Hadoop整合Hbase案列详解

Peony ·

更新时间:2024-11-10

· 747 次阅读

需求：编写mapreduce程序实现将hbase中的一张表的数据复制到另一张表中

要求：读取HBase当中user这张表的f1:name、f1:age数据，将数据写入到另外一张user2表的f1列族里面去==***

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第一步：创建表

**注意：**两张表的列族一定要相同

/**
 create 'user','f1'
 put 'user','rk001','f1:name','tony'
 put 'user','rk001','f1:age','12'
 put 'user','rk001','f1:address','beijing'
 put 'user','rk002','f1:name','wangwu'
 create 'user2','f1'
 */

第二步：创建maven工程并导入jar包

pom.xml文件内容如下：


    4.0.0
    Hadoop
    HbaseTang
    1.0-SNAPSHOT
    jar
        2.7.3
            commons-cli
            commons-cli
            1.2
            commons-logging
            commons-logging
            1.1.3
            org.apache.hadoop
            hadoop-mapreduce-client-jobclient
            ${hadoop.version}
            org.apache.hadoop
            hadoop-common
            ${hadoop.version}
            org.apache.hadoop
            hadoop-hdfs
            2.7.3
            org.apache.hadoop
            hadoop-hdfs
            ${hadoop.version}
            org.apache.hadoop
            hadoop-mapreduce-client-app
            ${hadoop.version}
            org.apache.hadoop
            hadoop-mapreduce-client-hs
            ${hadoop.version}
            org.apache.hbase
            hbase-client
            1.2.1
            org.apache.hbase
            hbase-common
            1.2.1
            org.apache.hbase
            hbase-server
            1.2.1
            junit
            junit
            4.12

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第三步：开发MR程序实现功能 （1）自定义map类

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.io.Text;

import java.io.IOException;

/**

myuser f1: name&age => myuser2 f1
*/
public class HBaseReadMapper extends TableMapper {
/**
*

@param key rowkey

@param value rowkey此行的数据 Result类型

@param context

@throws IOException

@throws InterruptedException
*/
@Override
protected void map(ImmutableBytesWritable key, Result value, Context context) throws IOException, InterruptedException {

/**

ImmutableBytesWritable key:Mapper接收数据值是Put对象，key是hbase中一条数据Put对应的rowkey(可序列化)

Result value：hbase中读取的result对象

获取rowkey的字节数组
*/

//获得roweky的字节数组
byte[] rowkey_bytes = key.get();
String rowkeyStr = Bytes.toString(rowkey_bytes);
Text text = new Text(rowkeyStr);

//输出数据 -> 写数据 -> Put 构建Put对象
Put put = new Put(rowkey_bytes);
//获取一行中所有的Cell对象
Cell[] cells = value.rawCells();
//将f1 : name& age输出
for(Cell cell: cells) {
//当前cell是否是f1
//列族
byte[] family_bytes = CellUtil.cloneFamily(cell);
String familyStr = Bytes.toString(family_bytes);
if("f1".equals(familyStr)) {
//在判断是否是name | age
byte[] qualifier_bytes = CellUtil.cloneQualifier(cell);
String qualifierStr = Bytes.toString(qualifier_bytes);
if("name".equals(qualifierStr)) {
put.add(cell);
}
if("age".equals(qualifierStr)) {
put.add(cell);
}
}
}

//判断是否为空；不为空，才输出
if(!put.isEmpty()){
context.write(text, put);
}
}
}

（2）自定义reduce类

package com.kaikeba.hbase.demo01;
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.Text;
import java.io.IOException;
/**
 * TableReducer第三个泛型包含rowkey信息
 */
public class HBaseWriteReducer extends TableReducer {
    //将map传输过来的数据，写入到hbase表
    /**
     Text:map端输出键类型
     Put:map端输出值类型
     ImmutableBytesWritable:reduce端输出键类型
    */
    @Override
    protected void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException {
        /**
        *Text key:接收map端输出键
        *Iterable values:接收map端输出值，put对象封装成的迭代器
        */
        //rowkey
        ImmutableBytesWritable immutableBytesWritable = new ImmutableBytesWritable();
        immutableBytesWritable.set(key.toString().getBytes());
        //遍历put对象，并输出
        for(Put put: values) {
            context.write(immutableBytesWritable, put);
        }
    }
}

（3）main入口类

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
public class HBaseMR extends Configured implements Tool {
    public static void main(String[] args) throws Exception {
        Configuration configuration = HBaseConfiguration.create();
        //设定绑定的zk集群
        configuration.set("hbase.zookeeper.quorum", "node01:2181,node02:2181,node03:2181");
        int run = ToolRunner.run(configuration, new HBaseMR(), args);
        System.exit(run);
    }
    @Override
    public int run(String[] args) throws Exception {
        Job job = Job.getInstance(super.getConf());
        job.setJarByClass(HBaseMR.class);
        //mapper
        TableMapReduceUtil.initTableMapperJob(TableName.valueOf("myuser"), new Scan(),HBaseReadMapper.class, Text.class, Put.class, job);
        //reducer
        TableMapReduceUtil.initTableReducerJob("myuser2", HBaseWriteReducer.class, job);
        boolean b = job.waitForCompletion(true);
        return b? 0: 1;
    }
}

第四步：打成jar包提交到集群运行

打包：
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执行命令：