025_MapReduce样例Hadoop TopKey算法

1、需求说明

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。

  1 package org.dragon.hadoop.mapreduce.app.topk;  2   3 import java.io.IOException;  4   5 import org.apache.hadoop.conf.Configuration;  6 import org.apache.hadoop.fs.Path;  7 import org.apache.hadoop.io.LongWritable;  8 import org.apache.hadoop.io.Text;  9 import org.apache.hadoop.mapreduce.Job; 10 import org.apache.hadoop.mapreduce.Mapper; 11 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 12 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 13  14 /** 15  * 功能：某个文件中某列数据的最大值某个文件中 16  *  17  * 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 18  * @author ZhuXY 19  * @time 2016-3-12 下午3:43:23 20  *  21  */ 22 public class TopKMapReduce { 23  24     /* 25      * ****************************************************** 26      * 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 27      * ****************************************************** 28      */ 29  30     // Mapper class 31     static class TopKMapper extends 32             Mapper<LongWritable, Text, Text, LongWritable> { 33         // map output key 34         private Text mapOutputKey = new Text();//java的变量（对象）使用前一定要先创建 35  36         // map output value 37         private LongWritable mapOutputValue = new LongWritable();  38          39         /* 40          * ******************************** 41          * 此处创建对所有的map()函数有效 42          * ******************************* 43          */ 44          45  46         // store max value,init long.MIN_VALUE 47         private long topKValue = Long.MIN_VALUE; 48  49         @Override 50         protected void map(LongWritable key, Text value, Context context) 51                 throws IOException, InterruptedException { 52             // get value 53             String lineValue =value.toString(); 54             String[] str = lineValue.split("\t"); 55  56             Long tempValue = Long.valueOf(str[1]); 57  58             // comparator 59             if (topKValue < tempValue) { 60                 topKValue = tempValue; 61                 // 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 62                 mapOutputKey.set(str[0]); 63             } 64  65             // 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 66         } 67  68         @Override 69         protected void setup(Context context) throws IOException, 70                 InterruptedException { 71             super.setup(context); 72         } 73  74         @Override 75         protected void cleanup(Context context) throws IOException, 76                 InterruptedException { 77             // set map output value 78             mapOutputValue.set(topKValue); 79  80             // set mapoutput context 81             context.write(mapOutputKey, mapOutputValue); 82         } 83     } 84  85     // Driver Code 86     public int run(String[] args) throws Exception, IOException, 87             InterruptedException { 88         // get conf 89         Configuration conf = new Configuration(); 90  91         // create job 92         Job job = new Job(conf, TopKMapReduce.class.getSimpleName()); 93  94         // set job 95         job.setJarByClass(TopKMapReduce.class); 96         // 1) input 97         Path inputDirPath = new Path(args[0]); 98         FileInputFormat.addInputPath(job, inputDirPath); 99 100         // 2) map101         job.setMapperClass(TopKMapper.class);102         job.setMapOutputKeyClass(Text.class);103         job.setMapOutputValueClass(LongWritable.class);104 105         // 3) reduce106         // job.setReducerClass(DataTotalReducer.class);107         // job.setOutputKeyClass(Text.class);108         // job.setOutputValueClass(DataWritable.class);109         job.setNumReduceTasks(0);// 因为本程序没有Reducer的过程，这里必须设置为0110         111         // 4) output112         Path outputDir = new Path(args[1]);113         FileOutputFormat.setOutputPath(job, outputDir);114 115         // submit job116         boolean isSuccess = job.waitForCompletion(true);117 118         // return status119         return isSuccess ? 0 : 1;120     }121 122     // run mapreduce123     public static void main(String[] args) throws Exception, IOException,124             InterruptedException {125         // set args126         args = new String[] { "hdfs://hadoop-master:9000/wc/wcoutput",127                 "hdfs://hadoop-master:9000/wc/output" };128 129         // run job130         int status = new TopKMapReduce().run(args);131         // exit132         System.exit(status);133     }134 135 }

