MapReduce案例实践
实验目的与要求
目的：
1.利用Mapreduce熟练编写大规模MR程序
2.理解单表链接的实际场景
要求：
（1）请写出解题的思路（可采用思维导图、流程图或伪代码说明等，任何能说明的方式）；
（2）请提供二以上的输入测试数据和输出结果截图；
代码：
package Mapreduce;
import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;
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.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
public class SingleTableLink {
private static int time = 0;
public static void main(String[] args) throws Exception {
//必须要传递的是自定的mapper和reducer的类，输入输出的路径必须指定，输出的类型<k3,v3>必须指定
//2将自定义的MyMapper和MyReducer组装在一起
Configuration conf=new Configuration();
String jobName=SingleTableLink.class.getSimpleName();
//1首先寫job，知道需要conf和jobname在去創建即可
Job job = Job.getInstance(conf, jobName);
//*13最后，如果要打包运行改程序，则需要调用如下行
job.setJarByClass(SingleTableLink.class);
//3读取HDFS內容：FileInputFormat在mapreduce.lib包下
FileInputFormat.setInputPaths(job, new Path(args[0]));
//4指定解析<k1,v1>的类（谁来解析键值对）
//*指定解析的类可以省略不写，因为设置解析类默认的就是TextInputFormat.class
job.setInputFormatClass(TextInputFormat.class);
//5指定自定义mapper类
job.setMapperClass(MyMapper.class);
//6指定map输出的key2的类型和value2的类型 <k2,v2>
//*下面两步可以省略，当<k3,v3>和<k2,v2>类型一致的时候,<k2,v2>类型可以不指定
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
//7分区(默认1个)，排序，分组，规约 采用 默认
//接下来采用reduce步骤
//8指定自定义的reduce类
job.setReducerClass(MyReducer.class);
//9指定输出的<k3,v3>类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//10指定输出<K3,V3>的类
//*下面这一步可以省
job.setOutputFormatClass(TextOutputFormat.class);
//11指定输出路径
FileOutputFormat.setOutputPath(job, new Path(args[1]));
//12写的mapreduce程序要交给resource manager运行
job.waitForCompletion(true);
}
private static class MyMapper extends Mapper<Object, Text, Text, Text> {
@Override
protected void map(Object k1, Text v1,
Mapper<Object, Text, Text, Text>.Context context)
throws IOException, InterruptedException {
String childName = new String();
String parentName = new String();
String relationType = new String();
Text k2 = new Text();
Text v2 = new Text();
// 輸入一行预处理的文本
StringTokenizer items = new StringTokenizer(v1.toString());
String[] values = new String[2];
int i = 0;
while (items.hasMoreTokens()) {
values[i] = items.nextToken();
i++;
}
if (values[0].compareTo("child") != 0) {
childName = values[0];
parentName = values[1];
// 输出左表,左表加1的标识
relationType = "1";
k2 = new Text(values[1]); // parent作为key，作为表1的key
v2 = new Text(relationType + "+" + childName + "+" + parentName);//<1+Lucy+Tom>
context.write(k2, v2);
// 输出右表,右表加2的标识
relationType = "2";
k2 = new Text(values[0]);// child作为key，作为表2的key
v2 = new Text(relationType + "+" + childName + "+" + parentName);//<2+Jone+Lucy>
context.write(k2, v2);
}
}
}
private static class MyReducer extends Reducer<Text, Text, Text, Text> {
Text k3 = new Text();
Text v3 = new Text();
@Override
protected void reduce(Text k2, Iterable<Text> v2s,
Reducer<Text, Text, Text, Text>.Context context)
throws IOException, InterruptedException {
if (0 == time) {
context.write(new Text("grandchild"), new Text("grandparent"));
time++;
}
int grandchildnum = 0;
String[] grandchild = new String[10];//孙子
int grandparentnum = 0;
String[] grandparent = new String[10];//爷爷
Iterator items = v2s.iterator();//["1 Tom","2 Mary","2 Ben"]
while (items.hasNext()) {
String record = items.next().toString();
int len = record.length();
int i = 2;
if (0 == len) {
continue;
}
// 取得左右表的标识
char relationType = record.charAt(0);
// 定义孩子和父母变量
String childname = new String();
String parentname = new String();
// 获取value列表中value的child
while (record.charAt(i) != '+') {
childname += record.charAt(i);
i++;
}
i = i + 1; //越过名字之间的“+”加号
// 获取value列表中value的parent
while (i < len) {
parentname += record.charAt(i);
i++;
}
// 左表，取出child放入grandchildren
if ('1' == relationType) {
grandchild[grandchildnum] = childname;
grandchildnum++;
}
// 右表，取出parent放入grandparent
if ('2' == relationType) {
grandparent[grandparentnum] = parentname;
grandparentnum++;
}
}
// grandchild和grandparentnum数组求笛卡尔积
if (0 != grandchildnum && 0 != grandparentnum) {
for (int i = 0; i < grandchildnum; i++) {
for (int j = 0; j < grandparentnum; j++) {
k3 = new Text(grandchild[i]);
v3 = new Text(grandparent[j]);
context.write(k3, v3);
}
}
}
}
}
}
