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Davies Liu
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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: network_wordcount.py <zk> <topic> | ||
To run this on your local machine, you need to setup Kafka and create a producer first | ||
$ bin/zookeeper-server-start.sh config/zookeeper.properties | ||
$ bin/kafka-server-start.sh config/server.properties | ||
$ bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test | ||
and then run the example | ||
`$ bin/spark-submit --driver-class-path lib_managed/jars/kafka_*.jar:\ | ||
external/kafka/target/scala-*/spark-streaming-kafka_*.jar examples/src/main/python/\ | ||
streaming/kafka_wordcount.py localhost:2181 test` | ||
""" | ||
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import sys | ||
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from pyspark import SparkContext | ||
from pyspark.streaming import StreamingContext | ||
from pyspark.streaming.kafka import KafkaUtils | ||
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if __name__ == "__main__": | ||
if len(sys.argv) != 3: | ||
print >> sys.stderr, "Usage: network_wordcount.py <zk> <topic>" | ||
exit(-1) | ||
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sc = SparkContext(appName="PythonStreamingKafkaWordCount") | ||
ssc = StreamingContext(sc, 1) | ||
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zkQuorum, topic = sys.argv[1:] | ||
lines = KafkaUtils.createStream(ssc, zkQuorum, "spark-streaming-consumer", {topic: 1}) | ||
counts = lines.map(lambda x: x[1]).flatMap(lambda line: line.split(" ")) \ | ||
.map(lambda word: (word, 1)) \ | ||
.reduceByKey(lambda a, b: a+b) | ||
counts.pprint() | ||
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ssc.start() | ||
ssc.awaitTermination() |
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