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

  1 package org.dragon.hadoop.mapreduce.app.topk;  2   3 import java.io.IOException;  4 import java.util.Iterator;  5 import java.util.Set;  6 import java.util.TreeMap;  7   8 import org.apache.hadoop.conf.Configuration;  9 import org.apache.hadoop.fs.Path; 10 import org.apache.hadoop.io.LongWritable; 11 import org.apache.hadoop.io.Text; 12 import org.apache.hadoop.mapreduce.Job; 13 import org.apache.hadoop.mapreduce.Mapper; 14 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 15 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 16  17 import com.sun.org.apache.bcel.internal.generic.NEW; 18  19 /** 20  * 功能：某列的TopKey的值，即最大（小）的几个。K小值问题 21  *  22  * @author ZhuXY 23  * @time 2016-3-12 下午3:43:23 24  *  25  */ 26 public class TopKMapReduceV2 { 27  28     /* 29      * 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。 30      *  该集合自动按照键进行排序，然后保留最大的三个 31      *  注意：集合   key   value 32      *      真是  value    key 33      */ 34  35     // Mapper class 36     static class TopKMapper extends 37             Mapper<LongWritable, Text, Text, LongWritable> { 38  39         // 用作保存TopKey的键和值 40         private TreeMap<Long, String> topKTreeMap = new TreeMap<Long, String>(); 41  42         @Override 43         protected void map(LongWritable key, Text value, Context context) 44                 throws IOException, InterruptedException { 45             // get value 46             String lineValue = value.toString(); 47             String[] str = lineValue.split("\t"); 48  49             long tempKey = Long.valueOf(str[1]); 50             String tempValue = String.valueOf(str[0]); 51  52             topKTreeMap.put(tempKey, tempValue); 53             if (topKTreeMap.size() > 3) { 54                 topKTreeMap.remove(topKTreeMap.firstKey()); 55             } 56         } 57  58         @Override 59         protected void setup(Context context) throws IOException, 60                 InterruptedException { 61             super.setup(context); 62         } 63  64         @Override 65         protected void cleanup(Context context) throws IOException, 66                 InterruptedException { 67             Set<Long> mapValueSet = topKTreeMap.keySet();// long 名字起得不好 68  69             Text mapOutputKey = new Text(); 70             LongWritable mapOutputValue = new LongWritable(); 71  72 //            for (Iterator<Long> iterator = mapValueSet.iterator(); iterator 73 //                    .hasNext();) { 74 // 75 //                long iteratorNum=iterator.next(); 76 //                mapOutputValue.set(iteratorNum);// long 77 //                mapOutputKey.set(topKTreeMap.get(iteratorNum)); 78 // 79 //                context.write(mapOutputKey, mapOutputValue); 80 //            } 81              82             for(long key:mapValueSet){ 83                 mapOutputValue.set(key);// long 84                 mapOutputKey.set(topKTreeMap.get(key)); 85                  86                 context.write(mapOutputKey, mapOutputValue); 87             } 88         } 89     } 90  91     // Driver Code 92     public int run(String[] args) throws Exception, IOException, 93             InterruptedException { 94         // get conf 95         Configuration conf = new Configuration(); 96  97         // create job 98         Job job = new Job(conf, TopKMapReduceV2.class.getSimpleName()); 99 100         // set job101         job.setJarByClass(TopKMapReduceV2.class);102         // 1) input103         Path inputDirPath = new Path(args[0]);104         FileInputFormat.addInputPath(job, inputDirPath);105 106         // 2) map107         job.setMapperClass(TopKMapper.class);108         job.setMapOutputKeyClass(Text.class);109         job.setMapOutputValueClass(LongWritable.class);110 111         // 3) reduce112         // job.setReducerClass(DataTotalReducer.class);113         // job.setOutputKeyClass(Text.class);114         // job.setOutputValueClass(DataWritable.class);115         job.setNumReduceTasks(0);// 因为本程序没有Reducer的过程，这里必须设置为0116 117         // 4) output118         Path outputDir = new Path(args[1]);119         FileOutputFormat.setOutputPath(job, outputDir);120 121         // submit job122         boolean isSuccess = job.waitForCompletion(true);123 124         // return status125         return isSuccess ? 0 : 1;126     }127 128     // run mapreduce129     public static void main(String[] args) throws Exception, IOException,130             InterruptedException {131         // set args132         args = new String[] { "hdfs://hadoop-master:9000/wc/wcoutput",133                 "hdfs://hadoop-master:9000/wc/output1" };134 135         // run job136         int status = new TopKMapReduceV2().run(args);137         // exit138         System.exit(status);139     }140 141 }

