怎么用MapReduce列出工资比上司高的员工姓名及工资
发表于:2025-02-01 作者:千家信息网编辑
千家信息网最后更新 2025年02月01日,这篇文章主要讲解了"怎么用MapReduce列出工资比上司高的员工姓名及工资",文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习"怎么用MapReduce列出
千家信息网最后更新 2025年02月01日怎么用MapReduce列出工资比上司高的员工姓名及工资
这篇文章主要讲解了"怎么用MapReduce列出工资比上司高的员工姓名及工资",文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习"怎么用MapReduce列出工资比上司高的员工姓名及工资"吧!
数据
EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO
7369 SMITH CLERK 7902 17-12月-80 800 20 7499 ALLEN SALESMAN 7698 20-2月 -81 1600 300 30 7521 WARD SALESMAN 7698 22-2月 -81 1250 500 30 7566 JONES MANAGER 7839 02-4月 -81 2975 20 7654 MARTIN SALESMAN 7698 28-9月 -81 1250 1400 30 7698 BLAKE MANAGER 7839 01-5月 -81 2850 30 7782 CLARK MANAGER 7839 09-6月 -81 2450 10 7839 KING PRESIDENT 17-11月-81 5000 10 7844 TURNER SALESMAN 7698 08-9月 -81 1500 0 30 7900 JAMES CLERK 7698 03-12月-81 950 30 7902 FORD ANALYST 7566 03-12月-81 3000 20 7934 MILLER CLERK 7782 23-1月 -82 1300 10
代码
package cn.kissoft.hadoop.week07;import java.io.IOException;import java.text.DateFormat;import java.text.SimpleDateFormat;import java.util.ArrayList;import java.util.Date;import java.util.List;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.conf.Configured;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.NullWritable;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.mapreduce.lib.output.TextOutputFormat;import org.apache.hadoop.util.Tool;import org.apache.hadoop.util.ToolRunner;import cn.kissoft.hadoop.util.HdfsUtil;/** * Homework-05:列出工资比上司高的员工姓名及其工资 * * @author wukong(jinsong.sun@139.com) */public class MorePayThanHigherups extends Configured implements Tool { public static class M extends Mapper{ @Override public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String line = value.toString(); String id = line.substring(1, 11).trim(); String name = line.substring(11, 21).trim(); String sal = line.substring(57, 68).trim(); String pid = line.substring(32, 43).trim(); context.write(new Text(pid), new Text("EMP," + pid + "," + name + "," + sal + "," + id)); context.write(new Text(id), new Text("BOSS," + id + "," + name + "," + sal + "," + pid)); } } public static class R extends Reducer { @Override public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException { String bossName = null; int bossSal = 0; List emps = new ArrayList (); for (Text value : values) { System.out.println(value); String[] ss = value.toString().split(","); if (ss[0].equals("EMP")) {// 可能有多个 emps.add(new Emp(ss[2], Integer.parseInt(ss[3]))); } else if (ss[0].equals("BOSS")) {// 只有一个 bossName = ss[2]; bossSal = Integer.parseInt(ss[3]); } } for (Emp e : emps) { if (bossSal > 0 && e.getSal() > bossSal) { context.write(null, new Text(e.getName() + "," + e.getSal() + "," + bossName + "," + bossSal)); } } } } @Override public int run(String[] args) throws Exception { Configuration conf = getConf(); Job job = new Job(conf, "Job-TotalSalaryByDeptMR"); job.setJarByClass(this.getClass()); job.setMapperClass(M.class); job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(Text.class); job.setReducerClass(R.class); job.setOutputFormatClass(TextOutputFormat.class); job.setOutputKeyClass(NullWritable.class); // 指定输出的KEY的格式 job.setOutputValueClass(Text.class); // 指定输出的VALUE的格式 FileInputFormat.addInputPath(job, new Path(args[0])); // 输入路径 FileOutputFormat.setOutputPath(job, new Path(args[1])); // 输出路径 return job.waitForCompletion(true) ? 