025_MapReduce样例Hadoop TopKey算法

1、需求说明

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" alt="" width="307" height="210" />

2、 某个文件中某列数据的最大值。

思路：对每一个列的值依次进行比较，保存最大的值进行输出，算法的思想类似于排序算法（快速和冒泡排序）。

Mapper：因为只是在wordcount统计的基础上统计的，只是针对一个列，故可以找到最大值后，将最大值和对应的text给，cleanup中的context.write（）方法，然后输出。此时不需要Reducer。

 package org.dragon.hadoop.mapreduce.app.topk;

 import java.io.IOException;

 import org.apache.hadoop.conf.Configuration;
 import org.apache.hadoop.fs.Path;
 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.lib.input.FileInputFormat;
 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

 /**
  * 功能：某个文件中某列数据的最大值某个文件中
  *
  * 针对wordcount程序输出的单词统计信息，求出单词出现频率最高的那个。 即：求给定的键值对中，value的最大值
  * @author ZhuXY
  * @time 2016-3-12 下午3:43:23
  *
  */
 public class TopKMapReduce {

     /*
      * ******************************************************
      * 这个程序很好解释了splitsize对应一个map task，而一行数据对应一个map()函数。 即一个map task对应几个map（）函数
      * ******************************************************
      */

     // Mapper class
     static class TopKMapper extends
             Mapper<LongWritable, Text, Text, LongWritable> {
         // map output key
         private Text mapOutputKey = new Text();//java的变量（对象）使用前一定要先创建

         // map output value
         private LongWritable mapOutputValue = new LongWritable(); 

         /*
          * ********************************
          * 此处创建对所有的map()函数有效
          * *******************************
          */

         // store max value,init long.MIN_VALUE
         private long topKValue = Long.MIN_VALUE;

         @Override
         protected void map(LongWritable key, Text value, Context context)
                 throws IOException, InterruptedException {
             // get value
             String lineValue =value.toString();
             String[] str = lineValue.split("\t");

             Long tempValue = Long.valueOf(str[1]);

             // comparator
             if (topKValue < tempValue) {
                 topKValue = tempValue;
                 // set mapout key当找到相对的最大值给topKValue时，将该单词同时赋值给输出key
                 mapOutputKey.set(str[0]);
             }

             // 此处的context不需要填写，查看源码发现context是个内部类，源码中是由cleanup负责处理
         }

         @Override
         protected void setup(Context context) throws IOException,
                 InterruptedException {
             super.setup(context);
         }

         @Override
         protected void cleanup(Context context) throws IOException,
                 InterruptedException {
             // set map output value
             mapOutputValue.set(topKValue);

             // set mapoutput context
             context.write(mapOutputKey, mapOutputValue);
         }
     }

     // Driver Code
     public int run(String[] args) throws Exception, IOException,
             InterruptedException {
         // get conf
         Configuration conf = new Configuration();

         // create job
         Job job = new Job(conf, TopKMapReduce.class.getSimpleName());

         // set job
         job.setJarByClass(TopKMapReduce.class);
         // 1) input
         Path inputDirPath = new Path(args[0]);
         FileInputFormat.addInputPath(job, inputDirPath);

         // 2) map
         job.setMapperClass(TopKMapper.class);
         job.setMapOutputKeyClass(Text.class);
         job.setMapOutputValueClass(LongWritable.class);

         // 3) reduce
         // job.setReducerClass(DataTotalReducer.class);
         // job.setOutputKeyClass(Text.class);
         // job.setOutputValueClass(DataWritable.class);
         job.setNumReduceTasks(0);// 因为本程序没有Reducer的过程，这里必须设置为0

         // 4) output
         Path outputDir = new Path(args[1]);
         FileOutputFormat.setOutputPath(job, outputDir);

         // submit job
         boolean isSuccess = job.waitForCompletion(true);

         // return status
         return isSuccess ? 0 : 1;
     }

     // run mapreduce
     public static void main(String[] args) throws Exception, IOException,
             InterruptedException {
         // set args
         args = new String[] { "hdfs://hadoop-master:9000/wc/wcoutput",
                 "hdfs://hadoop-master:9000/wc/output" };

         // run job
         int status = new TopKMapReduce().run(args);
         // exit
         System.exit(status);
     }

