examples/src/main/python/streaming/network_wordcount.py - master - githubmirror/spark

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

47 строк2 KB

Hyukjin Kwon

[SPARK-37836][PYTHON][INFRA] Enable F841, E722, E305 and E226 for PEP 8 compliance

07 янв 2022, 17:43

07 янв 2022, 17:439000339

#
# 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.
#

r"""
 Counts words in UTF8 encoded, '\n' delimited text received from the network every second.
 Usage: 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/network_wordcount.py localhost 9999`
"""
import sys

from pyspark import SparkContext
from pyspark.streaming import StreamingContext

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

    lines = ssc.socketTextStream(sys.argv[1], int(sys.argv[2]))
    counts = lines.flatMap(lambda line: line.split(" "))\
                  .map(lambda word: (word, 1))\
                  .reduceByKey(lambda a, b: a + b)
    counts.pprint()

    ssc.start()
    ssc.awaitTermination()