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.io.File;
  import java.io.IOException;
  import java.nio.charset.Charset;
  import java.util.Arrays;
  import java.util.Iterator;
  import java.util.List;
  import java.util.regex.Pattern;
  
  import scala.Tuple2;
  
  import com.google.common.io.Files;
  
  import org.apache.spark.SparkConf;
  import org.apache.spark.api.java.JavaPairRDD;
  import org.apache.spark.api.java.JavaSparkContext;
  import org.apache.spark.api.java.function.*;
  import org.apache.spark.broadcast.Broadcast;
  import org.apache.spark.streaming.Durations;
  import org.apache.spark.streaming.Time;
  import org.apache.spark.streaming.api.java.JavaDStream;
  import org.apache.spark.streaming.api.java.JavaPairDStream;
  import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
  import org.apache.spark.streaming.api.java.JavaStreamingContext;
  import org.apache.spark.util.LongAccumulator;
  
  /**
   * Use this singleton to get or register a Broadcast variable.
   */
  class JavaWordBlacklist {
  
    private static volatile Broadcast<List<String>> instance = null;
  
    public static Broadcast<List<String>> getInstance(JavaSparkContext jsc) {
      if (instance == null) {
        synchronized (JavaWordBlacklist.class) {
          if (instance == null) {
            List<String> wordBlacklist = Arrays.asList("a", "b", "c");
            instance = jsc.broadcast(wordBlacklist);
          }
        }
      }
      return instance;
    }
  }
  
  /**
   * Use this singleton to get or register an Accumulator.
   */
  class JavaDroppedWordsCounter {
  
    private static volatile LongAccumulator instance = null;
  
    public static LongAccumulator getInstance(JavaSparkContext jsc) {
      if (instance == null) {
        synchronized (JavaDroppedWordsCounter.class) {
          if (instance == null) {
            instance = jsc.sc().longAccumulator("WordsInBlacklistCounter");
          }
        }
      }
      return instance;
    }
  }
  
  /**
   * Counts words in text encoded with UTF8 received from the network every second. This example also
   * shows how to use lazily instantiated singleton instances for Accumulator and Broadcast so that
   * they can be registered on driver failures.
   *
   * Usage: JavaRecoverableNetworkWordCount <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
   *
   * <checkpoint-directory> and <output-file> must be absolute paths
   *
   * To run this on your local machine, you need to first run a Netcat server
   *
   *      `$ nc -lk 9999`
   *
   * and run the example as
   *
   *      `$ ./bin/run-example org.apache.spark.examples.streaming.JavaRecoverableNetworkWordCount \
   *              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.
   *
   * Refer to the online documentation for more details.
   */
  public final class JavaRecoverableNetworkWordCount {
    private static final Pattern SPACE = Pattern.compile(" ");
  
    private static JavaStreamingContext createContext(String ip,
                                                      int port,
                                                      String checkpointDirectory,
                                                      String outputPath) {
  
      // If you do not see this printed, that means the StreamingContext has been loaded
      // from the new checkpoint
      System.out.println("Creating new context");
      final File outputFile = new File(outputPath);
      if (outputFile.exists()) {
        outputFile.delete();
      }
      SparkConf sparkConf = new SparkConf().setAppName("JavaRecoverableNetworkWordCount");
      // Create the context with a 1 second batch size
      JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
      ssc.checkpoint(checkpointDirectory);
  
      // Create a socket stream on target ip:port and count the
      // words in input stream of \n delimited text (eg. generated by 'nc')
      JavaReceiverInputDStream<String> lines = ssc.socketTextStream(ip, port);
      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> wordCounts = words.mapToPair(
        new PairFunction<String, String, Integer>() {
          @Override
          public Tuple2<String, Integer> call(String s) {
            return new Tuple2<>(s, 1);
          }
        }).reduceByKey(new Function2<Integer, Integer, Integer>() {
          @Override
          public Integer call(Integer i1, Integer i2) {
            return i1 + i2;
          }
        });
  
      wordCounts.foreachRDD(new VoidFunction2<JavaPairRDD<String, Integer>, Time>() {
        @Override
        public void call(JavaPairRDD<String, Integer> rdd, Time time) throws IOException {
          // Get or register the blacklist Broadcast
          final Broadcast<List<String>> blacklist =
              JavaWordBlacklist.getInstance(new JavaSparkContext(rdd.context()));
          // Get or register the droppedWordsCounter Accumulator
          final LongAccumulator droppedWordsCounter =
              JavaDroppedWordsCounter.getInstance(new JavaSparkContext(rdd.context()));
          // Use blacklist to drop words and use droppedWordsCounter to count them
          String counts = rdd.filter(new Function<Tuple2<String, Integer>, Boolean>() {
            @Override
            public Boolean call(Tuple2<String, Integer> wordCount) {
              if (blacklist.value().contains(wordCount._1())) {
                droppedWordsCounter.add(wordCount._2());
                return false;
              } else {
                return true;
              }
            }
          }).collect().toString();
          String output = "Counts at time " + time + " " + counts;
          System.out.println(output);
          System.out.println("Dropped " + droppedWordsCounter.value() + " word(s) totally");
          System.out.println("Appending to " + outputFile.getAbsolutePath());
          Files.append(output + "\n", outputFile, Charset.defaultCharset());
        }
      });
  
      return ssc;
    }
  
    public static void main(String[] args) throws Exception {
      if (args.length != 4) {
        System.err.println("You arguments were " + Arrays.asList(args));
        System.err.println(
            "Usage: JavaRecoverableNetworkWordCount <hostname> <port> <checkpoint-directory>\n" +
            "     <output-file>. <hostname> and <port> describe the TCP server that Spark\n" +
            "     Streaming would connect to receive data. <checkpoint-directory> directory to\n" +
            "     HDFS-compatible file system which checkpoint data <output-file> file to which\n" +
            "     the word counts will be appended\n" +
            "\n" +
            "In local mode, <master> should be 'local[n]' with n > 1\n" +
            "Both <checkpoint-directory> and <output-file> must be absolute paths");
        System.exit(1);
      }
  
      final String ip = args[0];
      final int port = Integer.parseInt(args[1]);
      final String checkpointDirectory = args[2];
      final String outputPath = args[3];
  
      // Function to create JavaStreamingContext without any output operations
      // (used to detect the new context)
      Function0<JavaStreamingContext> createContextFunc = new Function0<JavaStreamingContext>() {
        @Override
        public JavaStreamingContext call() {
          return createContext(ip, port, checkpointDirectory, outputPath);
        }
      };
  
      JavaStreamingContext ssc =
        JavaStreamingContext.getOrCreate(checkpointDirectory, createContextFunc);
      ssc.start();
      ssc.awaitTermination();
    }
  }
  