added reducedByKey not working yet

examples/src/main/python/streaming/wordcount.py

@@ -1,22 +1,30 @@
 import sys
 from operator import add
 
+from pyspark.conf import SparkConf
 from pyspark.streaming.context import StreamingContext
 from pyspark.streaming.duration import *
 
 if __name__ == "__main__":
     if len(sys.argv) != 2:
         print >> sys.stderr, "Usage: wordcount <directory>"
         exit(-1)
-    ssc = StreamingContext(appName="PythonStreamingWordCount", duration=Seconds(1))
+    conf = SparkConf()
+    conf.setAppName("PythonStreamingWordCount")
+    conf.set("spark.default.parallelism", 1)
+
+#    ssc = StreamingContext(appName="PythonStreamingWordCount", duration=Seconds(1))
+    ssc = StreamingContext(conf=conf, duration=Seconds(1))
 
     lines = ssc.textFileStream(sys.argv[1])
     fm_lines = lines.flatMap(lambda x: x.split(" "))
     filtered_lines = fm_lines.filter(lambda line: "Spark" in line)
     mapped_lines = fm_lines.map(lambda x: (x, 1))
+    reduced_lines = mapped_lines.reduce(add)
 
     fm_lines.pyprint()
     filtered_lines.pyprint()
     mapped_lines.pyprint()
+    reduced_lines.pyprint()
     ssc.start()
     ssc.awaitTermination()

python/pyspark/streaming/dstream.py

@@ -29,6 +29,7 @@
 
 __all__ = ["DStream"]
 
+
 class DStream(object):
     def __init__(self, jdstream, ssc, jrdd_deserializer):
         self._jdstream = jdstream
@@ -149,7 +150,7 @@ def _combineByKey(self, createCombiner, mergeValue, mergeCombiners,
         """
         """
         if numPartitions is None:
-            numPartitions = self.ctx._defaultParallelism()
+            numPartitions = self._defaultReducePartitions()
         def combineLocally(iterator):
             combiners = {}
             for x in iterator:
@@ -211,7 +212,6 @@ def add_shuffle_key(split, iterator):
         return dstream
 
 
-
     def reduceByWindow(self, reduceFunc, windowDuration, slideDuration, inReduceTunc):
         """
         """
@@ -254,8 +254,31 @@ def wrapRDD(self, rdd):
         raise NotImplementedError
 
     def mapPartitionsWithIndex(self, f, preservesPartitioning=False):
+        """
+
+        """
         return PipelinedDStream(self, f, preservesPartitioning)
 
+    def _defaultReducePartitions(self):
+        """
+
+        """
+        # hard code to avoid the error
+        return 2
+        if self.ctx._conf.contains("spark.default.parallelism"):
+            return self.ctx.defaultParallelism
+        else:
+            return self.getNumPartitions()
+
+    def getNumPartitions(self):
+      """
+      Returns the number of partitions in RDD
+      >>> rdd = sc.parallelize([1, 2, 3, 4], 2)
+      >>> rdd.getNumPartitions()
+      2
+      """
+      return self._jdstream.partitions().size()
+
 
 class PipelinedDStream(DStream):
     def __init__(self, prev, func, preservesPartitioning=False):

streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala

@@ -129,7 +129,7 @@ class PythonDStream[T: ClassTag](
   }
 }
 
-/*
+
 private class PairwiseDStream(prev:DStream[Array[Byte]]) extends
 DStream[(Long, Array[Byte])](prev.ssc){
   override def dependencies = List(prev)
@@ -144,9 +144,9 @@ DStream[(Long, Array[Byte])](prev.ssc){
       case None => None
     }
   }
-  val asJavaPairDStream : JavaPairDStream[Long, Array[Byte]] = JavaPairDStream(this)
+  val asJavaPairDStream : JavaPairDStream[Long, Array[Byte]]  = JavaPairDStream.fromJavaDStream(this)
 }
-*/
+