题目描述：
现在有两个文件，1为存放公司名字和城市ID，2为存放城市ID和城市名
表一：
factoryname,addressed
Beijing Red Star,1
Shenzhen Thunder,3
Guangzhou Honda,2
Beijing Rising,1
Guangzhou Development Bank,2
Tencent,3
Back of Beijing,1
表2：
1,Beijing
2,Guangzhou
3,Shenzhen
4,Xian
现在要求输出公司名和城市名。例如：
Beijing Red Star Beijing
这个类似数据库里的多表连接。整体思路和单表连接差不多。还是利用reduce阶段对城市ID进行归并，我们在map阶段统一输出key=城市ID value=falg+“+”+城市名or公司名。然后通过reduce对flag的解析，分析后者是城市名还是公司名，并放到两个数组中，最后利用笛卡尔积将其输出
具体代码
public class MyMapper extends Mapper<LongWritable, Text, Text, Text> {
public void map(LongWritable ikey, Text ivalue, Context context )
throws IOException, InterruptedException {
String line=ivalue.toString();
StringTokenizer st= new StringTokenizer(line,"," );
String value0=st.nextToken();
String value1=st.nextToken();
if(value0.compareTo("factoryname" )!=0){
if(value0.length()==1){
context.write(new Text(value0), new Text("1" +"+"+value1));
} else{
context.write(new Text(value1), new Text("2" +"+"+value0));
}
}
}
}
public class MyReducer extends Reducer<Text, Text, Text, Text> {
public void reduce(Text _key, Iterable<Text> values, Context context)
throws IOException, InterruptedException {
// process values
ArrayList<String> address= new ArrayList<String>();
ArrayList<String> factory= new ArrayList<String>();
for (Text val : values) {
String line=val.toString();
StringTokenizer st=new StringTokenizer(line,"+" );
int flag=Integer.parseInt(st.nextToken());
if(flag==1){
String addressname=st.nextToken();
address.add(addressname);
} else if (flag==2){
String factoryname=st.nextToken();
factory.add(factoryname);
}
}
if(address.size()!=0&&factory.size()!=0){
for(int i=0;i<address.size();i++){
for(int j=0;j<factory.size();j++){
context.write( new Text(address.get(i)),new Text(factory.get(j)));
}
}
}
}
}