class_docstr: This class wraps a function RDD[X] -> RDD[Y] that was passed to
  DStream.transform(), allowing it to be called from Java via Py4J's
  callback server.
  
  Java calls this function with a sequence of JavaRDDs and this function
  returns a single JavaRDD pointer back to Java.
class_docstr_tok: ["This","class","wraps","a","function","RDD","[","X","]","-",">","RDD","[","Y","]","that","was","passed","to","DStream.transform","(",")",",","allowing","it","to","be","called","from","Java","via","Py4J's","callback","server",".","Java","calls","this","function","with","a","sequence","of","JavaRDDs","and","this","function","returns","a","single","JavaRDD","pointer","back","to","Java","."]
code: def rdd_wrapper(self, func):
      self.rdd_wrap_func = func
      return self
  
file_path: spark/python/pyspark/streaming/util.py
imports: import time
  from datetime import datetime
  import traceback
  import sys
  from py4j.java_gateway import is_instance_of
  from pyspark import SparkContext, RDD
label_desc: Use image node_id 2 for calling the TransformFunction obj's underlying member method code with example usage: obj.rdd_wrapper(func) and returns: self