Assignment.java Source code

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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.
 */
import scala.Tuple2;

import com.google.common.collect.Lists;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.api.java.StorageLevels;
import org.apache.spark.streaming.Duration;
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 java.util.regex.Pattern;

public final class Assignment {
    private static final Pattern SPACE = Pattern.compile(" ");

    public static void main(String[] args) {

        // Create the context with a 10 second batch size
        SparkConf sparkConf = new SparkConf().setAppName("Assignment");
        JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, new Duration(10000));

        // Create a JavaReceiverInputDStream on target ip:port and count the
        // words in input stream of \n delimited text (eg. generated by 'nc')
        // Note that no duplication in storage level only for running locally.
        // Replication necessary in distributed scenario for fault tolerance.
        JavaReceiverInputDStream<String> lines = ssc.socketTextStream("localhost", Integer.parseInt("9999"),
                StorageLevels.MEMORY_AND_DISK_SER);

        JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
            @Override
            public Iterable<String> call(String x) {
                return Lists.newArrayList(SPACE.split(x));
            }
        });

        JavaPairDStream<String, Integer> wordCounts = words.filter(new Function<String, Boolean>() {
            public Boolean call(String s) {
                return s.toLowerCase().contains("#obama");
            }
        }).mapToPair(new PairFunction<String, String, Integer>() {
            @Override
            public Tuple2<String, Integer> call(String s) {
                return new Tuple2<String, Integer>(s, 1);
            }
        });

        // Reduce function adding two integers, defined separately for clarity
        Function2<Integer, Integer, Integer> reduceFunc = new Function2<Integer, Integer, Integer>() {
            @Override
            public Integer call(Integer i1, Integer i2) throws Exception {
                return i1 + i2;
            }
        };

        // Reduce last 30 seconds of data, every 10 seconds
        JavaPairDStream<String, Integer> windowedWordCounts = wordCounts.reduceByKeyAndWindow(reduceFunc,
                new Duration(30000), new Duration(10000));

        windowedWordCounts.print();

        ssc.start();

        ssc.awaitTermination();
    }
}