Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/1551#discussion_r15565797
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -344,7 +345,12 @@ private[spark] object PythonRDD extends Logging {
throw new SparkException("Unexpected Tuple2 element type " +
pair._1.getClass)
}
case other =>
- throw new SparkException("Unexpected element type " +
first.getClass)
+ if (other == null) {
+ dataOut.writeInt(SpecialLengths.NULL)
+ writeIteratorToStream(iter, dataOut)
--- End diff --
It's easy to call private API in Python, log4j can easily to do this via
reflection, just like we do in PySpark.
For example,
{{{
java_func = sc._jvm.com.xxx.XClass.XFunc
scala_rdd = py_rdd._jrdd.rdd().map(java_func)
java_rdd = sc._jvm.PythonRDD(scala_rdd, '', env, includes, ...).asJavaRDD()
rdd = RDD(java_rdd, sc, UTF8Deserializer())
}}}
If java_func can return null, then it will have NPE.
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