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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 example;
import java.io.IOException;
import java.util.*;
import org.apache.avro.Schema;
import org.apache.avro.Schema.Type;
import org.apache.avro.mapred.AvroWrapper;
import org.apache.avro.mapred.Pair;
import org.apache.avro.mapreduce.AvroJob;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
/**
* The classic WordCount example modified to output Avro Pair<CharSequence,
* Integer> records instead of text.
*/
public class MapReduceAvroWordCount extends Configured implements Tool {
public static class Map
extends Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
public static class Reduce
extends Reducer<Text, IntWritable,
AvroWrapper<Pair<CharSequence, Integer>>, NullWritable> {
public void reduce(Text key, Iterable<IntWritable> values,
Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
context.write(new AvroWrapper<Pair<CharSequence, Integer>>
(new Pair<CharSequence, Integer>(key.toString(), sum)),
NullWritable.get());
}
}
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: AvroWordCount <input path> <output path>");
return -1;
}
Job job = new Job(getConf());
job.setJarByClass(MapReduceAvroWordCount.class);
job.setJobName("wordcount");
// We call setOutputSchema first so we can override the configuration
// parameters it sets
AvroJob.setOutputKeySchema(job,
Pair.getPairSchema(Schema.create(Type.STRING),
Schema.create(Type.INT)));
job.setOutputValueClass(NullWritable.class);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setInputFormatClass(TextInputFormat.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setSortComparatorClass(Text.Comparator.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.waitForCompletion(true);
return 0;
}
public static void main(String[] args) throws Exception {
int res =
ToolRunner.run(new Configuration(), new MapReduceAvroWordCount(), args);
System.exit(res);
}
}