上一节我们介绍了使用hbase提供的接口完成其与hdfs之间数据导入导出，但显然这种基于自带接口实现的操作是有局限的，即不能直接将hdfs中的数据导入到hbase。这一节我们将介绍一种更为通用的方法去完成从hdfs导入数据到hbase。

1、前提约束

• 已完成安装hdfs并启动
  https://www.jianshu.com/p/b7ae3b51e559
  假设hadoop的安装路径为：/root/hadoop-2.5.2，对应的ip为192.168.100.141，域名为hadoop1
• 已完成安装hbase并启动
  https://www.jianshu.com/p/90d1713d55ce
  假设hbase的安装路径为：/root/hbase-1.2.6，对应的ip为192.168.100.141
• win10本地安装hadoop
  假设路径为 C:/hadoop2.7.2

2、操作步骤

• 在idea中创建maven项目，加入以下依赖

        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-metastore</artifactId>
            <version>2.3.4</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-jdbc</artifactId>
            <version>0.14.0</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.47</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>1.1.1</version>
        </dependency>

• 在src/main/java文件夹下创建HdfsToHBase.java

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableOutputFormat;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import java.io.IOException;

public class HdfsToHBase {
    public static void main(String[] args) {
        try {
            System.setProperty("hadoop.home.dir", "C:/hadoop2.7.2");
            Configuration conf = HBaseConfiguration.create();
            conf.set("hbase.zookeeper.quorum", "192.168.100.141:2181");
            conf.set(TableOutputFormat.OUTPUT_TABLE, "t_user");
            Job job = Job.getInstance(conf, HdfsToHBase.class.getSimpleName());
            TableMapReduceUtil.addDependencyJars(job);
            job.setJarByClass(HdfsToHBase.class);

            job.setMapperClass(HdfsToHBaseMapper.class);
            job.setMapOutputKeyClass(Text.class);
            job.setMapOutputValueClass(Text.class);

            job.setReducerClass(HdfsToHBaseReducer.class);

            FileInputFormat.addInputPath(job, new Path("hdfs://192.168.100.141:9000/t_user"));
            job.setOutputFormatClass(TableOutputFormat.class);
            job.waitForCompletion(true);
        }
        catch (Exception e)
        {
            e.printStackTrace();
        }
    }

    public static class HdfsToHBaseMapper extends Mapper<LongWritable, Text, Text, Text> {
        private Text outKey = new Text();
        private Text outValue = new Text();

        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            String[] splits = value.toString().split("\\s");
            outKey.set(splits[0]);
            outValue.set(splits[1] + "," + splits[2]);
            context.write(outKey, outValue);
        }
    }

    public static class HdfsToHBaseReducer extends TableReducer<Text, Text, NullWritable> {
        @Override
        protected void reduce(Text k2, Iterable<Text> v2s, Context context) throws IOException, InterruptedException {
            Put put = new Put(k2.getBytes());
            for (Text v2 : v2s) {
                String[] splis = v2.toString().split(",");
                if (splis[0] != null && !"NULL".equals(splis[0])) {
                    put.add("f1".getBytes(), "name".getBytes(), splis[0].getBytes());
                }
                if (splis[1] != null && !"NULL".equals(splis[1])) {
                    put.add("f1".getBytes(), "age".getBytes(), splis[1].getBytes());
                }
            }
            context.write(NullWritable.get(), put);
        }
    }
}

• 修改C:\Windows\System32\drivers\etc\hosts，加入以下内容：
  192.168.100.141 hadoop1
• 在linux的hdfs中上传以下内容到/t_user

1 ali 10
2 xiaoli 20
3 zhangli 30
4 ali 11

• 在linux的hbase中创建表格

/root/hbase-1.2.6/hbase shell
create 't_user','f1'

• 执行HdfsToHBase.java
• 在linux的hbase中查看t_user

/root/hbase-1.2.6/hbase shell
scan 't_user'

hbase中t_user的内容

以上就是使用mr自定义完成hdfs数据导入到hbase。