参考代码

TVPlayCount.java

package com.dajiangtai.hadoop.tvplay;

import java.io.IOException;

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.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.MultipleOutputs;

import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

import org.apache.hadoop.util.Tool;

import org.apache.hadoop.util.ToolRunner;

import com.sun.org.apache.bcel.internal.generic.NEW;

public class TVPlayCount extends Configured implements Tool{

    public static class TVPlayMapper extends Mapper<Text, TVPlayData, Text, TVPlayData>{

        @Override

        protected void map(Text key, TVPlayData value,Context context)

                throws IOException, InterruptedException

                {

                     context.write(key, value);

                }

    }

    public static class TVPlayReducer extends Reducer<Text, TVPlayData, Text, Text>

    {

        private Text m_key=new Text();

        private Text m_value = new Text();

        private MultipleOutputs<Text, Text> mos;

        //将多路输出打开

        protected void setup(Context context) throws IOException,InterruptedException

        {

            mos = new MultipleOutputs<Text, Text>(context);

        }

        protected void reduce (Text Key,Iterable<TVPlayData> Values, Context context)

                throws IOException, InterruptedException{

            int daynumber = ;

            int collectnumber = ;

            int commentnumber = ;

            int againstnumber = ;

            int supportnumber = ;

            for (TVPlayData tv : Values){

                daynumber+=tv.getDaynumber();

                collectnumber+=tv.getCollectnumber();

                commentnumber += tv.getCommentnumber();

                againstnumber += tv.getAgainstnumber();

                supportnumber += tv.getSupportnumber();

            }

            String[] records=Key.toString().split("\t");

            // 1优酷 2搜狐   3 土豆    4爱奇艺    5迅雷看看

            String source =records[]; // 媒体类别

            m_key.set(records[]);

            m_value.set(daynumber+"\t"+collectnumber+"\t" +commentnumber+"\t"+againstnumber+"\t"+supportnumber);

        if(source.equals("")){

            mos.write("youku", m_key, m_value);

        }else if (source.equals("")) {

            mos.write("souhu", m_key, m_value);

        } else if (source.equals("")) {

            mos.write("tudou", m_key, m_value);

        } else if (source.equals("")) {

            mos.write("aiqiyi", m_key, m_value);

        } else if (source.equals("")) {

            mos.write("xunlei", m_key, m_value);

        }

    }

        //关闭 MultipleOutputs，也就是关闭 RecordWriter，并且是一堆 RecordWriter，因为这里会有很多 reduce 被调用。

    protected void cleanup( Context context) throws IOException,InterruptedException     {

        mos.close();

    }

}

    @Override

    public int run(String[] args) throws Exception {

        Configuration conf = new Configuration(); // 配置文件对象

        Path mypath = new Path(args[]);

        FileSystem hdfs = mypath.getFileSystem(conf);// 创建输出路径

        if (hdfs.isDirectory(mypath)) {

            hdfs.delete(mypath, true);

        }

        Job job = new Job(conf, "tvplay");// 构造任务

        job.setJarByClass(TVPlayCount.class);// 设置主类

        job.setMapperClass(TVPlayMapper.class);// 设置Mapper

        job.setMapOutputKeyClass(Text.class);// key输出类型

        job.setMapOutputValueClass(TVPlayData.class);// value输出类型

        job.setInputFormatClass(TVPlayInputFormat.class);//自定义输入格式

        job.setReducerClass(TVPlayReducer.class);// 设置Reducer

        job.setOutputKeyClass(Text.class);// reduce key类型

        job.setOutputValueClass(Text.class);// reduce value类型

        // 自定义文件输出格式，通过路径名（pathname）来指定输出路径

        MultipleOutputs.addNamedOutput(job, "youku", TextOutputFormat.class,

                Text.class, Text.class);

        MultipleOutputs.addNamedOutput(job, "souhu", TextOutputFormat.class,

                Text.class, Text.class);

