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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
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * See the License for the specific language governing permissions and
 * limitations under the License.
package org.apache.spark.streaming.examples;
Counts words in UTF8 encoded, '\n' delimited text received from the network every second. Usage: NetworkWordCount <master> <hostname> <port> <master> is the Spark master URL. In local mode, <master> should be 'local[n]' with n > 1. <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 `$ ./run org.apache.spark.streaming.examples.JavaNetworkWordCount local[2] localhost 9999`
public final class JavaNetworkWordCount {
  private static final Pattern SPACE = Pattern.compile(" ");
  private JavaNetworkWordCount() {
  public static void main(String[] args) {
    if (args.length < 3) {
      ..println("Usage: JavaNetworkWordCount <master> <hostname> <port>\n" +
          "In local mode, <master> should be 'local[n]' with n > 1");
    // Create the context with a 1 second batch size
    JavaStreamingContext ssc = new JavaStreamingContext(args[0], "JavaNetworkWordCount",
            new Duration(1000), System.getenv("SPARK_HOME"),
    // Create a NetworkInputDStream on target ip:port and count the
    // words in input stream of \n delimited text (eg. generated by 'nc')
    JavaDStream<Stringlines = ssc.socketTextStream(args[1], Integer.parseInt(args[2]));
    JavaDStream<Stringwords = lines.flatMap(new FlatMapFunction<StringString>() {
      public Iterable<Stringcall(String x) {
        return Lists.newArrayList(.split(x));
    JavaPairDStream<StringIntegerwordCounts =
      new PairFunction<StringStringInteger>() {
        public Tuple2<StringIntegercall(String s) {
          return new Tuple2<StringInteger>(s, 1);
      }).reduceByKey(new Function2<IntegerIntegerInteger>() {
        public Integer call(Integer i1Integer i2) {
          return i1 + i2;
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