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change updateStateByKey() to easy API
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examples/src/main/python/streaming/stateful_network_wordcount.py
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# | ||
# 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. | ||
# | ||
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""" | ||
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` | ||
""" | ||
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import sys | ||
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from pyspark import SparkContext | ||
from pyspark.streaming import StreamingContext | ||
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if __name__ == "__main__": | ||
if len(sys.argv) != 3: | ||
print >> sys.stderr, "Usage: stateful_network_wordcount.py <hostname> <port>" | ||
exit(-1) | ||
sc = SparkContext(appName="PythonStreamingNetworkWordCount") | ||
ssc = StreamingContext(sc, 1) | ||
ssc.checkpoint("checkpoint") | ||
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def updateFunc(new_values, last_sum): | ||
return sum(new_values) + (last_sum or 0) | ||
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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) | ||
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running_counts.pprint() | ||
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ssc.start() | ||
ssc.awaitTermination() |
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