MRUnit的安裝和使用

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MRUnit是對MapReduce程序進行單元測試的工具，可以對Mapper和Reducer程序分別進行測試。但是它沒有集成在Hadoop安裝環境中，如果想在開發MapReduce程序時使用這個工具，就需要自己安裝。

MRUnit的安裝

安裝環境：

Eclipse版本爲3.6.0

Hadoop版本爲1.0.4

安裝步驟：

（1）下載MRUnit，網址爲http://mrunit.apache.org/，我下載的是 apache-mrunit-1.0.0-hadoop1-bin.tar.gz

（2）解壓縮下載的文件，將lib目錄下的hamcrest-core-1.1.jar，junit-4.10.jar，mockito-all-1.8.5.jar和mrunit-1.0.0-hadoop1.jar加入到Eclipse的項目中。

方法如下：選中待測試項目-->右鍵Buid Path-->Configure Buid Path-->點擊Libraries-->點擊Add External JARs  

MRUnit的使用

以《Hadoop權威指南》上的MaxTemperature程序爲例，整個項目中包括如下4個源文件，前兩個分別是Mapper程序和Reducer程序，後兩個分別是針對Mapper和Reducer的測試程序：

MaxTemperatureMapper.java，MaxTemperatureReducer.java，MaxTemperatureMapperTest.java，MaxTemperatureReducerTest.java

MaxTemperatureMapper.java

import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class MaxTemperatureMapper 
	extends Mapper<LongWritable, Text, Text, IntWritable> {
	private static final int MISSING = 9999;
	
	public void map(LongWritable key, Text value, Context context)
		throws IOException, InterruptedException {
		String line = value.toString();
		String year = line.substring(15, 19);
		
		int airTemperature;
		if(line.charAt(87) == '+')
			airTemperature = Integer.parseInt(line.substring(88, 92));
		else
			airTemperature = Integer.parseInt(line.substring(87, 92));
		
		String quality = line.substring(92, 93);
		if(airTemperature != MISSING && quality.matches("[01459]"))
			context.write(new Text(year), new IntWritable(airTemperature));
	}
}

MaxTemperatureReducer.java

import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class MaxTemperatureReducer
	extends Reducer<Text, IntWritable, Text, IntWritable> {
	
	public void reduce(Text key, Iterable<IntWritable> values, Context context) 
		throws IOException, InterruptedException {
		
		int maxValue = Integer.MIN_VALUE;
		for(IntWritable val : values)
			maxValue = Math.max(maxValue, val.get());
		
		context.write(key, new IntWritable(maxValue));
	}
}

MaxTemperatureMapperTest.java

import java.io.IOException;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mrunit.mapreduce.MapDriver;
import org.junit.Test;

public class MaxTemperatureMapperTest {
	@Test
	public void processesValidRecord() throws IOException, InterruptedException {
		Text value = new Text("0057332130999991950010103004+51317+028783FM-12+017199999V0203201N00721004501CN0100001N9-01281-01391102681");
		
		new MapDriver<LongWritable, Text, Text, IntWritable>()
			.withMapper(new MaxTemperatureMapper())
			.withInput(new LongWritable(0), value)
			.withOutput(new Text("1950"), new IntWritable(-128))
			.runTest();
	}
}

MaxTemperatureReducerTest.java

import java.io.IOException;
import java.util.Arrays;

import org.junit.Test;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mrunit.mapreduce.ReduceDriver;

public class MaxTemperatureReducerTest {
	@Test
	public void returnsMaximumIntegerInValues() throws IOException, InterruptedException {
		new ReduceDriver<Text, IntWritable, Text, IntWritable>()
			.withReducer(new MaxTemperatureReducer())
			.withInput(new Text("1950"), Arrays.asList(new IntWritable(10), new IntWritable(5)))
			.withOutput(new Text("1950"), new IntWritable(10))
			.runTest();
	}
}

需要注意程序中的@Test是不可或缺的

下面就可以運行測試程序了，如果要測試Mapper程序，那麼就選中MaxTemperatureMapperTest.java，右鍵Run As-->JUnit Test，如果進度條爲綠色，則表示測試正確，否則代表有錯誤。測試Reducer程序也是如此。