MapReduce编程系列 — 3：数据去重

时间：2015-12-05 11:11:56 阅读：244 评论：0 收藏：0 [点我收藏+]

标签：

1、项目名称：

技术分享

2、程序代码：

package com.dedup;

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.GenericOptionsParser;

public class Dedup {
    //map将输入中的value复制到输出数据的key上，并直接输出，注意参数类型和个数
    public static class Map extends Mapper<Object, Text, Text, Text>{
        public static Text line = new Text();
        //注意参数类型和个数
        public void map(Object key , Text value , Context context) throws IOException,InterruptedException{
            System.out.println("mapper.......");
            System.out.println("key:"+key+"  value:"+value);
            line = value;
            context.write(line, new Text(" "));    
            System.out.println("line:"+ line +" value"+ value +"  context:" + context);
        }        
    }
    //reduce将输入中的key复制到输出数据的key上，并直接输出，注意参数类型和个数
    public static class Reduce extends Reducer<Text, Text, Text, Text>{
        //注意参数类型和个数
        public void reduce(Text key , Iterable<Text> values, Context context)throws IOException,InterruptedException{
            System.out.println("reducer.......");
            System.out.println("key:"+key+"  values:"+values);
            context.write(key, new Text(" "));
            System.out.println("key:"+key+"  values"+values+"  context:"+context);
        }
    }

    public static void main(String [] args)throws Exception{
        Configuration conf = new Configuration();
        String otherArgs[] = new GenericOptionsParser(conf,args).getRemainingArgs();
        if(otherArgs.length!=2){
            System.out.println("Usage:dedup <in> <out>");
            System.exit(2);
        }
        Job job = new Job(conf,"Data Deduplication");
        job.setJarByClass(Dedup.class);

        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));        
        System.exit(job.waitForCompletion(true)? 0 : 1 );
    }
}

3、测试数据：

file1：

2006-6-9 a
2006-6-10 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-15 c
2006-6-11 c

file2：

2006-6-9 b
2006-6-10 a
2006-6-11 b
2006-6-12 d
2006-6-13 a
2006-6-14 c
2006-6-15 d
2006-6-11 c

