1．构建 FruitMapper 类，用于读取 fruit 表中的数据

package com.atlxl.mr1;

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 org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class FruitMapper 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());

        //遍历数据
        Cell[] cells = value.rawCells();
        for (Cell cell : cells) {
            if ("name".equals(Bytes.toString(CellUtil.cloneQualifier(cell)))){
                put.add(cell);
            }
        }

        //写出去
        context.write(key, put);

    }
}

2．构建 FruitReducer 类，用于将读取到的 fruit 表中的数据写入到 fruit_mr表中

package com.atlxl.mr1;

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 org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class FruitReducer 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 FruitDriver extends Configured implements Tool 用于组装运行 Job任务

package com.atlxl.mr1;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
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;

public class FruitDriver extends Configuration implements Tool{

    private Configuration configuration = null;

    public int run(String[] strings) throws Exception {

        //获取任务对象
        Job job = Job.getInstance(configuration);

        //指定Driver类
        job.setJarByClass(FruitDriver.class);

        //指定Mapper
        TableMapReduceUtil.initTableMapperJob("fruit",new Scan(),FruitMapper.class, ImmutableBytesWritable.class,Put.class,job);

        //指定Reducer
        TableMapReduceUtil.initTableReducerJob("fruit_mr", FruitReducer.class, job);

        //提交
        boolean b = job.waitForCompletion(true);

        return b?0:1;
    }

    public void setConf(Configuration conf) {
        this.configuration = conf;
    }

    public Configuration getConf() {
        return configuration;
    }

//4．主函数中调用运行该 Job 任务


    public static void main(String[] args) throws Exception {

        Configuration configuration = HBaseConfiguration.create();

        int i = ToolRunner.run(configuration, new FruitDriver(), args);

    }
}

5．打包运行任务

提示：运行任务前，如果待数据导入的表不存在，则需要提前创建。

提示：maven 打包命令：-P local clean package 或-P dev clean package install（将第三方 jar 包

一同打包，需要插件：maven-shade-plugin）

1)将打好的jar包丢到hbase目录下

2)创建接受数据的表

hbase(main):005:0>  create 'fruit_mr','info'

3)运行jar包

[lxl@hadoop102 hbase]$ /opt/module/hadoop-2.7.2/bin/yarn jar Hbase01-1.0-SNAPSHOT.jar com.atlxl.mr1.FruitDriver

4)查看导入的数据

hbase(main):006:0> scan "fruit_mr"
ROW                        COLUMN+CELL                                                                
 1001                      column=info:name, timestamp=1560441335521, value=Apple                     
 1002                      column=info:name, timestamp=1560441335521, value=Pear                      
 1003                      column=info:name, timestamp=1560441335521, value=Pineapple                 
3 row(s) in 0.1330 seconds

自定义 HBase-MapReduce2

目标：实现将 HDFS 中的数据写入到 HBase 表中。

分步实现：

1．构建 HDFSMapper 于读取 HDFS 中的文件数据

package com.atlxl.mr2;

import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class HDFSMapper extends Mapper<LongWritable, Text, NullWritable, Put> {

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //获取一行数据
        String line = value.toString();


        //切割
        String[] split = line.split("	");


        //封装Put对象
        Put put = new Put(Bytes.toBytes(split[0]));
        put.addColumn(Bytes.toBytes("info"), Bytes.toBytes("name"), Bytes.toBytes(split[1]));
        put.addColumn(Bytes.toBytes("info"), Bytes.toBytes("color"), Bytes.toBytes(split[2]));


        //写出
        context.write(NullWritable.get(), put);


    }
}

2．构建 HDFSReducer 类

package com.atlxl.mr2;

import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class HDFSReducer extends TableReducer<NullWritable, Put,NullWritable>{

    @Override
    protected void reduce(NullWritable key, Iterable<Put> values, Context context) throws IOException, InterruptedException {

        //遍历写出
        for (Put value : values) {
            context.write(NullWritable.get(), value);
        }

    }
}

3．创建HDFSDriver 组装 Job

package com.atlxl.mr2;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class HDFSDriver extends Configuration implements Tool{

    private Configuration configuration = null;

    public int run(String[] args) throws Exception {

        //获取Job对象
        Job job = Job.getInstance(configuration);

        //设置主类
        job.setJarByClass(HDFSDriver.class);

        //设置Mapper
        job.setMapperClass(HDFSMapper.class);
        job.setMapOutputKeyClass(NullWritable.class);
        job.setMapOutputValueClass(Put.class);

        //设置Reducer
        TableMapReduceUtil.initTableReducerJob("fruit2", HDFSReducer.class, job);

        //设置输入路径
        FileInputFormat.setInputPaths(job, args[0]);

        //提交
        boolean result = job.waitForCompletion(true);

        return result?0:1;
    }

    public void setConf(Configuration conf) {
        configuration = conf;
    }

    public Configuration getConf() {
        return configuration;
    }

4．调用执行 Job


    public static void main(String[] args) throws Exception {
        Configuration configuration = HBaseConfiguration.create();
        int i = ToolRunner.run(configuration, new HDFSDriver(), args);

        System.exit(i);

    }

}

5．打包运行

输入路径为：HDFS

[lxl@hadoop102 hbase]$ /opt/module/hadoop-2.7.2/bin/yarn jar Hbase01-1.0-SNAPSHOT.jar com.atlxl.mr2.HDFSDriver /fruit.tsv

输入路径为：本地hbase包下

[lxl@hadoop102 hbase]$ /opt/module/hadoop-2.7.2/bin/yarn jar Hbase01-1.0-SNAPSHOT.jar com.atlxl.mr2.HDFSDriver file:///opt/module/hbase/fruit.tsv

自定义 HBase-MapReduce1