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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 1 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 3 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 ZooKeeper).
  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.

Spark executor gets killed all the time and Spark keeps retrying the failed stage; you may find 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 executor if it used more memory than the configured size of "spark.executor.memory" + "spark.yarn.executor.memoryOverhead".Increase "spark.yarn.executor.memoryOverhead" to make sure it covers the executor off-heap memory usage.

Run query and get an error like:

FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask

In Hive logs, it shows:

java.lang.NoClassDefFoundError: Could not initialize class org.xerial.snappy.Snappy
  at org.xerial.snappy.SnappyOutputStream.<init>(SnappyOutputStream.java:79)

Happens on Mac (not officially supported).

This is a general Snappy issue with Mac and is not unique to Hive on Spark, but workaround is noted here because it is needed for startup of Spark client.

Run this command before starting Hive or HiveServer2:

export HADOOP_OPTS="-Dorg.xerial.snappy.tempdir=/tmp -Dorg.xerial.snappy.lib.name=libsnappyjava.jnilib $HADOOP_OPTS"

Stack trace: ExitCodeException exitCode=1: .../launch_container.sh: line 27: $PWD:$PWD/__spark__.jar:$HADOOP_CONF_DIR.../usr/hdp/${hdp.version}/hadoop/lib/hadoop-lzo-0.6.0.${hdp.version}.jar:/etc/hadoop/conf/secure:$PWD/__app__.jar:$PWD/*: bad substitution

 

The key mapreduce.application.classpath in /etc/hadoop/conf/mapred-site.xml contains a variable which is invalid in bash.

From mapreduce.application.classpath remove

Code Block
:/usr/hdp/${hdp.version}/hadoop/lib/hadoop-lzo-0.6.0.${hdp.version}.jar

from

/etc/hadoop/conf/mapred-site.xml

Exception in thread "Driver" scala.MatchError: java.lang.NoClassDefFoundError: org/apache/hadoop/mapreduce/TaskAttemptContext (of class java.lang.NoClassDefFoundError)
  at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:432)

MR is not on the YARN classpath.

If on HDP change from

/hdp/apps/${hdp.version}/mapreduce/mapreduce.tar.gz#mr-framework

to

/hdp/apps/2.2.0.0-2041/mapreduce/mapreduce.tar.gz#mr-framework

java.lang.OutOfMemoryError: PermGen space with spark.master=localBy default (SPARK-1879), Spark's own launch scripts increase PermGen to 128 MB, so we need to increase PermGen in hive launch script.

If use JDK7, append following in conf/hive-env.sh:

Code Block
export HADOOP_OPTS="$HADOOP_OPTS -XX:MaxPermSize=128m"

If use JDK8, append following in Conf/hive-env.sh:

Code Block
export HADOOP_OPTS="$HADOOP_OPTS -XX:MaxMetaspaceSize=512m"

Recommended Configuration

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