 }

View TopKMapReduce Code

3、 某个文件某列数据的Top Key的值（最大或者最小）

思路：用一个TreeMap保存，TreeMap可以自动根据Key排序，故将出现的次数当做Key进行hash存储。然后TreeMap.size()>NUM时,删除最小的就行了。

Mapper：在原有的基础上增加TreeMap

 package org.dragon.hadoop.mapreduce.app.topk;

 import java.io.IOException;
 import java.util.Iterator;
 import java.util.Set;
 import java.util.TreeMap;

 import org.apache.hadoop.conf.Configuration;
 import org.apache.hadoop.fs.Path;
 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.lib.input.FileInputFormat;
 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

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

 /**
  * 功能：某列的TopKey的值，即最大（小）的几个。K小值问题
  *
  * @author ZhuXY
  * @time 2016-3-12 下午3:43:23
  *
  */
 public class TopKMapReduceV2 {

     /*
      * 思想：用一個集合TreeSet存儲對應的鍵值對，然後當大於三個的時候進行刪除。
      *  该集合自动按照键进行排序，然后保留最大的三个
      *  注意：集合   key   value
      *      真是  value    key
      */

     // Mapper class
     static class TopKMapper extends
             Mapper<LongWritable, Text, Text, LongWritable> {

         // 用作保存TopKey的键和值
         private TreeMap<Long, String> topKTreeMap = new TreeMap<Long, String>();

         @Override
         protected void map(LongWritable key, Text value, Context context)
                 throws IOException, InterruptedException {
             // get value
             String lineValue = value.toString();
             String[] str = lineValue.split("\t");

             long tempKey = Long.valueOf(str[1]);
             String tempValue = String.valueOf(str[0]);

             topKTreeMap.put(tempKey, tempValue);
             if (topKTreeMap.size() > 3) {
                 topKTreeMap.remove(topKTreeMap.firstKey());
             }
         }

         @Override
         protected void setup(Context context) throws IOException,
                 InterruptedException {
             super.setup(context);
         }

         @Override
         protected void cleanup(Context context) throws IOException,
                 InterruptedException {
             Set<Long> mapValueSet = topKTreeMap.keySet();// long 名字起得不好

             Text mapOutputKey = new Text();
             LongWritable mapOutputValue = new LongWritable();

 //            for (Iterator<Long> iterator = mapValueSet.iterator(); iterator
 //                    .hasNext();) {
 //
 //                long iteratorNum=iterator.next();
 //                mapOutputValue.set(iteratorNum);// long
 //                mapOutputKey.set(topKTreeMap.get(iteratorNum));
 //
 //                context.write(mapOutputKey, mapOutputValue);
 //            }

             for(long key:mapValueSet){
                 mapOutputValue.set(key);// long
                 mapOutputKey.set(topKTreeMap.get(key));

                 context.write(mapOutputKey, mapOutputValue);
             }
         }
     }

     // Driver Code
     public int run(String[] args) throws Exception, IOException,
             InterruptedException {
         // get conf
         Configuration conf = new Configuration();

         // create job
         Job job = new Job(conf, TopKMapReduceV2.class.getSimpleName());

         // set job
         job.setJarByClass(TopKMapReduceV2.class);
         // 1) input
         Path inputDirPath = new Path(args[0]);
         FileInputFormat.addInputPath(job, inputDirPath);

         // 2) map
         job.setMapperClass(TopKMapper.class);
         job.setMapOutputKeyClass(Text.class);
         job.setMapOutputValueClass(LongWritable.class);

         // 3) reduce
         // job.setReducerClass(DataTotalReducer.class);
         // job.setOutputKeyClass(Text.class);
         // job.setOutputValueClass(DataWritable.class);
         job.setNumReduceTasks(0);// 因为本程序没有Reducer的过程，这里必须设置为0

         // 4) output
         Path outputDir = new Path(args[1]);
         FileOutputFormat.setOutputPath(job, outputDir);

         // submit job
         boolean isSuccess = job.waitForCompletion(true);

         // return status
         return isSuccess ? 0 : 1;
     }

     // run mapreduce
     public static void main(String[] args) throws Exception, IOException,
             InterruptedException {
         // set args
         args = new String[] { "hdfs://hadoop-master:9000/wc/wcoutput",
                 "hdfs://hadoop-master:9000/wc/output1" };

         // run job
         int status = new TopKMapReduceV2().run(args);
         // exit
         System.exit(status);
     }

