Added Python streaming mqtt word count example

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

@@ -0,0 +1,58 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+ A sample wordcount with MqttStream stream
+ Usage: mqtt_wordcount.py <broker url> <topic>
+ To work with Mqtt, Mqtt Message broker/server required.
+ Mosquitto (http://mosquitto.org/) is an open source Mqtt Broker
+ In ubuntu mosquitto can be installed using the command  `$ sudo apt-get install mosquitto`
+ Run Mqtt publisher as
+  `$ bin/run-example \
+       org.apache.spark.examples.streaming.MQTTPublisher tcp://localhost:1883 foo`
+ and then run the example as
+    `$ bin/spark-submit --driver-class-path external/mqtt-assembly/target/scala-*/\
+      spark-streaming-mqtt-assembly-*.jar examples/src/main/python/streaming/mqtt_wordcount.py \
+      tcp://localhost:1883 foo`
+"""
+
+import sys
+
+from pyspark import SparkContext
+from pyspark.streaming import StreamingContext
+from pyspark.streaming.mqtt import MQTTUtils
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print >> sys.stderr, "Usage: mqtt_wordcount.py <broker url> <topic>"
+        exit(-1)
+
+    sc = SparkContext(appName="PythonStreamingMQTTWordCount")
+    ssc = StreamingContext(sc, 1)
+
+    broker_url = sys.argv[1]
+    topic = sys.argv[2]
+
+    data = MQTTUtils.createStream(ssc, topic, broker_url)
+    lines = data.map(lambda x: x[1])
+    counts = lines.flatMap(lambda line: line.split(" ")) \
+        .map(lambda word: (word, 1)) \
+        .reduceByKey(lambda a, b: a+b)
+    counts.pprint()
+
+    ssc.start()
+    ssc.awaitTermination()