org.apache.flink.test.hadoop.mapreduce.WordCountMapreduceITCase.java Source code

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Here is the source code for org.apache.flink.test.hadoop.mapreduce.WordCountMapreduceITCase.java

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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.
 */

package org.apache.flink.test.hadoop.mapreduce;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.hadoop.mapreduce.HadoopOutputFormat;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.test.testdata.WordCountData;
import org.apache.flink.test.util.JavaProgramTestBase;
import org.apache.flink.util.Collector;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class WordCountMapreduceITCase extends JavaProgramTestBase {

    protected String textPath;
    protected String resultPath;

    @Override
    protected void preSubmit() throws Exception {
        textPath = createTempFile("text.txt", WordCountData.TEXT);
        resultPath = getTempDirPath("result");
    }

    @Override
    protected void postSubmit() throws Exception {
        compareResultsByLinesInMemory(WordCountData.COUNTS, resultPath, new String[] { ".", "_" });
    }

    @Override
    protected void testProgram() throws Exception {
        final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        DataSet<Tuple2<LongWritable, Text>> input = env.readHadoopFile(new TextInputFormat(), LongWritable.class,
                Text.class, textPath);

        DataSet<String> text = input.map(new MapFunction<Tuple2<LongWritable, Text>, String>() {
            @Override
            public String map(Tuple2<LongWritable, Text> value) throws Exception {
                return value.f1.toString();
            }
        });

        DataSet<Tuple2<String, Integer>> counts =
                // split up the lines in pairs (2-tuples) containing: (word,1)
                text.flatMap(new Tokenizer())
                        // group by the tuple field "0" and sum up tuple field "1"
                        .groupBy(0).sum(1);

        DataSet<Tuple2<Text, LongWritable>> words = counts
                .map(new MapFunction<Tuple2<String, Integer>, Tuple2<Text, LongWritable>>() {

                    @Override
                    public Tuple2<Text, LongWritable> map(Tuple2<String, Integer> value) throws Exception {
                        return new Tuple2<Text, LongWritable>(new Text(value.f0), new LongWritable(value.f1));
                    }
                });

        // Set up Hadoop Output Format
        Job job = Job.getInstance();
        HadoopOutputFormat<Text, LongWritable> hadoopOutputFormat = new HadoopOutputFormat<Text, LongWritable>(
                new TextOutputFormat<Text, LongWritable>(), job);
        job.getConfiguration().set("mapred.textoutputformat.separator", " ");
        TextOutputFormat.setOutputPath(job, new Path(resultPath));

        // Output & Execute
        words.output(hadoopOutputFormat);
        env.execute("Hadoop Compat WordCount");
    }

    public static final class Tokenizer 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));
                }
            }
        }
    }
}