org.apache.hadoop.examples.WordMean Maven / Gradle / Ivy
package org.apache.hadoop.examples;
/**
* 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 java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import com.google.common.base.Charsets;
public class WordMean extends Configured implements Tool {
private double mean = 0;
private final static Text COUNT = new Text("count");
private final static Text LENGTH = new Text("length");
private final static LongWritable ONE = new LongWritable(1);
/**
* Maps words from line of text into 2 key-value pairs; one key-value pair for
* counting the word, another for counting its length.
*/
public static class WordMeanMapper extends
Mapper {
private LongWritable wordLen = new LongWritable();
/**
* Emits 2 key-value pairs for counting the word and its length. Outputs are
* (Text, LongWritable).
*
* @param value
* This will be a line of text coming in from our input file.
*/
public void map(Object key, Text value, Context context)
throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
String string = itr.nextToken();
this.wordLen.set(string.length());
context.write(LENGTH, this.wordLen);
context.write(COUNT, ONE);
}
}
}
/**
* Performs integer summation of all the values for each key.
*/
public static class WordMeanReducer extends
Reducer {
private LongWritable sum = new LongWritable();
/**
* Sums all the individual values within the iterator and writes them to the
* same key.
*
* @param key
* This will be one of 2 constants: LENGTH_STR or COUNT_STR.
* @param values
* This will be an iterator of all the values associated with that
* key.
*/
public void reduce(Text key, Iterable values, Context context)
throws IOException, InterruptedException {
int theSum = 0;
for (LongWritable val : values) {
theSum += val.get();
}
sum.set(theSum);
context.write(key, sum);
}
}
/**
* Reads the output file and parses the summation of lengths, and the word
* count, to perform a quick calculation of the mean.
*
* @param path
* The path to find the output file in. Set in main to the output
* directory.
* @throws IOException
* If it cannot access the output directory, we throw an exception.
*/
private double readAndCalcMean(Path path, Configuration conf)
throws IOException {
FileSystem fs = FileSystem.get(conf);
Path file = new Path(path, "part-r-00000");
if (!fs.exists(file))
throw new IOException("Output not found!");
BufferedReader br = null;
// average = total sum / number of elements;
try {
br = new BufferedReader(new InputStreamReader(fs.open(file), Charsets.UTF_8));
long count = 0;
long length = 0;
String line;
while ((line = br.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line);
// grab type
String type = st.nextToken();
// differentiate
if (type.equals(COUNT.toString())) {
String countLit = st.nextToken();
count = Long.parseLong(countLit);
} else if (type.equals(LENGTH.toString())) {
String lengthLit = st.nextToken();
length = Long.parseLong(lengthLit);
}
}
double theMean = (((double) length) / ((double) count));
System.out.println("The mean is: " + theMean);
return theMean;
} finally {
if (br != null) {
br.close();
}
}
}
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new WordMean(), args);
}
@Override
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: wordmean ");
return 0;
}
Configuration conf = getConf();
Job job = Job.getInstance(conf, "word mean");
job.setJarByClass(WordMean.class);
job.setMapperClass(WordMeanMapper.class);
job.setCombinerClass(WordMeanReducer.class);
job.setReducerClass(WordMeanReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
Path outputpath = new Path(args[1]);
FileOutputFormat.setOutputPath(job, outputpath);
boolean result = job.waitForCompletion(true);
mean = readAndCalcMean(outputpath, conf);
return (result ? 0 : 1);
}
/**
* Only valuable after run() called.
*
* @return Returns the mean value.
*/
public double getMean() {
return mean;
}
}