        MultipleOutputs.addNamedOutput(job, "tudou", TextOutputFormat.class,

                Text.class, Text.class);

        MultipleOutputs.addNamedOutput(job, "aiqiyi", TextOutputFormat.class,

                Text.class, Text.class);

        MultipleOutputs.addNamedOutput(job, "xunlei", TextOutputFormat.class,

                Text.class, Text.class);

        FileInputFormat.addInputPath(job, new Path(args[]));// 输入路径

        FileOutputFormat.setOutputPath(job, new Path(args[]));// 输出路径

        job.waitForCompletion(true);

        return ;

    }

    public static void main(String[] args) throws Exception{

        String[] args0={"hdfs://master:9000/tvplay/",

        "hdfs://master:9000/tvplay/out"};

    int ec = ToolRunner.run(new Configuration(), new TVPlayCount(), args0);

    System.exit(ec);

    }

}

TVPlayData.java

package com.dajiangtai.hadoop.tvplay;

import java.io.DataInput;

import java.io.DataOutput;

import java.io.IOException;

import org.apache.hadoop.io.WritableComparable;

/**

 *

 * @author yangjun

 * @function 自定义对象

 */

public class TVPlayData implements WritableComparable<Object>{

    private int daynumber;

    private int collectnumber;

    private int commentnumber;

    private int againstnumber;

    private int supportnumber;

    public TVPlayData(){}

    public void set(int daynumber,int collectnumber,int commentnumber,int againstnumber,int supportnumber){

        this.daynumber = daynumber;

        this.collectnumber = collectnumber;

        this.commentnumber = commentnumber;

        this.againstnumber = againstnumber;

        this.supportnumber = supportnumber;

    }

    public int getDaynumber() {

        return daynumber;

    }

    public void setDaynumber(int daynumber) {

        this.daynumber = daynumber;

    }

    public int getCollectnumber() {

        return collectnumber;

    }

    public void setCollectnumber(int collectnumber) {

        this.collectnumber = collectnumber;

    }

    public int getCommentnumber() {

        return commentnumber;

    }

    public void setCommentnumber(int commentnumber) {

        this.commentnumber = commentnumber;

    }

    public int getAgainstnumber() {

        return againstnumber;

    }

    public void setAgainstnumber(int againstnumber) {

        this.againstnumber = againstnumber;

    }

    public int getSupportnumber() {

        return supportnumber;

    }

    public void setSupportnumber(int supportnumber) {

        this.supportnumber = supportnumber;

    }

    @Override

    public void readFields(DataInput in) throws IOException {

        daynumber = in.readInt();

        collectnumber = in.readInt();

        commentnumber = in.readInt();

        againstnumber = in.readInt();

        supportnumber = in.readInt();

    }

    @Override

    public void write(DataOutput out) throws IOException {

        out.writeInt(daynumber);

        out.writeInt(collectnumber);

        out.writeInt(commentnumber);

        out.writeInt(againstnumber);

        out.writeInt(supportnumber);

    }

    @Override

    public int compareTo(Object o) {

        return ;

    };

}

TVPlayInputFormat.java

package com.dajiangtai.hadoop.tvplay;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.FSDataInputStream;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.InputSplit;

import org.apache.hadoop.mapreduce.RecordReader;

import org.apache.hadoop.mapreduce.TaskAttemptContext;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.input.FileSplit;

import org.apache.hadoop.util.LineReader;

/**

 *

 * @author yangjun

 * @function key vlaue 输入格式

 */

public class TVPlayInputFormat extends FileInputFormat<Text,TVPlayData>{

    @Override

    public RecordReader<Text, TVPlayData> createRecordReader(InputSplit input,

            TaskAttemptContext context) throws IOException, InterruptedException {

        return new TVPlayRecordReader();

    }

    public class TVPlayRecordReader extends RecordReader<Text, TVPlayData>{

        public LineReader in;

        public Text lineKey;

        public TVPlayData lineValue;

        public Text line;

        @Override

        public void close() throws IOException {

            if(in !=null){

                in.close();

