text: #
  # 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.
  #
  
  """
   Counts words in text encoded with UTF8 received from the network every second.
  
   Usage: recoverable_network_wordcount.py <hostname> <port> <checkpoint-directory> <output-file>
     <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive
     data. <checkpoint-directory> directory to HDFS-compatible file system which checkpoint data
     <output-file> file to which the word counts will be appended
  
   To run this on your local machine, you need to first run a Netcat server
      `$ nc -lk 9999`
  
   and then run the example
      `$ bin/spark-submit examples/src/main/python/streaming/recoverable_network_wordcount.py \
          localhost 9999 ~/checkpoint/ ~/out`
  
   If the directory ~/checkpoint/ does not exist (e.g. running for the first time), it will create
   a new StreamingContext (will print "Creating new context" to the console). Otherwise, if
   checkpoint data exists in ~/checkpoint/, then it will create StreamingContext from
   the checkpoint data.
  """
  import os
  import sys
  
  from pyspark import SparkContext
  from pyspark.streaming import StreamingContext
  
  
  # Get or register a Broadcast variable
  def getWordExcludeList(sparkContext):
      if ('wordExcludeList' not in globals()):
          globals()['wordExcludeList'] = sparkContext.broadcast(["a", "b", "c"])
      return globals()['wordExcludeList']
  
  
  # Get or register an Accumulator
  def getDroppedWordsCounter(sparkContext):
      if ('droppedWordsCounter' not in globals()):
          globals()['droppedWordsCounter'] = sparkContext.accumulator(0)
      return globals()['droppedWordsCounter']
  
  
  def createContext(host, port, outputPath):
      # If you do not see this printed, that means the StreamingContext has been loaded
      # from the new checkpoint
      print("Creating new context")
      if os.path.exists(outputPath):
          os.remove(outputPath)
      sc = SparkContext(appName="PythonStreamingRecoverableNetworkWordCount")
      ssc = StreamingContext(sc, 1)
  
      # Create a socket stream on target ip:port and count the
      # words in input stream of \n delimited text (e.g. generated by 'nc')
      lines = ssc.socketTextStream(host, port)
      words = lines.flatMap(lambda line: line.split(" "))
      wordCounts = words.map(lambda x: (x, 1)).reduceByKey(lambda x, y: x + y)
  
      def echo(time, rdd):
          # Get or register the excludeList Broadcast
          excludeList = getWordExcludeList(rdd.context)
          # Get or register the droppedWordsCounter Accumulator
          droppedWordsCounter = getDroppedWordsCounter(rdd.context)
  
          # Use excludeList to drop words and use droppedWordsCounter to count them
          def filterFunc(wordCount):
              if wordCount[0] in excludeList.value:
                  droppedWordsCounter.add(wordCount[1])
                  return False
              else:
                  return True
  
          counts = "Counts at time %s %s" % (time, rdd.filter(filterFunc).collect())
          print(counts)
          print("Dropped %d word(s) totally" % droppedWordsCounter.value)
          print("Appending to " + os.path.abspath(outputPath))
          with open(outputPath, 'a') as f:
              f.write(counts + "\n")
  
      wordCounts.foreachRDD(echo)
      return ssc
  
  if __name__ == "__main__":
      if len(sys.argv) != 5:
          print("Usage: recoverable_network_wordcount.py <hostname> <port> "
                "<checkpoint-directory> <output-file>", file=sys.stderr)
          sys.exit(-1)
      host, port, checkpoint, output = sys.argv[1:]
      ssc = StreamingContext.getOrCreate(checkpoint,
                                         lambda: createContext(host, int(port), output))
      ssc.start()
      ssc.awaitTermination()
  