Versions Compared

Old Version 43

changes.mady.by.user Unknown User (chengxiang.li)

Saved on

compared with

New Version 44

changes.mady.by.user Lefty Leverenz

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.
Comment: minor edits in Common Issues

...

IssueCauseResolution
Error: Could not find or load main class org.apache.spark.deploy.SparkSubmitSpark dependency not correctly set.Add Spark dependency to Hive, see Step 3 above.

org.apache.spark.SparkException: Job aborted due to stage failure:

Task 5.0:0 had a not serializable result: java.io.NotSerializableException: org.apache.hadoop.io.BytesWritable

Spark serializer not set to Kryo.Set spark.serializer to be org.apache.spark.serializer.KryoSerializer, see Step 5 above.

[ERROR] Terminal initialization failed; falling back to unsupported
java.lang.IncompatibleClassChangeError: Found class jline.Terminal, but interface was expected

Hive has upgraded to Jline2 but jline 0.94 exists in the Hadoop lib.
  1. Delete jline from the Hadoop lib directory (it's only pulled in transitively from zk).
  2. export HADOOP_USER_CLASSPATH_FIRST=true
  3. If this error occurs during mvn test, perform a mvn clean install on the root project and itests directory.

java.lang.SecurityException: class "javax.servlet.DispatcherType"'s
signer information does not match signer information of other classes in the same package at java.lang.ClassLoader.checkCerts(ClassLoader.java:952)

Two versions of the servlet-api are in the classpath.
  1. This should be fixed by HIVE-8905.
  2. Remove the servlet-api-2.5.jar under hive/lib.

Spark executor get gets killed all the times time and Spark keep keeps retrying the failed stage, ; you may find the similar information in the YARN nodemanager log.

WARN org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Container [pid=217989,containerID=container_1421717252700_0716_01_50767235] is running beyond physical memory limits. Current usage: 43.1 GB of 43 GB physical memory used; 43.9 GB of 90.3 GB virtual memory used. Killing container.

For Spark on YARN, nodemanager would kill spark Spark executor if it use used more memory than the configured size of "spark.executor.memory" + "spark.yarn.executor.memoryOverhead".increase Increase "spark.yarn.executor.memoryOverhead" to make sure it cover covers the executor off-heap memory usage.

...