Catalin Alexandru Zamfir created SPARK-15582:
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Summary: Support for Groovy closures
Key: SPARK-15582
URL: https://issues.apache.org/jira/browse/SPARK-15582
Project: Spark
Issue Type: Improvement
Components: Input/Output, Java API
Affects Versions: 1.6.1
Environment: 6 node Debian 8 based Spark cluster
Reporter: Catalin Alexandru Zamfir
After fixing SPARK-13599 and testing a build against this fix for Groovy
dependencies, we see the Spark executors stuck at a ClassNotFound exception
when running as a Script (via GroovyShell.evalute ()). It seems Spark cannot
de-serialize the closure, or the closure is not received by the executor.
{noformat}
sparkContext.binaryFiles (ourPath).flatMap ({ onePathEntry -> code-block } as
FlatMapFunction).count ();
{ onePathEntry -> code-block } denotes a Groovy closure.
{noformat}
There is a groovy-spark example @
https://github.com/bunions1/groovy-spark-example
However the above uses a modified Groovy. If my understanding is correct,
Groovy compiles to native byte-code, which should be easy for Spark to pick-up
and use closures.
However, the above example code fails with this stack-trace:
{noformat}
Caused by: java.lang.ClassNotFoundException: Script1$_run_closure1
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at
org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:68)
at
java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:76)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:115)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214
{noformat}
Any ideas on how to tackle this, welcomed. I've tried Googling around for
similar issues, but nobody has found a solution.
At least, point me on where to "hack" to make Spark support closures and I'd
share some of my time to make it work. There is SPARK-2171 arguing that support
for this is out of the box, but for projects of a relative complex size where
the driver application is contained/part-of a bigger application and running on
a cluster, things do not seem to work. I don't know if SPARK-2171 has tried to
run outside of a local[] cluster set-up where such issues can arise.
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