/** * 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 com.alibaba.flink.performance.test; import org.apache.flink.api.common.functions.FlatMapFunction; import org.apache.flink.api.java.tuple.Tuple2; import org.apache.flink.api.java.utils.ParameterTool; import org.apache.flink.streaming.api.datastream.DataStream; import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; import org.apache.flink.streaming.api.functions.source.ParallelSourceFunction; import org.apache.flink.streaming.api.functions.source.SourceFunction; import org.apache.flink.util.Collector; import java.util.Random; import java.util.concurrent.ThreadLocalRandom; /** * @author Jark (wuchong.wc@alibaba-inc.com) */ public class StreamWordCount { public static void main(String[] args) throws Exception { StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); // env.addS ParameterTool tool = ParameterTool.fromArgs(args); int sourceParallel = Integer.parseInt(tool.get("s")); int operatorParallel = Integer.parseInt(tool.get("p")); System.out.println("sourceParallel: " + sourceParallel + ", operatorParallel: " + operatorParallel); env.setParallelism(operatorParallel); // get input data DataStream<String> text = env.addSource(new WordSource()).setParallelism(sourceParallel); DataStream<Tuple2<String, Integer>> counts = // split up the lines in pairs (2-tuples) containing: (word,1) text.flatMap(new LineSplitter()) // group by the tuple field "0" and sum up tuple field "1" .keyBy(0) .sum(1); // execute program // env.execute("StreamWordCount"); System.out.println(env.getExecutionPlan()); } public static class WordSource implements ParallelSourceFunction<String> { Random _rand = ThreadLocalRandom.current(); private volatile boolean active = true; private static final String[] CHOICES = { "marry had a little lamb whos fleese was white as snow", "and every where that marry went the lamb was sure to go", "one two three four five six seven eight nine ten", "this is a test of the emergency broadcast system this is only a test", "peter piper picked a peck of pickeled peppers" }; @Override public void run(SourceContext<String> ctx) throws Exception { while (active) { String sentence = CHOICES[_rand.nextInt(CHOICES.length)]; ctx.collect(sentence); } } @Override public void cancel() { active = false; } } /** * Implements the string tokenizer that splits sentences into words as a user-defined * FlatMapFunction. The function takes a line (String) and splits it into * multiple pairs in the form of "(word,1)" (Tuple2<String, Integer>). */ public static final class LineSplitter implements FlatMapFunction<String, Tuple2<String, Integer>> { @Override public void flatMap(String value, Collector<Tuple2<String, Integer>> out) { // normalize and split the line String[] tokens = value.toLowerCase().split("\\W+"); // emit the pairs for (String token : tokens) { if (token.length() > 0) { out.collect(new Tuple2<String, Integer>(token, 1)); } } } } }