0 : 1; // job.waitForCompletion(true); // return job.isSuccessful() ? 0 : 1; } /** * * @param args hdfs://bd11:9000/user/wukong/w07/emp.txt hdfs://bd11:9000/user/wukong/w07/out05/ * @throws Exception */ public static void main(String[] args) throws Exception { checkArgs(args); HdfsUtil.rm(args[1], true); Date start = new Date(); int res = ToolRunner.run(new Configuration(), new MorePayThanHigherups(), args); printExcuteTime(start, new Date()); System.exit(res); } /** * 判断参数个数是否正确,如果无参数运行则显示以作程序说明。 * * @param args */ private static void checkArgs(String[] args) { if (args.length != 2) { System.err.println(""); System.err.println("Usage: Test_1 < input path > < output path > "); System.err .println("Example: hadoop jar ~/Test_1.jar hdfs://localhost:9000/home/james/Test_1 hdfs://localhost:9000/home/james/output"); System.err.println("Counter:"); System.err.println("\t" + "LINESKIP" + "\t" + "Lines which are too short"); System.exit(-1); } } /** * 打印程序运行时间 * * @param start * @param end */ private static void printExcuteTime(Date start, Date end) { DateFormat formatter = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); float time = (float) ((end.getTime() - start.getTime()) / 60000.0); System.out.println("任务开始:" + formatter.format(start)); System.out.println("任务结束:" + formatter.format(end)); System.out.println("任务耗时:" + String.valueOf(time) + " 分钟"); }}class Emp { private String name; private int sal; /** * @param name * @param sal */ public Emp(String name, int sal) { super(); this.name = name; this.sal = sal; } public String getName() { return name; } public int getSal() { return sal; }}
运行结果
FORD,3000,JONES,2975
控制台
14/08/31 23:09:06 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable14/08/31 23:09:06 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).14/08/31 23:09:07 INFO input.FileInputFormat: Total input paths to process : 114/08/31 23:09:07 WARN snappy.LoadSnappy: Snappy native library not loaded14/08/31 23:09:07 INFO mapred.JobClient: Running job: job_local1925230448_000114/08/31 23:09:07 INFO mapred.LocalJobRunner: Waiting for map tasks14/08/31 23:09:07 INFO mapred.LocalJobRunner: Starting task: attempt_local1925230448_0001_m_000000_014/08/31 23:09:07 INFO mapred.Task: Using ResourceCalculatorPlugin : null14/08/31 23:09:07 INFO mapred.MapTask: Processing split: hdfs://bd11:9000/user/wukong/w07/emp.txt:0+111914/08/31 23:09:07 INFO mapred.MapTask: io.sort.mb = 10014/08/31 23:09:07 INFO mapred.MapTask: data buffer = 79691776/9961472014/08/31 23:09:07 INFO mapred.MapTask: record buffer = 262144/32768014/08/31 23:09:07 INFO mapred.MapTask: Starting flush of map output14/08/31 23:09:07 INFO mapred.MapTask: Finished spill 014/08/31 23:09:07 INFO mapred.Task: Task:attempt_local1925230448_0001_m_000000_0 is done. And is in the process of commiting14/08/31 23:09:07 INFO mapred.LocalJobRunner: 14/08/31 23:09:07 INFO mapred.Task: Task 'attempt_local1925230448_0001_m_000000_0' done.14/08/31 23:09:07 INFO mapred.LocalJobRunner: Finishing task: attempt_local1925230448_0001_m_000000_014/08/31 23:09:07 INFO mapred.LocalJobRunner: Map task