 }

View TopKMapReduceV2 Code

4、 多个文件中某列数据的Top Key的值（最大或者最小）

思路：此处因为是多个文件，故Reducer至少且只能为1个，即default也就是1个。将TreeMap放在Reducer内部的reduce函数进行处理。

 package org.dragon.hadoop.mapreduce.app.topk;

 import java.io.IOException;
 import java.util.Iterator;
 import java.util.Set;
 import java.util.TreeMap;

 import org.apache.hadoop.conf.Configuration;
 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.Mapper.Context;
 import org.apache.hadoop.mapreduce.Reducer;
 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 import org.eclipse.core.internal.filesystem.local.Convert;

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

 /**
  * 功能：多个文件中某列数据和的最大值
  *
  * 思想：类似wordcount，把每行数据统计好，context出去---mapper
  *         接收到经过shuffle和merge形成<key,list<1,2,3,4…>>----透明
  *         在cleanup中，收集reduce中的TreeMap集合，进行排序删除-------reduce、cleanup
  *
  * @author ZhuXY
  * @time 2016-3-12 下午3:43:23
  *
  */
 public class TopKMapReduceV3 {

     /*
      * 思想：用一個集合TreeSet存儲對應的鍵值對，然後當大於三個的時候進行刪除。
      *  该集合自动按照键进行排序，然后保留最大的三个
      *  注意：集合   key   value
      *      真是  value    key
      */

     // Mapper class
     static class TopKMapper extends
             Mapper<LongWritable, Text, Text, LongWritable> {

         Text mapOutputKey=new Text(); //key
         LongWritable mapOutputValue=new LongWritable();//value

         @Override
         protected void map(LongWritable key, Text value, Context context)
                 throws IOException, InterruptedException {
             // get value
             String lineValue = value.toString();
             String[] str = lineValue.split("\t");

             mapOutputKey.set(str[0]);

             mapOutputValue.set(Long.parseLong(str[1]));

             context.write(mapOutputKey, mapOutputValue);

         }
     }

     static class TopKReducer extends
             Reducer<Text, LongWritable, Text, LongWritable>{

         // 用作保存TopKey的键和值
         private TreeMap<Long, String> topKTreeMap = new TreeMap<Long, String>();

         @Override
         protected void reduce(Text key, Iterable<LongWritable> values,Context context)
                 throws IOException, InterruptedException {
             int sum=0;
             //循环遍历Interable
             for(LongWritable value:values)
             {
                 //累加
                 sum+=value.get();
             }

             long tempKey = Long.valueOf(sum);
             String tempValue = String.valueOf(key);

             topKTreeMap.put(tempKey, tempValue);
             if (topKTreeMap.size() > 3) {
                 topKTreeMap.remove(topKTreeMap.firstKey());
             }
         }

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

             //TreeMap键的集合
             Set<Long> mapValueSet = topKTreeMap.keySet();// long 名字起得不好

             Text mapOutputKey = new Text();
             LongWritable mapOutputValue = new LongWritable();

             //根据键，获取值，并交叉赋予context中参数
             for(long key:mapValueSet){
                 mapOutputValue.set(key);// long
                 mapOutputKey.set(topKTreeMap.get(key));

                 context.write(mapOutputKey, mapOutputValue);
             }
         }

     }

     // Driver Code
     public int run(String[] args) throws Exception, IOException,
             InterruptedException {
         // get conf
         Configuration conf = new Configuration();

         // create job
         Job job = new Job(conf, TopKMapReduceV3.class.getSimpleName());

         // set job
         job.setJarByClass(TopKMapReduceV3.class);
         // 1) input
         Path inputDirPath = new Path(args[0]);
         FileInputFormat.addInputPath(job, inputDirPath);

         // 2) map
         job.setMapperClass(TopKMapper.class);
         job.setMapOutputKeyClass(Text.class);
         job.setMapOutputValueClass(LongWritable.class);

         // 3) reduce
         job.setReducerClass(TopKReducer.class);
         job.setOutputKeyClass(Text.class);
         job.setOutputValueClass(LongWritable.class);
         //job.setNumReduceTasks(0);// default 1

         // 4) output
         Path outputDir = new Path(args[1]);
         FileOutputFormat.setOutputPath(job, outputDir);

         // submit job
         boolean isSuccess = job.waitForCompletion(true);

