MAPREDUCE-2669. Add new examples for Mean, Median, and Standard Deviation. Contributed by Plamen Jeliazkov.

git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/trunk@1169874 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Konstantin Shvachko 2011-09-12 19:13:41 +00:00
parent fb65bfc661
commit 1c01951264
5 changed files with 893 additions and 0 deletions

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@ -2,6 +2,13 @@ Hadoop MapReduce Change Log
Trunk (unreleased changes)
INCOMPATIBLE CHANGES
NEW FEATURES
MAPREDUCE-2669. Add new examples for Mean, Median, and Standard Deviation.
(Plamen Jeliazkov via shv)
IMPROVEMENTS
MAPREDUCE-2887 due to HADOOP-7524 Change RPC to allow multiple protocols

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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;
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<Object, Text, Text, LongWritable> {
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<Text, LongWritable, Text, LongWritable> {
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<LongWritable> 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)));
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 {
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 <in> <out>");
return 0;
}
Configuration conf = getConf();
@SuppressWarnings("deprecation")
Job job = new Job(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;
}
}

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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.IntWritable;
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.TaskCounter;
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;
public class WordMedian extends Configured implements Tool {
private double median = 0;
private final static IntWritable ONE = new IntWritable(1);
/**
* Maps words from line of text into a key-value pair; the length of the word
* as the key, and 1 as the value.
*/
public static class WordMedianMapper extends
Mapper<Object, Text, IntWritable, IntWritable> {
private IntWritable length = new IntWritable();
/**
* Emits a key-value pair for counting the word. Outputs are (IntWritable,
* IntWritable).
*
* @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();
length.set(string.length());
context.write(length, ONE);
}
}
}
/**
* Performs integer summation of all the values for each key.
*/
public static class WordMedianReducer extends
Reducer<IntWritable, IntWritable, IntWritable, IntWritable> {
private IntWritable val = new IntWritable();
/**
* Sums all the individual values within the iterator and writes them to the
* same key.
*
* @param key
* This will be a length of a word that was read.
* @param values
* This will be an iterator of all the values associated with that
* key.
*/
public void reduce(IntWritable key, Iterable<IntWritable> values,
Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
val.set(sum);
context.write(key, val);
}
}
/**
* This is a standard program to read and find a median value based on a file
* of word counts such as: 1 456, 2 132, 3 56... Where the first values are
* the word lengths and the following values are the number of times that
* words of that length appear.
*
* @param path
* The path to read the HDFS file from (part-r-00000...00001...etc).
* @param medianIndex1
* The first length value to look for.
* @param medianIndex2
* The second length value to look for (will be the same as the first
* if there are an even number of words total).
* @throws IOException
* If file cannot be found, we throw an exception.
* */
private double readAndFindMedian(String path, int medianIndex1,
int medianIndex2, 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;
try {
br = new BufferedReader(new InputStreamReader(fs.open(file)));
int num = 0;
String line;
while ((line = br.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line);
// grab length
String currLen = st.nextToken();
// grab count
String lengthFreq = st.nextToken();
int prevNum = num;
num += Integer.parseInt(lengthFreq);
if (medianIndex2 >= prevNum && medianIndex1 <= num) {
System.out.println("The median is: " + currLen);
br.close();
return Double.parseDouble(currLen);
} else if (medianIndex2 >= prevNum && medianIndex1 < num) {
String nextCurrLen = st.nextToken();
double theMedian = (Integer.parseInt(currLen) + Integer
.parseInt(nextCurrLen)) / 2.0;
System.out.println("The median is: " + theMedian);
br.close();
return theMedian;
}
}
} finally {
br.close();
}
// error, no median found
return -1;
}
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new WordMedian(), args);
}
@Override
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: wordmedian <in> <out>");
return 0;
}
setConf(new Configuration());
Configuration conf = getConf();
@SuppressWarnings("deprecation")
Job job = new Job(conf, "word median");
job.setJarByClass(WordMedian.class);
job.setMapperClass(WordMedianMapper.class);
job.setCombinerClass(WordMedianReducer.class);
job.setReducerClass(WordMedianReducer.class);
job.setOutputKeyClass(IntWritable.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
boolean result = job.waitForCompletion(true);
// Wait for JOB 1 -- get middle value to check for Median
long totalWords = job.getCounters()
.getGroup(TaskCounter.class.getCanonicalName())
.findCounter("MAP_OUTPUT_RECORDS", "Map output records").getValue();
int medianIndex1 = (int) Math.ceil((totalWords / 2.0));
int medianIndex2 = (int) Math.floor((totalWords / 2.0));
median = readAndFindMedian(args[1], medianIndex1, medianIndex2, conf);
return (result ? 0 : 1);
}
public double getMedian() {
return median;
}
}

