MapReduce读取文本，实现降序排序_mapreduce降序

目录

1、Maven导入hadoop-client包

2、core-site.xml文件配置

3、log4j.properties 文件配置

4、Top5.java（主要代码）

5、测试数据

6、运行结果

1、Maven导入hadoop-client包

		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-client</artifactId>
			<version>2.7.3</version>
		</dependency>

2、core-site.xml文件配置

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration xmlns:xi="http://www.w3.org/2001/XInclude">
	<!--  
	<property>
		<name>fs.defaultFS</name>
		<value>hdfs://localhost:8020</value>
		<descript>配置HDFS环境，不配置则默认使用Windows系统下的磁盘</descript>
	</property>
	 -->
	<property>
		<name>fs.defaultFS</name>
		<value>file://34455/</value>
		<descript>使用Windows系统下的磁盘</descript>
	</property>
	
</configuration>

3、log4j.properties 文件配置

hadoop.root.logger=INFO,console
hadoop.log.dir=.
hadoop.log.file=hadoop.log
 
log4j.threshold=ALL
 
log4j.appender.NullAppender=org.apache.log4j.varia.NullAppender
 
hadoop.log.maxfilesize=256MB
hadoop.log.maxbackupindex=20
log4j.appender.RFA=org.apache.log4j.RollingFileAppender
log4j.appender.RFA.File=${hadoop.log.dir}/${hadoop.log.file}
 
log4j.appender.RFA.MaxFileSize=${hadoop.log.maxfilesize}
log4j.appender.RFA.MaxBackupIndex=${hadoop.log.maxbackupindex}
 
log4j.appender.RFA.layout=org.apache.log4j.PatternLayout
 
log4j.appender.DRFA=org.apache.log4j.DailyRollingFileAppender
log4j.appender.DRFA.File=${hadoop.log.dir}/${hadoop.log.file}
 
log4j.appender.DRFA.DatePattern=.yyyy-MM-dd
 
log4j.appender.DRFA.layout=org.apache.log4j.PatternLayout
 
log4j.appender.DRFA.layout.ConversionPattern=%d{ISO8601} %p %c: %m%n
 
log4j.logger.org.apache.hadoop.conf.Configuration=ERROR
 
log4j.appender.console=org.apache.log4j.ConsoleAppender
log4j.appender.console.target=System.err
log4j.appender.console.layout=org.apache.log4j.PatternLayout
log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{2}: %m%n
 
#Default values
hadoop.tasklog.taskid=null
hadoop.tasklog.iscleanup=false
hadoop.tasklog.noKeepSplits=4
hadoop.tasklog.totalLogFileSize=100
hadoop.tasklog.purgeLogSplits=true
hadoop.tasklog.logsRetainHours=12
 
log4j.appender.TLA=org.apache.hadoop.mapred.TaskLogAppender
log4j.appender.TLA.taskId=${hadoop.tasklog.taskid}
log4j.appender.TLA.isCleanup=${hadoop.tasklog.iscleanup}
log4j.appender.TLA.totalLogFileSize=${hadoop.tasklog.totalLogFileSize}
 
log4j.appender.TLA.layout=org.apache.log4j.PatternLayout
log4j.appender.TLA.layout.ConversionPattern=%d{ISO8601} %p %c: %m%n
 
hadoop.security.logger=INFO,NullAppender
hadoop.security.log.maxfilesize=256MB
hadoop.security.log.maxbackupindex=20
log4j.category.SecurityLogger=${hadoop.security.logger}
hadoop.security.log.file=SecurityAuth-${user.name}.audit
log4j.appender.RFAS=org.apache.log4j.RollingFileAppender 
log4j.appender.RFAS.File=${hadoop.log.dir}/${hadoop.security.log.file}
log4j.appender.RFAS.layout=org.apache.log4j.PatternLayout
log4j.appender.RFAS.layout.ConversionPattern=%d{ISO8601} %p %c: %m%n
log4j.appender.RFAS.MaxFileSize=${hadoop.security.log.maxfilesize}
log4j.appender.RFAS.MaxBackupIndex=${hadoop.security.log.maxbackupindex}
 
log4j.appender.DRFAS=org.apache.log4j.DailyRollingFileAppender 
log4j.appender.DRFAS.File=${hadoop.log.dir}/${hadoop.security.log.file}
log4j.appender.DRFAS.layout=org.apache.log4j.PatternLayout
log4j.appender.DRFAS.layout.ConversionPattern=%d{ISO8601} %p %c: %m%n
log4j.appender.DRFAS.DatePattern=.yyyy-MM-dd
 
