[SPARK-20525] ClassCast exception when interpreting UDFs from a String in spark-shell

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Incomplete
• Affects Version/s: 2.1.0
• Component/s: Spark Core, Spark Shell
• Labels: bulk-closed

Environment

OS X 10.11.6, spark-2.1.0-bin-hadoop2.7, Scala version 2.11.8 (bundled w/ Spark), Java 1.8.0_121

• Assignee: Unassigned
• Reporter: Dave Knoester
• Created: 28/Apr/17 16:56
• Updated: 22/Sep/20 18:16
• Resolved: 21/May/19 04:14

Description

I'm trying to interpret a string containing Scala code from inside a Spark session. Everything is working fine, except for User Defined Function-like things (UDFs, map, flatMap, etc). This is a blocker for production launch of a large number of Spark jobs.

I've been able to boil the problem down to a number of spark-shell examples, shown below. Because it's reproducible in the spark-shell, these related issues *don't apply*:

https://issues.apache.org/jira/browse/SPARK-9219
https://issues.apache.org/jira/browse/SPARK-18075
https://issues.apache.org/jira/browse/SPARK-19938
http://apache-spark-developers-list.1001551.n3.nabble.com/This-Exception-has-been-really-hard-to-trace-td19362.html
https://community.mapr.com/thread/21488-spark-error-scalacollectionseq-in-instance-of-orgapachesparkrddmappartitionsrdd
https://github.com/scala/bug/issues/9237

Any help is appreciated!

========
Repro:
Run each of the below from a spark-shell.

Preamble:

import scala.tools.nsc.GenericRunnerSettings
import scala.tools.nsc.interpreter.IMain
val settings = new GenericRunnerSettings( println _ )
settings.usejavacp.value = true
val interpreter = new IMain(settings, new java.io.PrintWriter(System.out))
interpreter.bind("spark", spark);

These work:

// works:
interpreter.interpret("val x = 5")

// works:
interpreter.interpret("import spark.implicits._\nval df = spark.sparkContext.parallelize(Seq(\"foo\",\"bar\")).toDF.show")

These do not work:

// doesn't work, fails with seq/RDD serialization error:
interpreter.interpret("import org.apache.spark.sql.functions.\nimport spark.implicits.\nval upper: String => String = _.toUpperCase\nval upperUDF = udf(upper)\nspark.sparkContext.parallelize(Seq(\"foo\",\"bar\")).toDF.withColumn(\"UPPER\", upperUDF($\"value\")).show")

// doesn't work, fails with seq/RDD serialization error:
interpreter.interpret("import org.apache.spark.sql.functions.\nimport spark.implicits.\nval upper: String => String = _.toUpperCase\nspark.udf.register(\"myUpper\", upper)\nspark.sparkContext.parallelize(Seq(\"foo\",\"bar\")).toDF.withColumn(\"UPPER\", callUDF(\"myUpper\", ($\"value\"))).show")

The not-working ones fail with this exception:

Caused by: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.List$SerializationProxy to field org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2237)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2155)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2013)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1535)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2231)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2155)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2013)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1535)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:422)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:80)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)

Issue Links

• duplicates: SPARK-18075 UDF doesn't work on non-local spark