content: /*
   * 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.
   */
  
  package org.apache.spark.examples.streaming;
  
  import java.util.Arrays;
  import java.util.Iterator;
  import java.util.List;
  import java.util.regex.Pattern;
  
  import scala.Tuple2;
  
  import org.apache.spark.SparkConf;
  import org.apache.spark.api.java.function.*;
  import org.apache.spark.api.java.JavaPairRDD;
  import org.apache.spark.api.java.Optional;
  import org.apache.spark.api.java.StorageLevels;
  import org.apache.spark.streaming.Durations;
  import org.apache.spark.streaming.State;
  import org.apache.spark.streaming.StateSpec;
  import org.apache.spark.streaming.api.java.*;
  
  /**
   * Counts words cumulatively in UTF8 encoded, '\n' delimited text received from the network every
   * second starting with initial value of word count.
   * Usage: JavaStatefulNetworkWordCount <hostname> <port>
   * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive
   * data.
   * <p>
   * To run this on your local machine, you need to first run a Netcat server
   * `$ nc -lk 9999`
   * and then run the example
   * `$ bin/run-example
   * org.apache.spark.examples.streaming.JavaStatefulNetworkWordCount localhost 9999`
   */
  public class JavaStatefulNetworkWordCount {
    private static final Pattern SPACE = Pattern.compile(" ");
  
    public static void main(String[] args) throws Exception {
      if (args.length < 2) {
        System.err.println("Usage: JavaStatefulNetworkWordCount <hostname> <port>");
        System.exit(1);
      }
  
      StreamingExamples.setStreamingLogLevels();
  
      // Create the context with a 1 second batch size
      SparkConf sparkConf = new SparkConf().setAppName("JavaStatefulNetworkWordCount");
      JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
      ssc.checkpoint(".");
  
      // Initial state RDD input to mapWithState
      @SuppressWarnings("unchecked")
      List<Tuple2<String, Integer>> tuples =
          Arrays.asList(new Tuple2<>("hello", 1), new Tuple2<>("world", 1));
      JavaPairRDD<String, Integer> initialRDD = ssc.sparkContext().parallelizePairs(tuples);
  
      JavaReceiverInputDStream<String> lines = ssc.socketTextStream(
              args[0], Integer.parseInt(args[1]), StorageLevels.MEMORY_AND_DISK_SER_2);
  
      JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
        @Override
        public Iterator<String> call(String x) {
          return Arrays.asList(SPACE.split(x)).iterator();
        }
      });
  
      JavaPairDStream<String, Integer> wordsDstream = words.mapToPair(
          new PairFunction<String, String, Integer>() {
            @Override
            public Tuple2<String, Integer> call(String s) {
              return new Tuple2<>(s, 1);
            }
          });
  
      // Update the cumulative count function
      Function3<String, Optional<Integer>, State<Integer>, Tuple2<String, Integer>> mappingFunc =
          new Function3<String, Optional<Integer>, State<Integer>, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> call(String word, Optional<Integer> one,
                State<Integer> state) {
              int sum = one.orElse(0) + (state.exists() ? state.get() : 0);
              Tuple2<String, Integer> output = new Tuple2<>(word, sum);
              state.update(sum);
              return output;
            }
          };
  
      // DStream made of get cumulative counts that get updated in every batch
      JavaMapWithStateDStream<String, Integer, Integer, Tuple2<String, Integer>> stateDstream =
          wordsDstream.mapWithState(StateSpec.function(mappingFunc).initialState(initialRDD));
  
      stateDstream.print();
      ssc.start();
      ssc.awaitTermination();
    }
  }
  