hdfs.audit.logger=INFO,NullAppender
hdfs.audit.log.maxfilesize=256MB
hdfs.audit.log.maxbackupindex=20
log4j.logger.org.apache.hadoop.hdfs.server.namenode.FSNamesystem.audit=${hdfs.audit.logger}
log4j.additivity.org.apache.hadoop.hdfs.server.namenode.FSNamesystem.audit=false
log4j.appender.RFAAUDIT=org.apache.log4j.RollingFileAppender
log4j.appender.RFAAUDIT.File=${hadoop.log.dir}/hdfs-audit.log
log4j.appender.RFAAUDIT.layout=org.apache.log4j.PatternLayout
log4j.appender.RFAAUDIT.layout.ConversionPattern=%d{ISO8601} %p %c{2}: %m%n
log4j.appender.RFAAUDIT.MaxFileSize=${hdfs.audit.log.maxfilesize}
log4j.appender.RFAAUDIT.MaxBackupIndex=${hdfs.audit.log.maxbackupindex}
 
mapred.audit.logger=INFO,NullAppender
mapred.audit.log.maxfilesize=256MB
mapred.audit.log.maxbackupindex=20
log4j.logger.org.apache.hadoop.mapred.AuditLogger=${mapred.audit.logger}
log4j.additivity.org.apache.hadoop.mapred.AuditLogger=false
log4j.appender.MRAUDIT=org.apache.log4j.RollingFileAppender
log4j.appender.MRAUDIT.File=${hadoop.log.dir}/mapred-audit.log
log4j.appender.MRAUDIT.layout=org.apache.log4j.PatternLayout
log4j.appender.MRAUDIT.layout.ConversionPattern=%d{ISO8601} %p %c{2}: %m%n
log4j.appender.MRAUDIT.MaxFileSize=${mapred.audit.log.maxfilesize}
log4j.appender.MRAUDIT.MaxBackupIndex=${mapred.audit.log.maxbackupindex}
 
hadoop.mapreduce.jobsummary.logger=${hadoop.root.logger}
hadoop.mapreduce.jobsummary.log.file=hadoop-mapreduce.jobsummary.log
hadoop.mapreduce.jobsummary.log.maxfilesize=256MB
hadoop.mapreduce.jobsummary.log.maxbackupindex=20
log4j.appender.JSA=org.apache.log4j.RollingFileAppender
log4j.appender.JSA.File=${hadoop.log.dir}/${hadoop.mapreduce.jobsummary.log.file}
log4j.appender.JSA.MaxFileSize=${hadoop.mapreduce.jobsummary.log.maxfilesize}
log4j.appender.JSA.MaxBackupIndex=${hadoop.mapreduce.jobsummary.log.maxbackupindex}
log4j.appender.JSA.layout=org.apache.log4j.PatternLayout
log4j.appender.JSA.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{2}: %m%n
log4j.logger.org.apache.hadoop.mapred.JobInProgress$JobSummary=${hadoop.mapreduce.jobsummary.logger}
log4j.additivity.org.apache.hadoop.mapred.JobInProgress$JobSummary=false
 
log4j.logger.org.apache.hadoop.yarn.server.resourcemanager.RMAppManager$ApplicationSummary=${yarn.server.resourcemanager.appsummary.logger}
log4j.additivity.org.apache.hadoop.yarn.server.resourcemanager.RMAppManager$ApplicationSummary=false
log4j.appender.RMSUMMARY=org.apache.log4j.RollingFileAppender
log4j.appender.RMSUMMARY.File=${hadoop.log.dir}/${yarn.server.resourcemanager.appsummary.log.file}
log4j.appender.RMSUMMARY.MaxFileSize=256MB
log4j.appender.RMSUMMARY.MaxBackupIndex=20
log4j.appender.RMSUMMARY.layout=org.apache.log4j.PatternLayout
log4j.appender.RMSUMMARY.layout.ConversionPattern=%d{ISO8601} %p %c{2}: %m%n
 

4、Top5.java（主要代码）

package com.gxwz.mapreduce;
 
import java.io.IOException;
import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
 
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.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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
 