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。

  1 package org.dragon.hadoop.mapreduce.app.topk;  2   3 import java.io.IOException;  4 import java.util.Iterator;  5 import java.util.Set;  6 import java.util.TreeMap;  7   8 import org.apache.hadoop.conf.Configuration;  9 import org.apache.hadoop.fs.Path; 10 import org.apache.hadoop.io.IntWritable; 11 import org.apache.hadoop.io.LongWritable; 12 import org.apache.hadoop.io.Text; 13 import org.apache.hadoop.mapreduce.Job; 14 import org.apache.hadoop.mapreduce.Mapper; 15 import org.apache.hadoop.mapreduce.Mapper.Context; 16 import org.apache.hadoop.mapreduce.Reducer; 17 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 18 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 19 import org.eclipse.core.internal.filesystem.local.Convert; 20  21 import com.sun.org.apache.bcel.internal.generic.NEW; 22  23 /** 24  * 功能：多个文件中某列数据和的最大值 25  *  26  * 思想：类似wordcount，把每行数据统计好，context出去---mapper 27  *         接收到经过shuffle和merge形成<key,list<1,2,3,4…>>----透明 28  *         在cleanup中，收集reduce中的TreeMap集合，进行排序删除-------reduce、cleanup 29  *   30  * @author ZhuXY 31  * @time 2016-3-12 下午3:43:23 32  *  33  */ 34 public class TopKMapReduceV3 { 35  36     /* 37      * 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。 38      *  该集合自动按照键进行排序，然后保留最大的三个 39      *  注意：集合   key   value 40      *      真是  value    key 41      */ 42  43     // Mapper class 44     static class TopKMapper extends 45             Mapper<LongWritable, Text, Text, LongWritable> { 46  47         Text mapOutputKey=new Text(); //key 48         LongWritable mapOutputValue=new LongWritable();//value 49          50         @Override 51         protected void map(LongWritable key, Text value, Context context) 52                 throws IOException, InterruptedException { 53             // get value 54             String lineValue = value.toString(); 55             String[] str = lineValue.split("\t"); 56              57             mapOutputKey.set(str[0]); 58              59             mapOutputValue.set(Long.parseLong(str[1])); 60              61             context.write(mapOutputKey, mapOutputValue); 62  63         } 64     } 65  66     static class TopKReducer extends  67             Reducer<Text, LongWritable, Text, LongWritable>{ 68          69          70          71         // 用作保存TopKey的键和值 72         private TreeMap<Long, String> topKTreeMap = new TreeMap<Long, String>(); 73  74         @Override 75         protected void reduce(Text key, Iterable<LongWritable> values,Context context) 76                 throws IOException, InterruptedException { 77             int sum=0; 78             //循环遍历Interable 79             for(LongWritable value:values) 80             { 81                 //累加 82                 sum+=value.get(); 83             } 84              85             long tempKey = Long.valueOf(sum); 86             String tempValue = String.valueOf(key); 87  88             topKTreeMap.put(tempKey, tempValue); 89             if (topKTreeMap.size() > 3) { 90                 topKTreeMap.remove(topKTreeMap.firstKey()); 91             } 92         } 93  94         @Override 95         protected void cleanup(Context context) 96                 throws IOException, InterruptedException { 97              98             //TreeMap键的集合 99             Set<Long> mapValueSet = topKTreeMap.keySet();// long 名字起得不好100 101             Text mapOutputKey = new Text();102             LongWritable mapOutputValue = new LongWritable();103             104             //根据键，获取值，并交叉赋予context中参数105             for(long key:mapValueSet){106                 mapOutputValue.set(key);// long107                 mapOutputKey.set(topKTreeMap.get(key));108                 109                 context.write(mapOutputKey, mapOutputValue);110             }111         }112 113     }114     115     // Driver Code116     public int run(String[] args) throws Exception, IOException,117             InterruptedException {118         // get conf119         Configuration conf = new Configuration();120 121         // create job122         Job job = new Job(conf, TopKMapReduceV3.class.getSimpleName());123 124         // set job125         job.setJarByClass(TopKMapReduceV3.class);126         // 1) input127         Path inputDirPath = new Path(args[0]); 128         FileInputFormat.addInputPath(job, inputDirPath);129 130         // 2) map131         job.setMapperClass(TopKMapper.class);132         job.setMapOutputKeyClass(Text.class);133         job.setMapOutputValueClass(LongWritable.class);134 135         // 3) reduce136         job.setReducerClass(TopKReducer.class);137         job.setOutputKeyClass(Text.class);138         job.setOutputValueClass(LongWritable.class);139         //job.setNumReduceTasks(0);// default 1140 141         // 4) output142         Path outputDir = new Path(args[1]);143         FileOutputFormat.setOutputPath(job, outputDir);144 145         // submit job146         boolean isSuccess = job.waitForCompletion(true);147 148         // return status149         return isSuccess ? 0 : 1;150     }151 152     // run mapreduce153     public static void main(String[] args) throws Exception, IOException,154             InterruptedException {155         // set args156         args = new String[] { "hdfs://hadoop-master:9000/wc/wcinput",157                 "hdfs://hadoop-master:9000/wc/output2" };158 159         // run job160         int status = new TopKMapReduceV3().run(args);161         // exit162         System.exit(status);163     }164 165 }