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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;
public class WordStandardDeviation extends Configured implements Tool {
private double stddev = 0;
private final static Text LENGTH = new Text("length");
private final static Text SQUARE = new Text("square");
private final static Text COUNT = new Text("count");
private final static LongWritable ONE = new LongWritable(1);
/**
* Maps words from line of text into 3 key-value pairs; one key-value pair for
* counting the word, one for counting its length, and one for counting the
* square of its length.
*/
public static class WordStandardDeviationMapper extends
Mapper<Object, Text, Text, LongWritable> {
private LongWritable wordLen = new LongWritable();
private LongWritable wordLenSq = new LongWritable();
/**
* Emits 3 key-value pairs for counting the word, its length, and the
* squares of 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());
// the square of an integer is an integer...
this.wordLenSq.set((long) Math.pow(string.length(), 2.0));
context.write(LENGTH, this.wordLen);
context.write(SQUARE, this.wordLenSq);
context.write(COUNT, ONE);
}
}
}
/**
* Performs integer summation of all the values for each key.
*/
public static class WordStandardDeviationReducer extends
Reducer<Text, LongWritable, Text, LongWritable> {
private LongWritable val = 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, COUNT_STR, or
* SQUARE_STR.
* @param values
* This will be an iterator of all the values associated with that
* key.
*/
public void reduce(Text key, Iterable<LongWritable> values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (LongWritable value : values) {
sum += value.get();
}
val.set(sum);
context.write(key, val);
}
}
/**
* Reads the output file and parses the summation of lengths, the word count,
* and the lengths squared, to perform a quick calculation of the standard
* deviation.
*
* @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 readAndCalcStdDev(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!");
double stddev = 0;
BufferedReader br = null;
try {
br = new BufferedReader(new InputStreamReader(fs.open(file)));
long count = 0;
long length = 0;
long square = 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);
} else if (type.equals(SQUARE.toString())) {
String squareLit = st.nextToken();
square = Long.parseLong(squareLit);
}
}
// average = total sum / number of elements;
double mean = (((double) length) / ((double) count));
// standard deviation = sqrt((sum(lengths ^ 2)/count) - (mean ^ 2))
mean = Math.pow(mean, 2.0);
double term = (((double) square / ((double) count)));
stddev = Math.sqrt((term - mean));
System.out.println("The standard deviation is: " + stddev);
} finally {
br.close();
}
return stddev;
}
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new WordStandardDeviation(),
args);
}
@Override
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: wordstddev <in> <out>");
return 0;
}
Configuration conf = getConf();
@SuppressWarnings("deprecation")
Job job = new Job(conf, "word stddev");
job.setJarByClass(WordStandardDeviation.class);
job.setMapperClass(WordStandardDeviationMapper.class);
job.setCombinerClass(WordStandardDeviationReducer.class);
job.setReducerClass(WordStandardDeviationReducer.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);
// read output and calculate standard deviation
stddev = readAndCalcStdDev(outputpath, conf);
return (result ? 0 : 1);
}
public double getStandardDeviation() {
return stddev;
}
}

