【Hadoop测试程序】编写MapReduce测试Hadoop环境

• 我们使用之前搭建好的Hadoop环境，可参见：
  

《【Hadoop环境搭建】Centos6.8搭建hadoop伪分布模式》http://www.cnblogs.com/ssslinppp/p/5923793.html   

• 示例程序为《Hadoop权威指南3》中的获取最高温度的示例程序；
  

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数据准备

输入数据为：sample.txt

0067011990999991950051507004+68750+023550FM-12+038299999V0203301N00671220001CN9999999N9+00001+99999999999
0043011990999991950051512004+68750+023550FM-12+038299999V0203201N00671220001CN9999999N9+00221+99999999999
0043011990999991950051518004+68750+023550FM-12+038299999V0203201N00261220001CN9999999N9-00111+99999999999
0043012650999991949032412004+62300+010750FM-12+048599999V0202701N00461220001CN0500001N9+01111+99999999999
0043012650999991949032418004+62300+010750FM-12+048599999V0202701N00461220001CN0500001N9+00781+99999999999

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将samle.txt上传至HDFS

hadoop fs -put /home/hadoop/ncdcData/sample.txt input

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项目结构

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MaxTemperatureMapper类

package com.ll.maxTemperature;
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;
	@Override
	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) == '+') { // parseInt doesn't like leading plus
										// signs
			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));
		}
	}
}
// ^^ MaxTemperatureMapper

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MaxTemperatureReducer类

package com.ll.maxTemperature;
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> {
	@Override
	public void reduce(Text key, Iterable<IntWritable> values, Context context)
			throws IOException, InterruptedException {
		int maxValue = Integer.MIN_VALUE;
		for (IntWritable value : values) {
			maxValue = Math.max(maxValue, value.get());
		}
		context.write(key, new IntWritable(maxValue));
	}
}
// ^^ MaxTemperatureReducer

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MaxTemperature类（主函数）

package com.ll.maxTemperature;
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class MaxTemperature {
	public static void main(String[] args) throws Exception {
		if (args.length != 2) {
			args = new String[] {
					"hdfs://localhost:9000/user/hadoop/input/sample.txt",
					"hdfs://localhost:9000/user/hadoop/out2" };
		}
		Job job = new Job(); // 指定作业执行规范
		job.setJarByClass(MaxTemperature.class);
		job.setJobName("Max temperature");
		FileInputFormat.addInputPath(job, new Path(args[0]));
		FileOutputFormat.setOutputPath(job, new Path(args[1])); // Reduce函数输出文件的写入路径
		job.setMapperClass(MaxTemperatureMapper.class);
		job.setCombinerClass(MaxTemperatureReducer.class);
		job.setReducerClass(MaxTemperatureReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}
// ^^ MaxTemperature

解释说明：

输入路径为：hdfs://localhost:9000/user/hadoop/input/sample.txt

这部分由两部分组成：

1. hdfs://localhost:9000/；
   
2. /user/hadoop/input/sample.txt
   

其中hdfs://localhost:9000/由文件core-size.xml进行设置：

其中/user/hadoop/input/sample.txt就是上面准备数据时sample.txt存放的路径：

输出路径为：hdfs://localhost:9000/user/hadoop/out2

需要注意的是，在执行MapReduce时，这个输出路径一定不要存在，否则会出错。

---

pom.xml

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
	xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
	<modelVersion>4.0.0</modelVersion>
	<groupId>com.ll</groupId>
	<artifactId>MapReduceTest</artifactId>
	<version>0.0.1-SNAPSHOT</version>
	<packaging>jar</packaging>
	<name>MapReduceTest</name>
	<url>http://maven.apache.org</url>
	<properties>
		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
		<hadoopVersion>1.2.1</hadoopVersion>
		<junit.version>3.8.1</junit.version>
	</properties>
	<dependencies>
		<dependency>
			<groupId>junit</groupId>
			<artifactId>junit</artifactId>
			<version>${junit.version}</version>
			<scope>test</scope>
		</dependency>
		<!-- Hadoop -->
		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-core</artifactId>
			<version>${hadoopVersion}</version>
			<!-- Hadoop -->
		</dependency>
	</dependencies>
</project>

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程序测试

Hadoop环境准备

我们使用之前搭建好的Hadoop环境，可参见：

《【Hadoop环境搭建】Centos6.8搭建hadoop伪分布模式》http://www.cnblogs.com/ssslinppp/p/5923793.html 

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生成jar包

下面是生成jar包过程

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上传服务器并运行测试

使用默认的输入输出路径：

hadoop jar mc.jar

指定输入输出路径：

hadoop jar /home/hadoop/jars/mc.jar hdfs://localhost:9000/user/hadoop/input/sample.txt hdfs://localhost:9000/user/hadoop/out5

来自为知笔记(Wiz)