/**
 * TODO 	 MapReduce读取文本，实现降序排序
 * @author   com
 * @Date	 2019年9月28日 	Configured 
 */
public class Top5 extends Configured implements Tool {
 
	public static class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
		
		Text outkey = new Text();
		IntWritable outval = new IntWritable(1);
		String [] line = null;
		@Override
		protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, IntWritable>.Context context)
				throws IOException, InterruptedException {
			line = value.toString().split("\t");
			if(null != line && line.length > 0 && Arrays.toString(line).length()>2) {
				for (String s : line) {
					outkey.set(s);
					context.write(outkey, outval);
				}
			}
		}
	}
	
	public static class MyReduce extends Reducer<Text, IntWritable, Text, LongWritable> {
		
		Text outkey = new Text();
		LongWritable outval = new LongWritable();
		Integer sum = new Integer(0);	//非new生成的Long变量指向的是java常量池中的对象，而new Long()生成的变量指向堆中新建的对象，两者在内存中的地址不同
		Map<String, Long> map = new HashMap<String, Long>();
		@Override
		protected void reduce(Text key, Iterable<IntWritable> values,
				Reducer<Text, IntWritable, Text, LongWritable>.Context context) throws IOException, InterruptedException {
			sum = 0;
			for (IntWritable value : values) {
				sum += value.get();
			}
			map.put(key.toString(), (long)sum);
		}
		
		@Override
		protected void cleanup(Reducer<Text, IntWritable, Text, LongWritable>.Context context)
				throws IOException, InterruptedException {
			List<Map.Entry<String, Long>> list = new LinkedList<Map.Entry<String,Long>>(map.entrySet());
			Collections.sort(list, new Comparator<Map.Entry<String,Long>>() {
				@Override
				public int compare(Entry<String, Long> o1, Entry<String, Long> o2) {
					return (int) (o2.getValue() - o1.getValue());
				}
			});
			for (Entry<String, Long> entry : list) {
				System.out.println(entry.getKey()+":"+entry.getValue());
				outkey.set(entry.getKey());
				outval.set(entry.getValue());
				context.write(outkey, outval);
			}
		}
	}
	
	@Override
	public int run(String[] args) throws Exception {
		
		// 1、配置文件获取
		Configuration conf = this.getConf();
		// 2、获取文件目录
		FileSystem fs = FileSystem.get(conf); 
		// 3、定义 job的输入输出路径
		Path inpath = new Path(args[0]);
		Path outpath = new Path(args[1]);
		// 4、判断输出文件是否为空
		if(fs.exists(outpath)) {
			fs.delete(outpath, true);
			System.out.println("The old path has been deleted!");
		}
		// 5、获取一个job的实例
		Job job = Job.getInstance();
		// 6、设置MapReduce的打包类
		job.setJarByClass(Top5.class);
		// 7、设置Mapper类和Reducer类
		job.setMapperClass(MyMapper.class);
		job.setReducerClass(MyReduce.class);
		// 8、设置MR的输入输出格式
		job.setInputFormatClass(TextInputFormat.class);
		job.setOutputFormatClass(TextOutputFormat.class);
		// 9、因为Mapper的输出和Reducer的输出类型不一样，所有还需设置Mapper类的输出类
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		// 10、设置job的输入输出路径
		FileInputFormat.addInputPath(job, inpath);
		FileOutputFormat.setOutputPath(job, outpath);
		// 11、提交job任务
		int result = job.waitForCompletion(true) ? 0 : 1;
		return result;
	}
	
	//C:\Users\com\Desktop\mr\top10\ C:\Users\com\Desktop\mr\top10\output\
	public static void main(String[] args) {
		String [] path = new String[2];
		path[0] = "C:\\Users\\com\\Desktop\\mr\\top10";			//输入路径
		path[1] = "C:\\Users\\com\\Desktop\\mr\\top10\\output"; //输出路径
		try {
			int result = ToolRunner.run(new Top5(), path);
			String msg = result==0?"job finish!":"job fail!";
			System.out.println(msg);
			System.exit(result);
		} catch (Exception e) {
			e.printStackTrace();
		}
	}
 
}
 

5、测试数据

小明	小绿	小黑
 
小红	小红	小白
 
小蓝	小蓝	小蓝
 
小黑	小白	小黑
 
小红	小红	小黄
 
小黑	小白	小绿
 
小红	小蓝	小蓝
 
小红	小红	小黄
 
小绿	小蓝	小蓝
 
小黑	小白	小蓝

6、运行结果

小蓝	8
小红	7
小黑	5
小白	4
小绿	3
小黄	2
小明	1