MapReduce的Reduce side Join

1. 简单介绍

reduce side  join是全部join中用时最长的一种join，可是这样的方法可以适用内连接、left外连接、right外连接、full外连接和反连接等全部的join方式。reduce side
 join不仅能够对小数据进行join，也能够对大数据进行join，可是大数据会占用大量的集群内部网络IO，由于全部数据终于要写入到reduce端进行join。

假设要做join的数据量很大的话。就不得不用reduce join了。

2. 适用场景

-join的两部分数据量很大；

-想要通过一种模式灵活的适用多种join。

3.Reduce side  join的架构

3.1 map 阶段

map 阶段首先从数据中提取出join的foreign key作为map输出的key，然后将输入的记录所有作为输出value。输出的value须要依据输入的数据集打上数据集的标签，比方在value的开头加上‘A’‘B’的标签。

3.2 reduce阶段

reduce端对具有相同foreign key的数据进行处理，对具有标签'A'和'B'的数据进行迭代处理，下面分别用伪代码对不同的join的处理进行说明。

-内连接：假设带有标签‘A’和‘B’的数据都存在，遍历并连接这些数据，然后输出

if (!listA.isEmpty() && !listB.isEmpty()) {
     for (Text A : listA) {
          for (Text B : listB) {
          context.write(A, B);
          }
     }
}

-左外连接：右边的数据假设存在就与左边连接，否则将右边的字段都赋null。仅仅输出左边

// For each entry in A,
for (Text A : listA) {
// If list B is not empty, join A and B
     if (!listB.isEmpty()) {
          for (Text B : listB) {
               context.write(A, B);
          }
     } else {
// Else, output A by itself
          context.write(A, EMPTY_TEXT);
     }
}

-右外连接：与左外连接类似。左边为空就将左边赋值null，仅仅输出右边

// For each entry in B,
for (Text B : listB) {
// If list A is not empty, join A and B
     if (!listA.isEmpty()) {
          for (Text A : listA) {
               context.write(A, B);
          }
     } else {
// Else, output B by itself
          context.write(EMPTY_TEXT, B);
     }
}

-全外连接：这个要相对复杂点，首先输出A和B都不为空的。然后输出某一边为空的

// If list A is not empty
if (!listA.isEmpty()) {
// For each entry in A
     for (Text A : listA) {
// If list B is not empty, join A with B
          if (!listB.isEmpty()) {
               for (Text B : listB) {
                    context.write(A, B);
               }
          } else {
          // Else, output A by itself
               context.write(A, EMPTY_TEXT);
          }
     }
} else {
// If list A is empty, just output B
     for (Text B : listB) {
          context.write(EMPTY_TEXT, B);
     }
}

-反连接：输出A和B没有共同foreign key的值

// If list A is empty and B is empty or vice versa
if (listA.isEmpty() ^ listB.isEmpty()) {
// Iterate both A and B with null values
// The previous XOR check will make sure exactly one of
// these lists is empty and therefore the list will be skipped
     for (Text A : listA) {
          context.write(A, EMPTY_TEXT);
     }
     for (Text B : listB) {
          context.write(EMPTY_TEXT, B);
     }
}

4.实例

以下举一个简单的样例，要求可以用reduce side join方式实现以上全部的join。

4.1数据

User 表

---------------------------
username     cityid
--------------------------
 Li lei,       1
Xiao hong,     2
Lily,          3
Lucy,          3
Daive,         4
Jake,          5
Xiao Ming,     6

City表

---------------------------
cityid     cityname
--------------------------
1,     Shanghai
2,     Beijing
3,     Jinan
4,     Guangzhou
7,     Wuhan
8,     Shenzhen

4.2 代码介绍

写两个mapper，一个mapper处理user数据，一个mapper处理city数据。在主函数中调用时用MultipleInputs类加入数据路径，并分别指派两个处理的Mapper。

往configuration中加入參数“join.type”,传给reducer，决定在reduce端採用什么样的join。

具体代码例如以下：

package com.study.hadoop.mapreduce;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

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.util.GenericOptionsParser;
import org.apache.hadoop.mapreduce.lib.input.MultipleInputs;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class ReduceJoin {