4、运行过程：

14/09/21 16:51:16 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/09/21 16:51:16 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
14/09/21 16:51:16 INFO input.FileInputFormat: Total input paths to process : 2
14/09/21 16:51:16 WARN snappy.LoadSnappy: Snappy native library not loaded
14/09/21 16:51:16 INFO mapred.JobClient: Running job: job_local_0001
14/09/21 16:51:16 INFO util.ProcessTree: setsid exited with exit code 0
14/09/21 16:51:16 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@2e9aa770
14/09/21 16:51:16 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:16 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:16 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 a
line:2006-6-9 a value2006-6-9 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:11 value:2006-6-10 b
line:2006-6-10 b value2006-6-10 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:23 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:59 value:2006-6-14 b
line:2006-6-14 b value2006-6-14 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:71 value:2006-6-15 c
line:2006-6-15 c value2006-6-15 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
14/09/21 16:51:16 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:16 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:16 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
14/09/21 16:51:17 INFO mapred.JobClient: map 0% reduce 0%
14/09/21 16:51:19 INFO mapred.LocalJobRunner:
14/09/21 16:51:19 INFO mapred.Task: Task ‘attempt_local_0001_m_000000_0‘ done.
14/09/21 16:51:19 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3697e580
14/09/21 16:51:19 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:19 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:19 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 b
line:2006-6-9 b value2006-6-9 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:11 value:2006-6-10 a
line:2006-6-10 a value2006-6-10 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:23 value:2006-6-11 b
line:2006-6-11 b value2006-6-11 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:59 value:2006-6-14 c
line:2006-6-14 c value2006-6-14 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:71 value:2006-6-15 d
line:2006-6-15 d value2006-6-15 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
14/09/21 16:51:19 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:19 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:19 INFO mapred.Task: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
14/09/21 16:51:20 INFO mapred.JobClient: map 100% reduce 0%
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task ‘attempt_local_0001_m_000001_0‘ done.
14/09/21 16:51:22 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3c844c07
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Merger: Merging 2 sorted segments
14/09/21 16:51:22 INFO mapred.Merger: Down to the last merge-pass, with 2 segments left of total size: 258 bytes
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
reducer.......
key:2006-6-10 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-10 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-12 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-12 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-13 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-13 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
14/09/21 16:51:22 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
14/09/21 16:51:22 INFO output.FileOutputCommitter: Saved output of task ‘attempt_local_0001_r_000000_0‘ to hdfs://localhost:9000/user/hadoop/dedup_output
14/09/21 16:51:25 INFO mapred.LocalJobRunner: reduce > reduce
14/09/21 16:51:25 INFO mapred.Task: Task ‘attempt_local_0001_r_000000_0‘ done.
14/09/21 16:51:26 INFO mapred.JobClient: map 100% reduce 100%
14/09/21 16:51:26 INFO mapred.JobClient: Job complete: job_local_0001
14/09/21 16:51:26 INFO mapred.JobClient: Counters: 22
14/09/21 16:51:26 INFO mapred.JobClient:   Map-Reduce Framework
14/09/21 16:51:26 INFO mapred.JobClient:     Spilled Records=32
14/09/21 16:51:26 INFO mapred.JobClient:     Map output materialized bytes=266
14/09/21 16:51:26 INFO mapred.JobClient:     Reduce input records=16
14/09/21 16:51:26 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient:     Map input records=16
14/09/21 16:51:26 INFO mapred.JobClient:     SPLIT_RAW_BYTES=232
14/09/21 16:51:26 INFO mapred.JobClient:     Map output bytes=222
14/09/21 16:51:26 INFO mapred.JobClient:     Reduce shuffle bytes=0
14/09/21 16:51:26 INFO mapred.JobClient:     Physical memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient:     Reduce input groups=12
14/09/21 16:51:26 INFO mapred.JobClient:     Combine output records=0
14/09/21 16:51:26 INFO mapred.JobClient:     Reduce output records=12
14/09/21 16:51:26 INFO mapred.JobClient:     Map output records=16
14/09/21 16:51:26 INFO mapred.JobClient:     Combine input records=0
14/09/21 16:51:26 INFO mapred.JobClient:     CPU time spent (ms)=0
14/09/21 16:51:26 INFO mapred.JobClient:     Total committed heap usage (bytes)=813170688
14/09/21 16:51:26 INFO mapred.JobClient:   File Input Format Counters
14/09/21 16:51:26 INFO mapred.JobClient:     Bytes Read=190
14/09/21 16:51:26 INFO mapred.JobClient:   FileSystemCounters
14/09/21 16:51:26 INFO mapred.JobClient:     HDFS_BYTES_READ=475
14/09/21 16:51:26 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=122061
14/09/21 16:51:26 INFO mapred.JobClient:     FILE_BYTES_READ=1665
14/09/21 16:51:26 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=166
14/09/21 16:51:26 INFO mapred.JobClient:   File Output Format Counters
14/09/21 16:51:26 INFO mapred.JobClient:     Bytes Written=166

5、运行结果：

2006-6-10 a
2006-6-10 b
2006-6-11 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-14 c
2006-6-15 c
2006-6-15 d
2006-6-9 a
2006-6-9 b

MapReduce编程系列 — 3：数据去重

标签：

原文地址：http://www.cnblogs.com/yangyquin/p/5021166.html

踩

(0)

评论一句话评论（0）

分享档案

更多>

2021年07月29日 (22)
2021年07月28日 (40)
2021年07月27日 (32)
2021年07月26日 (79)
2021年07月23日 (29)
2021年07月22日 (30)
2021年07月21日 (42)
2021年07月20日 (16)
2021年07月19日 (90)
2021年07月16日 (35)

周排行