Monthly Archives: July 2017

  • 2

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.


  • 2

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.