executor complete.14/08/31 23:09:07 INFO mapred.Task: Using ResourceCalculatorPlugin : null14/08/31 23:09:07 INFO mapred.LocalJobRunner: 14/08/31 23:09:07 INFO mapred.Merger: Merging 1 sorted segments14/08/31 23:09:07 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 766 bytes14/08/31 23:09:07 INFO mapred.LocalJobRunner: EMP,,KING,5000,7839BOSS,7369,SMITH,800,7902BOSS,7499,ALLEN,1600,7698BOSS,7521,WARD,1250,7698EMP,7566,FORD,3000,7902BOSS,7566,JONES,2975,7839BOSS,7654,MARTIN,1250,7698EMP,7698,WARD,1250,7521EMP,7698,JAMES,950,7900EMP,7698,MARTIN,1250,7654EMP,7698,ALLEN,1600,7499BOSS,7698,BLAKE,2850,7839EMP,7698,TURNER,1500,7844BOSS,7782,CLARK,2450,7839EMP,7782,MILLER,1300,7934BOSS,7839,KING,5000,EMP,7839,CLARK,2450,7782EMP,7839,BLAKE,2850,7698EMP,7839,JONES,2975,7566BOSS,7844,TURNER,1500,7698BOSS,7900,JAMES,950,7698EMP,7902,SMITH,800,7369BOSS,7902,FORD,3000,7566BOSS,7934,MILLER,1300,778214/08/31 23:09:07 INFO mapred.Task: Task:attempt_local1925230448_0001_r_000000_0 is done. And is in the process of commiting14/08/31 23:09:07 INFO mapred.LocalJobRunner: 14/08/31 23:09:07 INFO mapred.Task: Task attempt_local1925230448_0001_r_000000_0 is allowed to commit now14/08/31 23:09:07 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1925230448_0001_r_000000_0' to hdfs://bd11:9000/user/wukong/w07/out0514/08/31 23:09:07 INFO mapred.LocalJobRunner: reduce > reduce14/08/31 23:09:07 INFO mapred.Task: Task 'attempt_local1925230448_0001_r_000000_0' done.14/08/31 23:09:08 INFO mapred.JobClient: map 100% reduce 100/08/31 23:09:08 INFO mapred.JobClient: Job complete: job_local1925230448_000114/08/31 23:09:08 INFO mapred.JobClient: Counters: 1914/08/31 23:09:08 INFO mapred.JobClient: File Output Format Counters 14/08/31 23:09:08 INFO mapred.JobClient: Bytes Written=2114/08/31 23:09:08 INFO mapred.JobClient: File Input Format Counters 14/08/31 23:09:08 INFO mapred.JobClient: Bytes Read=111914/08/31 23:09:08 INFO mapred.JobClient: FileSystemCounters14/08/31 23:09:08 INFO mapred.JobClient: FILE_BYTES_READ=108214/08/31 23:09:08 INFO mapred.JobClient: HDFS_BYTES_READ=223814/08/31 23:09:08 INFO mapred.JobClient: FILE_BYTES_WRITTEN=13988214/08/31 23:09:08 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=2114/08/31 23:09:08 INFO mapred.JobClient: Map-Reduce Framework14/08/31 23:09:08 INFO mapred.JobClient: Reduce input groups=1314/08/31 23:09:08 INFO mapred.JobClient: Map output materialized bytes=77014/08/31 23:09:08 INFO mapred.JobClient: Combine output records=014/08/31 23:09:08 INFO mapred.JobClient: Map input records=1214/08/31 23:09:08 INFO mapred.JobClient: Reduce shuffle bytes=014/08/31 23:09:08 INFO mapred.JobClient: Reduce output records=114/08/31 23:09:08 INFO mapred.JobClient: Spilled Records=4814/08/31 23:09:08 INFO mapred.JobClient: Map output bytes=71614/08/31 23:09:08 INFO mapred.JobClient: Total committed heap usage (bytes)=32610713614/08/31 23:09:08 INFO mapred.JobClient: SPLIT_RAW_BYTES=10514/08/31 23:09:08 INFO mapred.JobClient: Map output records=2414/08/31 23:09:08 INFO mapred.JobClient: Combine input records=014/08/31 23:09:08 INFO mapred.JobClient: Reduce input records=24任务开始:2014-08-31 23:09:06任务结束:2014-08-31 23:09:08任务耗时:0.023083333 分钟
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