory. If those queries are super big, containing lots of characters, it is possible that the history file size will reach as big as a few GBs. When beeline is trying to load such big history file into memory, it will eventually fail with OutOfMemory error.

Currently Beeline does not provide an option to limit the max size for beeline history file, in the case that each query is very big, it will flood the history file and slow down beeline on start up and shutdown.

[root@m1 ]ls -ltrh /home/hdpdib/.beeline/
total 1.1G
-rw-r--r-- 1 hdpdib hdpuser 1.1G Jul1 03:15 history

Solution : So now for time-being to we have a workaround and that is to remove or clean the ~/.beeline/history file and then run again your jobs. Now you should be good for running jobs. 

[root@m1 ~]# rm /home/hdpdib/.beeline/history

Please feel free to reach out to me or give your valuable feedback.

  • 0

Run all service checks in bulk

In this blogs I tried to explain that how you can use ambari API to trigger all Service Checks with a single command.

In order to check the status and stability of any service in your cluster you need to run the service checks that are included in Ambari. Usually each Service provides its own service check in ambari and to run a service check you have to select the service (e.g. HDFS) in Ambari and click “Run Service Check” in the “Actions” dropdown menu.

But its a tedious job to run every service check one by one in case if we have many services. So I created this script by using Ambari API to start all available service checks via single script. Only thing you need to pass required parameters according to your env.


[s0998dnz@m1.hdp22 ~]$ ./
Enter Ambari server name : m1.hdp22
Enter Ambari admin's User Name: saurkuma
Enter Password for saurkuma : 
Your cluster name is: HDPTST
There are following running services :
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1315",
  "Requests" : {
    "id" : 1315,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1316",
  "Requests" : {
    "id" : 1316,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1317",
  "Requests" : {
    "id" : 1317,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1318",
  "Requests" : {
    "id" : 1318,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1319",
  "Requests" : {
    "id" : 1319,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1320",
  "Requests" : {
    "id" : 1320,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1321",
  "Requests" : {
    "id" : 1321,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1322",
  "Requests" : {
    "id" : 1322,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1323",
  "Requests" : {
    "id" : 1323,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1324",
  "Requests" : {
    "id" : 1324,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1325",
  "Requests" : {
    "id" : 1325,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1326",
  "Requests" : {
    "id" : 1326,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1327",
  "Requests" : {
    "id" : 1327,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1328",
  "Requests" : {
    "id" : 1328,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1329",
  "Requests" : {
    "id" : 1329,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1330",
  "Requests" : {
    "id" : 1330,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1331",
  "Requests" : {
    "id" : 1331,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1332",
  "Requests" : {
    "id" : 1332,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1333",
  "Requests" : {
    "id" : 1333,
    "status" : "Accepted"
  "href" : "http://m1.hdp22:8080/api/v1/clusters/HDPTST/requests/1334",
  "Requests" : {
    "id" : 1334,
    "status" : "Accepted"

Now if you will login to your ambari server you will see all service checks are running. So now you will be thinking which script is doing this magic,so don’t worry here is script. You use it and enjoy.

[s0998dnz@m1.hdp22 ~]$ cat 
#!/usr/bin/env bash
## Saurabh Singh ###
### Version 1.0 ####
echo -n "Enter Ambari server name : "
read "server"
echo -n "Enter Ambari admin's User Name: "
read "user"
echo -n "Enter Password for $user : "
read -s "pwd"
if [ -e "~/.ambari_login" ]; then
    . ~/.ambari_login

cluster_name=$(curl -s -u $LOGIN:$PASSWORD --insecure "http://$AMBARI_HOST:8080/api/v1/clusters"  | python -mjson.tool | perl -ne '/"cluster_name":.*?"(.*?)"/ && print "$1\n"')
if [ -z "$cluster_name" ]; then
echo -e "\nYour cluster name is: $cluster_name"

running_services=$(curl -s -u $LOGIN:$PASSWORD --insecure "http://$AMBARI_HOST:8080/api/v1/clusters/$cluster_name/services?fields=ServiceInfo/service_name&ServiceInfo/maintenance_state=OFF" | python -mjson.tool | perl -ne '/"service_name":.*?"(.*?)"/ && print "$1\n"')
if [ -z "$running_services" ]; then
echo "There are following running services :

for s in $running_services; do
    if [ "$s" == "ZOOKEEPER" ]; then
        post_body="{\"RequestInfo\":{\"context\":\"$s Service Check\",\"command\":\"${s}_QUORUM_SERVICE_CHECK\"},\"Requests/resource_filters\":[{\"service_name\":\"$s\"}]}"

        post_body="{\"RequestInfo\":{\"context\":\"$s Service Check\",\"command\":\"${s}_SERVICE_CHECK\"},\"Requests/resource_filters\":[{\"service_name\":\"$s\"}]}"
    curl -s -u $LOGIN:$PASSWORD --insecure -H "X-Requested-By:X-Requested-By" -X POST --data "$post_body"  "http://$AMBARI_HOST:8080/api/v1/clusters/$cluster_name/requests"

As always I welcome your valuable feedback or any suggestion.

  • 0

Enable Debug mode in beeline

Some time you have to troubleshoot beeline issue and then you think how to get into debug mode for beeline command shell as you have in hive (-hiveconf hive.root.logger=Debug,console). I know same is not going to work with beeline
So don’t worry following steps will help you and good part is you do not need to restart the hiveserve2.

Step 1: Login to your server and check whether you have file in /etc/hive/conf/ or not if not then copy the Beeline log4j property file from the given template.

[s0998dnz@m1.hdp22 ~]$ ll /etc/hive/conf/
ls: cannot access /etc/hive/conf/ No such file or directory
[s0998dnz@m1.hdp22 ~]$ ll /etc/hive/conf/
-rw-r--r-- 1 root root 1139 Nov 19  2014 /etc/hive/conf/
[s0998dnz@m1.hdp22 ~]$ cp /etc/hive/conf/ /etc/hive/conf/
cp: cannot create regular file `/etc/hive/conf/': Permission denied
[s0998dnz@m1.hdp22 ~]$ sudo su - hive
[hive@m1.hdp22 ~]$ cp /etc/hive/conf/ /etc/hive/conf/
[hive@m1.hdp22 ~]$ ll /etc/hive/conf/
-rw-r--r-- 1 hive hadoop 1139 May 31 03:34 /etc/hive/conf/
[hive@m1.hdp22 ~]$ cat /etc/hive/conf/
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

log4j.rootLogger=WARN, console

######## console appender ########
log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} [%t]: %p %c{2}: %m%n
[hive@m1.hdp22 ~]$

Step 2: Now open /etc/hive/conf/ and change log4j.rootLogger from WARN/INFO to DEBUG, console.
log4j.rootLogger=DEBUG, console

Save the changes, run Beeline client and debug output should be displayed.

Please feel free to give your valuable feedback or suggestion.