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add Python examples in Streaming Programming Guide
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examples/src/main/python/streaming/recoverable_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 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. | ||
""" | ||
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import os | ||
import sys | ||
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from pyspark import SparkContext | ||
from pyspark.streaming import StreamingContext | ||
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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) | ||
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# Create a socket stream on target ip:port and count the | ||
# words in input stream of \n delimited text (eg. 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) | ||
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def echo(time, rdd): | ||
counts = "Counts at time %s %s" % (time, rdd.collect()) | ||
print counts | ||
print "Appending to " + os.path.abspath(outputPath) | ||
with open(outputPath, 'a') as f: | ||
f.write(counts + "\n") | ||
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wordCounts.foreachRDD(echo) | ||
return ssc | ||
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if __name__ == "__main__": | ||
if len(sys.argv) != 5: | ||
print >> sys.stderr, "Usage: recoverable_network_wordcount.py <hostname> <port> "\ | ||
"<checkpoint-directory> <output-file>" | ||
exit(-1) | ||
host, port, checkpoint, output = sys.argv[1:] | ||
ssc = StreamingContext.getOrCreate(checkpoint, | ||
lambda: createContext(host, int(port), output)) | ||
ssc.start() | ||
ssc.awaitTermination() |
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