	//user map
	public static class UserJoinMapper extends Mapper<Object, Text, Text, Text>{
		private Text outKey = new Text();
		private Text outValue = new Text();
		@Override
		protected void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			// TODO Auto-generated method stub
			String line = value.toString();
			String[] items = line.split(",");

			outKey.set(items[1]);
			outValue.set("A"+items[0]);
			context.write(outKey, outValue);
		}
	}
	//city map
	public static class CityJoinMapper extends Mapper<Object, Text, Text, Text>{
		// TODO Auto-generated constructor stub
		private Text outKey = new Text();
		private Text outValue = new Text();
		@Override
		protected void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			// TODO Auto-generated method stub
			String line = value.toString();
			String[] items = line.split(",");

			outKey.set(items[0]);
			outValue.set("B"+items[1]);
			context.write(outKey, outValue);
		}

	}
	public static class JoinReducer extends Reducer<Text, Text, Text, Text>{
		// TODO Auto-generated constructor stub
		//Join type:{inner,leftOuter,rightOuter,fullOuter,anti}
		private String joinType = null;
		private static final Text EMPTY_VALUE = new Text("");
		private List<Text> listA = new ArrayList<Text>();
		private List<Text> listB = new ArrayList<Text>();
		@Override
		protected void setup(Context context)
				throws IOException, InterruptedException {
			// TODO Auto-generated method stub
			//获取join的类型
			joinType = context.getConfiguration().get("join.type");
		}

		@Override
		protected void reduce(Text key, Iterable<Text> values,Context context)
				throws IOException, InterruptedException {
			// TODO Auto-generated method stub
			listA.clear();
			listB.clear();

			Iterator<Text> iterator = values.iterator();
			while(iterator.hasNext()){
				String value = iterator.next().toString();
				if(value.charAt(0)=='A')
					listA.add(new Text(value.substring(1)));
				if(value.charAt(0)=='B')
					listB.add(new Text(value.substring(1)));
			}
			joinAndWrite(context);
		}

		private void joinAndWrite(Context context)
				throws IOException, InterruptedException{
			//inner join
			if(joinType.equalsIgnoreCase("inner")){
				if(!listA.isEmpty() && !listB.isEmpty()) {
					for (Text A : listA)
						for(Text B : listB){
							context.write(A, B);
						}
				}
			}
			//left outer join
			if(joinType.equalsIgnoreCase("leftouter")){
				if(!listA.isEmpty()){
					for (Text A : listA){
						if(!listB.isEmpty()){
							for(Text B: listB){
								context.write(A, B);
							}
						}
						else{
							context.write(A, EMPTY_VALUE);
						}
					}
				}
			}
			//right outer join
			else if(joinType.equalsIgnoreCase("rightouter")){
				if(!listB.isEmpty()){
					for(Text B: listB){
						if(!listA.isEmpty()){
							for(Text A: listA)
								context.write(A, B);
						}else {
							context.write(EMPTY_VALUE, B);
						}
					}
				}
			}
			//full outer join
			else if(joinType.equalsIgnoreCase("fullouter")){
				if(!listA.isEmpty()){
					for (Text A : listA){
						if(!listB.isEmpty()){
							for(Text B : listB){
								context.write(A, B);
							}
						}else {
							context.write(A, EMPTY_VALUE);
						}
					}
				}else{
					for(Text B : listB)
						context.write(EMPTY_VALUE, B);
				}
			}
			//anti join
			else if(joinType.equalsIgnoreCase("anti")){
				if(listA.isEmpty() ^ listB.isEmpty()){
					for(Text A : listA)
						context.write(A, EMPTY_VALUE);
					for(Text B : listB)
						context.write(EMPTY_VALUE, B);
				}
			}
		}
	}

	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		// TODO Auto-generated method stub
		Configuration conf = new Configuration();
		String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();

	    if (otherArgs.length < 4)
	    {
	      System.err.println("params:<UserInDir> <CityInDir> <OutDir> <join Type>");
	      System.exit(1);
	    }
	    Job job = new Job(conf,"Reduce side join Job");
	    job.setJarByClass(ReduceJoin.class);
	    job.setReducerClass(JoinReducer.class);
	    job.setOutputKeyClass(Text.class);
	    job.setOutputValueClass(Text.class);
	    MultipleInputs.addInputPath(job, new Path(otherArgs[0]), TextInputFormat.class, UserJoinMapper.class);
	    MultipleInputs.addInputPath(job, new Path(otherArgs[1]), TextInputFormat.class, CityJoinMapper.class);
	    FileOutputFormat.setOutputPath(job, new Path(otherArgs[2]));
	    job.getConfiguration().set("join.type", otherArgs[3]);

	    System.exit(job.waitForCompletion(true) ? 0 : 1);
	}

}

4.3 结果

运行语句：

inner join：

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left outer join：

right outer join：

full outer join：

anti join：

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