            }

        }

        @Override

        public Text getCurrentKey() throws IOException, InterruptedException {

            return lineKey;

        }

        @Override

        public TVPlayData getCurrentValue() throws IOException, InterruptedException {

            return lineValue;

        }

        @Override

        public float getProgress() throws IOException, InterruptedException {

            return ;

        }

        @Override

        public void initialize(InputSplit input, TaskAttemptContext context)

                throws IOException, InterruptedException {

            FileSplit split=(FileSplit)input;

            Configuration job=context.getConfiguration();

            Path file=split.getPath();

            FileSystem fs=file.getFileSystem(job);  

            FSDataInputStream filein=fs.open(file);

            in=new LineReader(filein,job);

            line=new Text();

            lineKey=new Text();

            lineValue = new TVPlayData();

        }

        @Override

        public boolean nextKeyValue() throws IOException, InterruptedException {

            int linesize=in.readLine(line);

            if(linesize==)  return false;

            String[] pieces = line.toString().split("\t");

            if(pieces.length != ){

                throw new IOException("Invalid record received");

            }

            lineKey.set(pieces[]+"\t"+pieces[]);

            lineValue.set(Integer.parseInt(pieces[]),Integer.parseInt(pieces[]),Integer.parseInt(pieces[])

                    ,Integer.parseInt(pieces[]),Integer.parseInt(pieces[]));

            return true;

        }

    }

}

先启动3节点集群

与自己在本地搭建的3节点集群的hdfs连接上

在终端显示的运行结果，程序没有错误

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - session.id is deprecated. Instead, use dfs.metrics.session-id

-- ::, INFO [org.apache.hadoop.metrics.jvm.JvmMetrics] - Initializing JVM Metrics with processName=JobTracker, sessionId=

-- ::, WARN [org.apache.hadoop.mapreduce.JobSubmitter] - Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.

-- ::, WARN [org.apache.hadoop.mapreduce.JobSubmitter] - No job jar file set.  User classes may not be found. See Job or Job#setJar(String).

-- ::, INFO [org.apache.hadoop.mapreduce.lib.input.FileInputFormat] - Total input paths to process :

-- ::, INFO [org.apache.hadoop.mapreduce.JobSubmitter] - number of splits:

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - user.name is deprecated. Instead, use mapreduce.job.user.name

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.mapoutput.value.class is deprecated. Instead, use mapreduce.map.output.value.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.job.name is deprecated. Instead, use mapreduce.job.name

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.mapoutput.key.class is deprecated. Instead, use mapreduce.map.output.key.class

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir

-- ::, INFO [org.apache.hadoop.mapreduce.JobSubmitter] - Submitting tokens for job: job_local300699497_0001

-- ::, WARN [org.apache.hadoop.conf.Configuration] - file:/tmp/hadoop-Administrator/mapred/staging/Administrator300699497/.staging/job_local300699497_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.

-- ::, WARN [org.apache.hadoop.conf.Configuration] - file:/tmp/hadoop-Administrator/mapred/staging/Administrator300699497/.staging/job_local300699497_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.

-- ::, WARN [org.apache.hadoop.conf.Configuration] - file:/tmp/hadoop-Administrator/mapred/local/localRunner/Administrator/job_local300699497_0001/job_local300699497_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.

-- ::, WARN [org.apache.hadoop.conf.Configuration] - file:/tmp/hadoop-Administrator/mapred/local/localRunner/Administrator/job_local300699497_0001/job_local300699497_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.

-- ::, INFO [org.apache.hadoop.mapreduce.Job] - The url to track the job: http://localhost:8080/

-- ::, INFO [org.apache.hadoop.mapreduce.Job] - Running job: job_local300699497_0001

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - OutputCommitter set in config null

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - Waiting for map tasks

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - Starting task: attempt_local300699497_0001_m_000000_0

-- ::, INFO [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] - ProcfsBasedProcessTree currently is supported only on Linux.