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package org.apache.hadoop.examples;
import static org.junit.Assert.assertEquals;
import java.io.BufferedReader;
import java.io.File;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.StringTokenizer;
import java.util.TreeMap;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.util.ToolRunner;
import org.junit.Before;
import org.junit.Test;
public class TestWordStats {
private final static String INPUT = "src/test/mapred/org/apache/hadoop/examples/pi/math";
private final static String MEAN_OUTPUT = "build/data/mean_output";
private final static String MEDIAN_OUTPUT = "build/data/median_output";
private final static String STDDEV_OUTPUT = "build/data/stddev_output";
/**
* Modified internal test class that is designed to read all the files in the
* input directory, and find the standard deviation between all of the word
* lengths.
*/
public static class WordStdDevReader {
private long wordsRead = 0;
private long wordLengthsRead = 0;
private long wordLengthsReadSquared = 0;
public WordStdDevReader() {
}
public double read(String path) throws IOException {
FileSystem fs = FileSystem.get(new Configuration());
FileStatus[] files = fs.listStatus(new Path(path));
for (FileStatus fileStat : files) {
if (!fileStat.isFile())
continue;
BufferedReader br = null;
try {
br = new BufferedReader(new InputStreamReader(fs.open(fileStat.getPath())));
String line;
while ((line = br.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line);
String word;
while (st.hasMoreTokens()) {
word = st.nextToken();
this.wordsRead++;
this.wordLengthsRead += word.length();
this.wordLengthsReadSquared += (long) Math.pow(word.length(), 2.0);
}
}
} catch (IOException e) {
System.out.println("Output could not be read!");
throw e;
} finally {
br.close();
}
}
double mean = (((double) this.wordLengthsRead) / ((double) this.wordsRead));
mean = Math.pow(mean, 2.0);
double term = (((double) this.wordLengthsReadSquared / ((double) this.wordsRead)));
double stddev = Math.sqrt((term - mean));
return stddev;
}
}
/**
* Modified internal test class that is designed to read all the files in the
* input directory, and find the median length of all the words.
*/
public static class WordMedianReader {
private long wordsRead = 0;
private TreeMap<Integer, Integer> map = new TreeMap<Integer, Integer>();
public WordMedianReader() {
}
public double read(String path) throws IOException {
FileSystem fs = FileSystem.get(new Configuration());
FileStatus[] files = fs.listStatus(new Path(path));
int num = 0;
for (FileStatus fileStat : files) {
if (!fileStat.isFile())
continue;
BufferedReader br = null;
try {
br = new BufferedReader(new InputStreamReader(fs.open(fileStat.getPath())));
String line;
while ((line = br.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line);
String word;
while (st.hasMoreTokens()) {
word = st.nextToken();
this.wordsRead++;
if (this.map.get(word.length()) == null) {
this.map.put(word.length(), 1);
} else {
int count = this.map.get(word.length());
this.map.put(word.length(), count + 1);
}
}
}
} catch (IOException e) {
System.out.println("Output could not be read!");
throw e;
} finally {
br.close();
}
}
int medianIndex1 = (int) Math.ceil((this.wordsRead / 2.0));
int medianIndex2 = (int) Math.floor((this.wordsRead / 2.0));
for (Integer key : this.map.navigableKeySet()) {
int prevNum = num;
num += this.map.get(key);
if (medianIndex2 >= prevNum && medianIndex1 <= num) {
return key;
} else if (medianIndex2 >= prevNum && medianIndex1 < num) {
Integer nextCurrLen = this.map.navigableKeySet().iterator().next();
double median = (key + nextCurrLen) / 2.0;
return median;
}
}
return -1;
}
}
/**
* Modified internal test class that is designed to read all the files in the
* input directory, and find the mean length of all the words.
*/
public static class WordMeanReader {
private long wordsRead = 0;
private long wordLengthsRead = 0;
public WordMeanReader() {
}
public double read(String path) throws IOException {
FileSystem fs = FileSystem.get(new Configuration());
FileStatus[] files = fs.listStatus(new Path(path));
for (FileStatus fileStat : files) {
if (!fileStat.isFile())
continue;
BufferedReader br = null;
try {
br = new BufferedReader(new InputStreamReader(fs.open(fileStat.getPath())));
String line;
while ((line = br.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line);
String word;
while (st.hasMoreTokens()) {
word = st.nextToken();
this.wordsRead++;
this.wordLengthsRead += word.length();
}
}
} catch (IOException e) {
System.out.println("Output could not be read!");
throw e;
} finally {
br.close();
}
}
double mean = (((double) this.wordLengthsRead) / ((double) this.wordsRead));
return mean;
}
}
/**
* Internal class designed to delete the output directory. Meant solely for
* use before and after the test is run; this is so next iterations of the
* test do not encounter a "file already exists" error.
*
* @param dir
* The directory to delete.
* @return Returns whether the deletion was successful or not.
*/
public static boolean deleteDir(File dir) {
if (dir.isDirectory()) {
String[] children = dir.list();
for (int i = 0; i < children.length; i++) {
boolean success = deleteDir(new File(dir, children[i]));
if (!success) {
System.out.println("Could not delete directory after test!");
return false;
}
}
}
// The directory is now empty so delete it
return dir.delete();
}
@Before public void setup() throws Exception {
deleteDir(new File(MEAN_OUTPUT));
deleteDir(new File(MEDIAN_OUTPUT));
deleteDir(new File(STDDEV_OUTPUT));
}
@Test public void testGetTheMean() throws Exception {
String args[] = new String[2];
args[0] = INPUT;
args[1] = MEAN_OUTPUT;
WordMean wm = new WordMean();
ToolRunner.run(new Configuration(), wm, args);
double mean = wm.getMean();
// outputs MUST match
WordMeanReader wr = new WordMeanReader();
assertEquals(mean, wr.read(INPUT), 0.0);
}
@Test public void testGetTheMedian() throws Exception {
String args[] = new String[2];
args[0] = INPUT;
args[1] = MEDIAN_OUTPUT;
WordMedian wm = new WordMedian();
ToolRunner.run(new Configuration(), wm, args);
double median = wm.getMedian();
// outputs MUST match
WordMedianReader wr = new WordMedianReader();
assertEquals(median, wr.read(INPUT), 0.0);
}
@Test public void testGetTheStandardDeviation() throws Exception {
String args[] = new String[2];
args[0] = INPUT;
args[1] = STDDEV_OUTPUT;
WordStandardDeviation wsd = new WordStandardDeviation();
ToolRunner.run(new Configuration(), wsd, args);
double stddev = wsd.getStandardDeviation();
// outputs MUST match
WordStdDevReader wr = new WordStdDevReader();
assertEquals(stddev, wr.read(INPUT), 0.0);
}
}