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：

  1 package org.dragon.hadoop.mapreduce.app.topk;  2   3 import java.io.DataInput;  4 import java.io.DataOutput;  5 import java.io.IOException;  6   7 import org.apache.hadoop.io.WritableComparable;  8   9 /** 10  * 11  * @author ZhuXY   12  * @time   2016-3-13 下午7:30:21 13  * 14  */ 15  16 /** 17  *  18  * 数据格式：  19  *         语言类别     歌曲名称     收藏次数     播放次数     歌手名称 20  * 需求：  21  *      统计前十首播放次数最多的歌曲名称和次数。 22  */ 23 public class TopKWritable implements WritableComparable<TopKWritable>{ 24     private String languageType=null; 25     private String songName=null; 26     private long playNum=0; 27      28     public TopKWritable(){ 29          30     } 31     public TopKWritable(String languageType,String songName,long playNum){ 32         set(languageType, songName, playNum); 33     } 34     public void set(String languageType,String songName,Long playNum){ 35         this.languageType=languageType; 36         this.songName=songName; 37         this.playNum=playNum; 38     } 39      40     public String getLanguageType() { 41         return languageType; 42     } 43     public String getSongName() { 44         return songName; 45     } 46     public Long getPlayNum() { 47         return playNum; 48     } 49      50     @Override 51     public void write(DataOutput out) throws IOException { 52         out.writeUTF(languageType); 53         out.writeUTF(songName); 54         out.writeLong(playNum); 55     } 56      57     @Override 58     public void readFields(DataInput in) throws IOException { 59         this.languageType=in.readUTF(); 60         this.songName=in.readUTF(); 61         this.playNum=in.readLong(); 62     } 63      64     @Override 65     public int compareTo(TopKWritable o) { 66          67         //此处-1是为了在输出的时候是按照从大到小的次序输出 68         return -this.getPlayNum().compareTo(o.getPlayNum()); 69     } 70      71     @Override 72     public String toString() { 73         return languageType + "\t" 74                 + songName + "\t" 75                 + playNum; 76     } 77      78     @Override 79     public int hashCode() { 80         final int prime = 31; 81         int result = 1; 82         result = prime * result 83                 + ((languageType == null) ? 0 : languageType.hashCode()); 84         result = prime * result + (int) (playNum ^ (playNum >>> 32)); 85         result = prime * result 86                 + ((songName == null) ? 0 : songName.hashCode()); 87         return result; 88     } 89      90     @Override 91     public boolean equals(Object obj) { 92         if (this == obj) 93             return true; 94         if (obj == null) 95             return false; 96         if (getClass() != obj.getClass()) 97             return false; 98         TopKWritable other = (TopKWritable) obj; 99         if (languageType == null) {100             if (other.languageType != null)101                 return false;102         } else if (!languageType.equals(other.languageType))103             return false;104         if (playNum != other.playNum)105             return false;106         if (songName == null) {107             if (other.songName != null)108                 return false;109         } else if (!songName.equals(other.songName))110             return false;111         return true;112     }113 }

View TopKWritable Code

正式的Mapper和Reducer类;