-- ::, INFO [org.apache.hadoop.mapred.Task] -  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@1b9156ad

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - Processing split: hdfs://master:9000/tvplay/tvplay.txt:0+10833923

-- ::, INFO [org.apache.hadoop.mapreduce.Job] - Job job_local300699497_0001 running in uber mode : false

-- ::, INFO [org.apache.hadoop.mapreduce.Job] -  map % reduce %

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - (EQUATOR)  kvi ()

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - mapreduce.task.io.sort.mb:

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - soft limit at

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - bufstart = ; bufvoid =

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - kvstart = ; length =

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] -

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - Starting flush of map output

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - Spilling map output

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - bufstart = ; bufend = ; bufvoid =

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - kvstart = (); kvend = (); length = /

-- ::, INFO [org.apache.hadoop.mapred.MapTask] - Finished spill

-- ::, INFO [org.apache.hadoop.mapred.Task] - Task:attempt_local300699497_0001_m_000000_0 is done. And is in the process of committing

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - map

-- ::, INFO [org.apache.hadoop.mapred.Task] - Task 'attempt_local300699497_0001_m_000000_0' done.

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - Finishing task: attempt_local300699497_0001_m_000000_0

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - Map task executor complete.

-- ::, INFO [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] - ProcfsBasedProcessTree currently is supported only on Linux.

-- ::, INFO [org.apache.hadoop.mapred.Task] -  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@fba110e

-- ::, INFO [org.apache.hadoop.mapred.Merger] - Merging  sorted segments

-- ::, INFO [org.apache.hadoop.mapred.Merger] - Down to the last merge-pass, with  segments left of total size:  bytes

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] -

-- ::, INFO [org.apache.hadoop.conf.Configuration.deprecation] - mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords

-- ::, INFO [org.apache.hadoop.mapreduce.Job] -  map % reduce %

-- ::, INFO [org.apache.hadoop.mapred.Task] - Task:attempt_local300699497_0001_r_000000_0 is done. And is in the process of committing

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] -

-- ::, INFO [org.apache.hadoop.mapred.Task] - Task attempt_local300699497_0001_r_000000_0 is allowed to commit now

-- ::, INFO [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] - Saved output of task 'attempt_local300699497_0001_r_000000_0' to hdfs://master:9000/tvplay/out/_temporary/0/task_local300699497_0001_r_000000

-- ::, INFO [org.apache.hadoop.mapred.LocalJobRunner] - reduce > reduce

-- ::, INFO [org.apache.hadoop.mapred.Task] - Task 'attempt_local300699497_0001_r_000000_0' done.

-- ::, INFO [org.apache.hadoop.mapreduce.Job] -  map % reduce %

-- ::, INFO [org.apache.hadoop.mapreduce.Job] - Job job_local300699497_0001 completed successfully

-- ::, INFO [org.apache.hadoop.mapreduce.Job] - Counters:

    File System Counters

        FILE: Number of bytes read=

        FILE: Number of bytes written=

        FILE: Number of read operations=

        FILE: Number of large read operations=

        FILE: Number of write operations=

        HDFS: Number of bytes read=

        HDFS: Number of bytes written=

        HDFS: Number of read operations=

        HDFS: Number of large read operations=

        HDFS: Number of write operations=

    Map-Reduce Framework

        Map input records=

        Map output records=

        Map output bytes=

        Map output materialized bytes=

        Input split bytes=

        Combine input records=

        Combine output records=

        Reduce input groups=

        Reduce shuffle bytes=

        Reduce input records=

        Reduce output records=

        Spilled Records=

        Shuffled Maps =

        Failed Shuffles=

        Merged Map outputs=

        GC time elapsed (ms)=

        CPU time spent (ms)=

        Physical memory (bytes) snapshot=

        Virtual memory (bytes) snapshot=

        Total committed heap usage (bytes)=

    File Input Format Counters

        Bytes Read=

    File Output Format Counters

        Bytes Written=

查看hdfs上的输出结果

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