         // return status
         return isSuccess ? 0 : 1;
     }

     // run mapreduce
     public static void main(String[] args) throws Exception, IOException,
             InterruptedException {
         // set args
         args = new String[] { "hdfs://hadoop-master:9000/wc/wcinput",
                 "hdfs://hadoop-master:9000/wc/output2" };

         // run job
         int status = new TopKMapReduceV3().run(args);
         // exit
         System.exit(status);
     }

 }

View TopKMapReduceV3 Code

5、 统计和Top Key

思路：这个比较难。没有在统计好的基础上进行操作，而是直接统计，然后进行比较。具体看下面应用

数据格式：

语言类别    歌曲名称    收藏次数    播放次数    歌手名称

需求：

统计前十首播放次数最多的歌曲名称和次数。

测试数据：

经典老歌    我只在乎你    1234    34535    邓丽君
流行歌曲    流着泪说分手    125    2342    金志文
流行歌曲    菠萝菠萝蜜    543    536    谢娜
经典老歌    大花轿    123    3465    火风
流行歌曲    无所谓    3453    87654    杨坤

定义一个数据类型TopKWritable：

 package org.dragon.hadoop.mapreduce.app.topk;

 import java.io.DataInput;
 import java.io.DataOutput;
 import java.io.IOException;

 import org.apache.hadoop.io.WritableComparable;

 /**
  *
  * @author ZhuXY
  * @time   2016-3-13 下午7:30:21
  *
  */

 /**
  *
  * 数据格式：
  *         语言类别     歌曲名称     收藏次数     播放次数     歌手名称
  * 需求：
  *      统计前十首播放次数最多的歌曲名称和次数。
  */
 public class TopKWritable implements WritableComparable<TopKWritable>{
     private String languageType=null;
     private String songName=null;
     private long playNum=0;

     public TopKWritable(){

     }
     public TopKWritable(String languageType,String songName,long playNum){
         set(languageType, songName, playNum);
     }
     public void set(String languageType,String songName,Long playNum){
         this.languageType=languageType;
         this.songName=songName;
         this.playNum=playNum;
     }

     public String getLanguageType() {
         return languageType;
     }
     public String getSongName() {
         return songName;
     }
     public Long getPlayNum() {
         return playNum;
     }

     @Override
     public void write(DataOutput out) throws IOException {
         out.writeUTF(languageType);
         out.writeUTF(songName);
         out.writeLong(playNum);
     }

     @Override
     public void readFields(DataInput in) throws IOException {
         this.languageType=in.readUTF();
         this.songName=in.readUTF();
         this.playNum=in.readLong();
     }

     @Override
     public int compareTo(TopKWritable o) {

         //此处-1是为了在输出的时候是按照从大到小的次序输出
         return -this.getPlayNum().compareTo(o.getPlayNum());
     }

     @Override
     public String toString() {
         return languageType + "\t"
                 + songName + "\t"
                 + playNum;
     }

     @Override
     public int hashCode() {
         final int prime = 31;
         int result = 1;
         result = prime * result
                 + ((languageType == null) ? 0 : languageType.hashCode());
         result = prime * result + (int) (playNum ^ (playNum >>> 32));
         result = prime * result
                 + ((songName == null) ? 0 : songName.hashCode());
         return result;
     }

     @Override
     public boolean equals(Object obj) {
         if (this == obj)
             return true;
         if (obj == null)
             return false;
         if (getClass() != obj.getClass())
             return false;
         TopKWritable other = (TopKWritable) obj;
         if (languageType == null) {
             if (other.languageType != null)
                 return false;
         } else if (!languageType.equals(other.languageType))
             return false;
         if (playNum != other.playNum)
             return false;
         if (songName == null) {
             if (other.songName != null)
                 return false;
         } else if (!songName.equals(other.songName))
             return false;
         return true;
     }
 }

View TopKWritable Code

正式的Mapper和Reducer类;

 package org.dragon.hadoop.mapreduce.app.topk;

 import java.io.IOException;
 import java.util.Iterator;
 import java.util.TreeMap;
 import java.util.TreeSet;

 import javax.security.auth.callback.LanguageCallback;

 import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.conf.Configuration;
 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.Mapper.Context;
 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 import org.dragon.hadoop.mapreduce.app.topk.TopKMapReduceV3.TopKReducer;

 import com.sun.jersey.core.header.LanguageTag;

 import sun.reflect.LangReflectAccess;

