HBase-API操作之与MR交互（三）

# 前言

目标：将 HBase 的 fruit 表中的数据，通过 MR 筛选处理，导入到 HBase 中的 fruit2 表中

1. 构建 Mapper 类，用于读取 fruit 表中的数据

   	package com.yaindream.mr2;
   	import org.apache.hadoop.hbase.Cell;
   	import org.apache.hadoop.hbase.CellUtil;
   	import org.apache.hadoop.hbase.client.Put;
   	import org.apache.hadoop.hbase.client.Result;
   	import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
   	import org.apache.hadoop.hbase.mapreduce.TableMapper;
   	import org.apache.hadoop.hbase.util.Bytes;
   	import java.io.IOException;
   	/**
   	* Created with IntelliJ IDEA.
   	* User: WangYu
   	* Date: 2020/6/15
   	* Time: 23:27
   	* Description:
   	*/
   	public class Fruit2Mapper extends TableMapper<ImmutableBytesWritable, Put> {
   	@Override
   	protected void map(ImmutableBytesWritable key, Result value, Context context) throws IOException, InterruptedException {
   	// 构建 put 对象
   	Put put = new Put(key.get());
   	// 1. 获取数据
   	for (Cell cell : value.rawCells()) {
   	// 2. 判断当前的 cell 是否为 “name” 列
   	if ("name".equals(Bytes.toString(CellUtil.cloneQualifier(cell)))) {
   	// 3. 给 put 对象赋值
   	put.add(cell);
   	}
   	}
   	// 4. 写出
   	context.write(key, put);
   	}
   	}

2. 构建 Reducer 类，用于将处理过的数据写入到 fruit2 表中

   	package com.yaindream.mr2;
   	import org.apache.hadoop.hbase.client.Put;
   	import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
   	import org.apache.hadoop.hbase.mapreduce.TableReducer;
   	import org.apache.hadoop.io.NullWritable;
   	import java.io.IOException;
   	/**
   	* Created with IntelliJ IDEA.
   	* User: WangYu
   	* Date: 2020/6/15
   	* Time: 23:27
   	* Description:
   	*/
   	public class Fruit2Reducer extends TableReducer<ImmutableBytesWritable, Put, NullWritable> {
   	@Override
   	protected void reduce(ImmutableBytesWritable key, Iterable<Put> values, Context context) throws IOException, InterruptedException {
   	// 遍历写出
   	for (Put value : values) {
   	context.write(NullWritable.get(), value);
   	}
   	}
   	}

3. 构建 Driver 类组装 Job

   	package com.yaindream.mr2;
   	import org.apache.hadoop.conf.Configuration;
   	import org.apache.hadoop.hbase.client.Put;
   	import org.apache.hadoop.hbase.client.Scan;
   	import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
   	import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
   	import org.apache.hadoop.mapreduce.Job;
   	import org.apache.hadoop.util.Tool;
   	import org.apache.hadoop.util.ToolRunner;
   	/**
   	* Created with IntelliJ IDEA.
   	* User: WangYu
   	* Date: 2020/6/15
   	* Time: 23:27
   	* Description:
   	*/
   	public class Fruit2Driver implements Tool {
   	// 定义配置信息
   	private Configuration configuration = null;
   	public int run(String[] args) throws Exception {
   	// 1. 获取 Job 对象
   	Job job = Job.getInstance(configuration);
   	// 2. 设置主类路径
   	job.setJarByClass(Fruit2Driver.class);
   	// 3. 设置 Mapper & 输出 KV 类型
   	TableMapReduceUtil.initTableMapperJob(args[0],
   	new Scan(),
   	Fruit2Mapper.class,
   	ImmutableBytesWritable.class,
   	Put.class,
   	job);
   	// 4. 设置 Reducer & 输出的表
   	TableMapReduceUtil.initTableReducerJob(args[1],
   	Fruit2Reducer.class,
   	job);
   	// 5. 提交任务
   	boolean result = job.waitForCompletion(true);
   	return result ? 0 : 1;
   	}
   	public void setConf(Configuration conf) {
   	configuration = conf;
   	}
   	public Configuration getConf() {
   	return configuration;
   	}
   	public static void main(String[] args) {
   	try {
   	Configuration configuration = new Configuration();
   	ToolRunner.run(configuration, new Fruit2Driver(), args);
   	} catch (Exception e) {
   	e.printStackTrace();
   	}
   	}
   	}

4. 将程序打包成 Jar 包并上传至集群。方法见 HBase-API 操作之与 MR 交互（二）

5. 运行命令

   [root@hadoop02 hbase-1.3.1]# yarn jar hbase-demo-1.0-SNAPSHOT.jar com.yaindream.mr2.Fruit2Driver fruit fruit2
   

6. 运行结果

   可以看到 name 列已经被我们筛选出来了