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

#
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# 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
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#    http://www.apache.org/licenses/LICENSE-2.0
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r"""
 Counts words in UTF8 encoded, '\n' delimited text received from the
 network every second.

 Usage: stateful_network_wordcount.py <hostname> <port>
   <hostname> and <port> describe the TCP server that Spark Streaming
    would connect to receive data.

 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/stateful_network_wordcount.py \
        localhost 9999`
"""
import sys
from typing import Iterable, Optional

from pyspark import SparkContext
from pyspark.streaming import StreamingContext

if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: stateful_network_wordcount.py <hostname> <port>", file=sys.stderr)
        sys.exit(-1)
    sc = SparkContext(appName="PythonStreamingStatefulNetworkWordCount")
    ssc = StreamingContext(sc, 1)
    ssc.checkpoint("checkpoint")

    # RDD with initial state (key, value) pairs
    initialStateRDD = sc.parallelize([(u'hello', 1), (u'world', 1)])

    def updateFunc(new_values: Iterable[int], last_sum: Optional[int]) -> int:
        return sum(new_values) + (last_sum or 0)

    lines = ssc.socketTextStream(sys.argv[1], int(sys.argv[2]))
    running_counts = lines.flatMap(lambda line: line.split(" "))\
                          .map(lambda word: (word, 1))\
                          .updateStateByKey(updateFunc, initialRDD=initialStateRDD)

    running_counts.pprint()

    ssc.start()
    ssc.awaitTermination()