 /**
  *
  * @author ZhuXY
  * @time 2016-3-13 下午12:57:26
  *
  */

 /**
  * 统计 & TopKey
  *
  * 数据格式： 语言类别 歌曲名称 收藏次数 播放次数 歌手名称 需求： 统计前十首播放次数最多的歌曲名称和次数。
  *
  * 思想:在Mapper中输出：key---歌曲类型+歌曲名称
  *                     value---播放次数
  * Reducer中：key----封装成TopKWritable对象
  *             value---nullwritable
  * reduce方法中进行集合存储，然后删除多余的
  *
  */
 public class TopKMapReduceV4 {
     private static final int KEY = 4;

     // Mapper class
     public static class TopKMapper extends
             Mapper<LongWritable, Text, Text, LongWritable> {

         @Override
         protected void cleanup(Context context) throws IOException,
                 InterruptedException {
             super.cleanup(context);
         }

         @Override
         protected void map(LongWritable key, Text value, Context context)
                 throws IOException, InterruptedException {
             //文件的输入类型为TextInputFormat，默认到map中的为<Longwritable,Text>
             String lineValue = value.toString();

             if (null == lineValue) {
                 return;
             }

             //split
             String[] splitValue = lineValue.split("\t");

             if (splitValue != null && splitValue.length == 5) {
                 String languageType = splitValue[0];
                 String songName = splitValue[1];
                 Long playNum = Long.parseLong(splitValue[3]);

                 context.write(new Text(languageType + "\t" + songName),
                         new LongWritable(playNum));
             }
         }

         @Override
         protected void setup(Context context) throws IOException,
                 InterruptedException {
             // TODO Auto-generated method stub
             super.setup(context);
         }
     }

     // Reducer class
     public static class TopKReducer extends
             Reducer<Text, LongWritable, TopKWritable, NullWritable> {

         //此集合的排序规则即为TopKWritable中comparaTo的排序规则
         TreeSet<TopKWritable> treeSet=new TreeSet<TopKWritable>();

         @Override
         protected void setup(Context context)
                 throws IOException, InterruptedException {
             // TODO Auto-generated method stub
             super.setup(context);
         }

         @Override
         protected void reduce(Text key, Iterable<LongWritable> values,
                 Context context) throws IOException, InterruptedException {

             Long palyNum=(long) 0;
             if (key==null) {
                 return;
             }

             //get key
             String[] keyArr=key.toString().split("\t");
             String languageType=keyArr[0];
             String songName=keyArr[1];

             //sum
             for(LongWritable value:values){
                 palyNum+=value.get();
             }

             //歌曲类型、歌曲名称、歌曲播放次数封装成TopKWritable对象，保存在treeSet集合中，此集合自动排序
             treeSet.add(new TopKWritable(
                     languageType,songName,palyNum
                     ));

             if (treeSet.size()>KEY) {
                 treeSet.remove(treeSet.last());//remove the current small longNum
             }
         }

         @Override
         protected void cleanup(Context context)
                 throws IOException, InterruptedException {
             for (TopKWritable topKWritable : treeSet) {
                 context.write(topKWritable,NullWritable.get());
             }
         }

     }
     // Driver Code
     public int run(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
         // get conf
         Configuration conf=new Configuration();

         // create job
         Job job =new Job(conf, TopKMapReduceV4.class.getSimpleName());//Job name

         // set job
         job.setJarByClass(TopKMapReduceV4.class);

         //    1)set inputPath
         FileInputFormat.addInputPath(job, new Path(args[0]));

         //    2)set map
         job.setMapperClass(TopKMapper.class);
         job.setMapOutputKeyClass(Text.class);
         job.setMapOutputValueClass(LongWritable.class);

         //    3)set outputPath
         FileOutputFormat.setOutputPath(job, new Path(args[1]));

         //    4)set reduce
         job.setReducerClass(TopKReducer.class);
         job.setOutputKeyClass(TopKWritable.class);
         job.setOutputValueClass(NullWritable.class);

         // submit job
         boolean isSuccess=job.waitForCompletion(true);

         //return status
         return isSuccess?0:1;
     }

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

         args=new String[]{
                 "hdfs://hadoop-master.dragon.org:9000/wc/wcinput/",
                 "hdfs://hadoop-master.dragon.org:9000/wc/wcoutput"
         };
         int status =new TopKMapReduceV4().run(args);
         System.exit(status);
     }
 }

View TopKMapReduceV4 Code