  1 package org.dragon.hadoop.mapreduce.app.topk;  2   3 import java.io.IOException;  4 import java.util.Iterator;  5 import java.util.TreeMap;  6 import java.util.TreeSet;  7   8 import javax.security.auth.callback.LanguageCallback;  9  10 import org.apache.hadoop.classification.InterfaceAudience.Private; 11 import org.apache.hadoop.conf.Configuration; 12 import org.apache.hadoop.fs.Path; 13 import org.apache.hadoop.io.LongWritable; 14 import org.apache.hadoop.io.NullWritable; 15 import org.apache.hadoop.io.Text; 16 import org.apache.hadoop.mapreduce.Job; 17 import org.apache.hadoop.mapreduce.Mapper; 18 import org.apache.hadoop.mapreduce.Reducer; 19 import org.apache.hadoop.mapreduce.Mapper.Context; 20 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 21 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 22 import org.dragon.hadoop.mapreduce.app.topk.TopKMapReduceV3.TopKReducer; 23  24 import com.sun.jersey.core.header.LanguageTag; 25  26 import sun.reflect.LangReflectAccess; 27  28 /** 29  *  30  * @author ZhuXY 31  * @time 2016-3-13 下午12:57:26 32  *  33  */ 34  35 /** 36  * 统计 & TopKey 37  *  38  * 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。 39  *  40  * 思想:在Mapper中输出：key---歌曲类型+歌曲名称 41  *                     value---播放次数 42  * Reducer中：key----封装成TopKWritable对象 43  *             value---nullwritable 44  * reduce方法中进行集合存储，然后删除多余的 45  *  46  */ 47 public class TopKMapReduceV4 { 48     private static final int KEY = 4; 49  50     // Mapper class 51     public static class TopKMapper extends 52             Mapper<LongWritable, Text, Text, LongWritable> { 53  54         @Override 55         protected void cleanup(Context context) throws IOException, 56                 InterruptedException { 57             super.cleanup(context); 58         } 59  60         @Override 61         protected void map(LongWritable key, Text value, Context context) 62                 throws IOException, InterruptedException { 63             //文件的输入类型为TextInputFormat，默认到map中的为<Longwritable,Text> 64             String lineValue = value.toString(); 65  66             if (null == lineValue) { 67                 return; 68             } 69              70             //split 71             String[] splitValue = lineValue.split("\t"); 72  73             if (splitValue != null && splitValue.length == 5) { 74                 String languageType = splitValue[0]; 75                 String songName = splitValue[1]; 76                 Long playNum = Long.parseLong(splitValue[3]); 77  78                 context.write(new Text(languageType + "\t" + songName), 79                         new LongWritable(playNum)); 80             } 81         } 82  83         @Override 84         protected void setup(Context context) throws IOException, 85                 InterruptedException { 86             // TODO Auto-generated method stub 87             super.setup(context); 88         } 89     } 90  91     // Reducer class 92     public static class TopKReducer extends 93             Reducer<Text, LongWritable, TopKWritable, NullWritable> { 94          95         //此集合的排序规则即为TopKWritable中comparaTo的排序规则 96         TreeSet<TopKWritable> treeSet=new TreeSet<TopKWritable>(); 97                  98         @Override 99         protected void setup(Context context)100                 throws IOException, InterruptedException {101             // TODO Auto-generated method stub102             super.setup(context);103         }104         105         @Override106         protected void reduce(Text key, Iterable<LongWritable> values,107                 Context context) throws IOException, InterruptedException {108             109             Long palyNum=(long) 0;110             if (key==null) {111                 return;112             }113             114             //get key115             String[] keyArr=key.toString().split("\t");116             String languageType=keyArr[0];117             String songName=keyArr[1];118             119             //sum120             for(LongWritable value:values){121                 palyNum+=value.get();122             }123             124             //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125             treeSet.add(new TopKWritable(126                     languageType,songName,palyNum127                     ));128             129             if (treeSet.size()>KEY) {130                 treeSet.remove(treeSet.last());//remove the current small longNum131             }132         }133 134         @Override135         protected void cleanup(Context context)136                 throws IOException, InterruptedException {137             for (TopKWritable topKWritable : treeSet) {138                 context.write(topKWritable,NullWritable.get());139             }140         }141 142         143     }144     // Driver Code145     public int run(String[] args) throws IOException, ClassNotFoundException, InterruptedException {146         // get conf147         Configuration conf=new Configuration();148         149         // create job150         Job job =new Job(conf, TopKMapReduceV4.class.getSimpleName());//Job name151         152         // set job153         job.setJarByClass(TopKMapReduceV4.class);154         155         //    1)set inputPath156         FileInputFormat.addInputPath(job, new Path(args[0]));157         158         //    2)set map159         job.setMapperClass(TopKMapper.class);160         job.setMapOutputKeyClass(Text.class);161         job.setMapOutputValueClass(LongWritable.class);162         163         //    3)set outputPath164         FileOutputFormat.setOutputPath(job, new Path(args[1]));165         166         //    4)set reduce 167         job.setReducerClass(TopKReducer.class);168         job.setOutputKeyClass(TopKWritable.class);169         job.setOutputValueClass(NullWritable.class);170         171         // submit job172         boolean isSuccess=job.waitForCompletion(true);173         174         //return status175         return isSuccess?0:1;176     }177     178     public static void main(String[] args) throws IOException, InterruptedException, Exception {179         180         args=new String[]{181                 "hdfs://hadoop-master.dragon.org:9000/wc/wcinput/",182                 "hdfs://hadoop-master.dragon.org:9000/wc/wcoutput"183         };184         int status =new TopKMapReduceV4().run(args);185         System.exit(status);186     }187 }

View TopKMapReduceV4 Code