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Posted to dev@ambari.apache.org by "Alexander Denissov (JIRA)" <ji...@apache.org> on 2015/11/04 21:00:30 UTC
[jira] [Created] (AMBARI-13719) MAPREDUCE2 service check fails
sporadically with JDK1.8
Alexander Denissov created AMBARI-13719:
-------------------------------------------
Summary: MAPREDUCE2 service check fails sporadically with JDK1.8
Key: AMBARI-13719
URL: https://issues.apache.org/jira/browse/AMBARI-13719
Project: Ambari
Issue Type: Bug
Reporter: Alexander Denissov
Used PHD Ambari 2.1.2 with JDK 1.8 to create a cluster using blueprints. Cluster in AWS using r3.large instances (~17G of RAM).
Seems that stack advisor is not used during a blueprint deployment, so the services take default configurations. For MAPREDUCE2 the value of mapreduce.map.memory.mb is set to "512" and mapreduce.map.java.opts is set to "-Xmx410m"
Service checks are not run by default during blueprint deployment. When a service check REST API is called, the service check fails with mapper task running out of memory:
2015-11-03 18:53:56,256 FATAL [main] org.apache.hadoop.mapred.YarnChild: Error running child : java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.init(MapTask.java:986)
at org.apache.hadoop.mapred.MapTask.createSortingCollector(MapTask.java:402)
When connecting to the cluster via UI and re-running the service check, it sometimes succeeds and sometimes fails again.
This behavior is observed when using JDK1.8 -- the same environment, blueprint and tests work well with JDK 1.7
The behavior is observed with JDK 1.8 with the blueprint containing many services (HBase, Hive, etc). A blueprint with just HDFS/YARN/MR2/ZK seems not to have this issue on JDK 1.8.
Manually increasing the memory parameters (or adding configurations to the blueprint) seem to resolve the problem:
"mapred-site":{
"mapreduce.map.java.opts":"-Xmx819m",
"mapreduce.map.memory.mb":"1024"
}
However, we should get to the root cause of why using JDK1.8 causes OOM errors on default configuration.
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