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  此篇为大家带来的是官方HBase-MapReduce与自定义。


目录


  通过HBase的相关JavaAPI,我们可以实现伴随HBase操作的MapReduce过程,比如使用MapReduce将数据从本地文件系统导入到HBase的表中,比如我们从HBase中读取一些原始数据后使用MapReduce做数据分析。

标注:
此处为反爬虫标记:读者可自行忽略

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据

1. 官方HBase-MapReduce

1.查看HBase的MapReduce任务的执行

[bigdata@hadoop002 hbase]$ bin/hbase mapredcp

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_02

上图标记处为所需jar包

2. 环境变量的导入

  • 1. 执行环境变量的导入(临时生效,在命令行执行下述操作)
$ export HBASE_HOME=/opt/module/hbase
$ export HADOOP_HOME=/opt/module/hadoop-2.7.2
$ export HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase mapredcp`

// 也可以直接这样
[bigdata@hadoop002 hbase]$ export HADOOP_CLASSPATH=`/opt/module/hbase/bin/hbase mapredcp`

配置完成后查看是否成功

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_mapreduce_03

  • 2. 永久生效:在/etc/profile配置
export HBASE_HOME=/opt/module/hbase
export HADOOP_HOME=/opt/module/hadoop-2.7.2

在hadoop-env.sh中配置:(注意:在for循环之后配)

export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:/opt/module/hbase/lib/*
  • 3. 运行官方的MapReduce任务

– 案例一:统计Student表中有多少行数据

[bigdata@hadoop002 hbase]$ /opt/module/hadoop-2.7.2/bin/yarn jar lib/hbase-server-1.3.1.jar rowcounter student

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_apache_04

– 案例二:使用MapReduce将HDFS导入到HBase

  • 1.在本地创建一个tsv格式的文件:fruit.tsv
[bigdata@hadoop002 datas]$ vim fruit.tsv

1001 Apple Red
1002 Pear Yellow
1003 Pineapple Yellow

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_hbase_05

  • 2.创建HBase表
hbase(main):001:0> create 'fruit','info'
  • 3.在HDFS中创建input_fruit文件夹并上传fruit.tsv文件
[bigdata@hadoop002 datas]$ hadoop fs -mkdir /input_fruit/
[bigdata@hadoop002 datas]$ hadoop fs -put fruit.tsv /input_fruit/

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_06

  • 4.执行MapReduce到HBase的fruit表中
[bigdata@hadoop002 hbase]$ /opt/module/hadoop-2.7.2/bin/yarn jar lib/hbase-server-1.3.1.jar importtsv \
-Dimporttsv.columns=HBASE_ROW_KEY,info:name,info:color fruit \
hdfs://hadoop002:9000/input_fruit
  • 5.使用scan命令查看导入后的结果
hbase(main):001:0> scan ‘fruit’

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_hadoop_07

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_apache_08

经过测试证明是没问题的

2. 自定义HBase-MapReduce1

目标:将fruit表中的一部分数据,通过MR迁入到fruit_mr表中。

  • 1.构建ReadMapper类,用于读取fruit表中的数据
package com.buwenbuhuo.hbase.mr;

import java.io.IOException;
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;


/**
* @author 卜温不火
* @create 2020-05-12 19:32
* com.buwenbuhuo.hbase.mr - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class ReadMapper extends TableMapper<ImmutableBytesWritable,Put> {

@Override
protected void map(ImmutableBytesWritable key, Result value, Context context) throws IOException, InterruptedException {
Put put = new Put(key.copyBytes());

for (Cell cell : value.rawCells()) {
if ("name".equals(Bytes.toString(CellUtil.cloneQualifier(cell)))){

put.add(cell);

}
}
context.write(key,put);
}
}
  • 2. 构建WriteReducer类,用于将读取到的fruit表中的数据写入到fruit_mr表中
package com.buwenbuhuo.hbase.mr;

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;


/**
* @author 卜温不火
* @create 2020-05-12 19:32
* com.buwenbuhuo.hbase.mr - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class WriteReducer extends TableReducer<ImmutableBytesWritable,Put, NullWritable> {

@Override
protected void reduce(ImmutableBytesWritable key, Iterable<Put> values, Context context) throws IOException, InterruptedException {
for (Put value : values) {
context.write(NullWritable.get(),value);
}
}
}
  • 3. 构建Driver用于组装运行Job任务
package com.buwenbuhuo.hbase.mr;

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.HRegionPartitioner;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.mapreduce.Job;

import java.io.IOException;

/**
* @author 卜温不火
* @create 2020-05-12 19:32
* com.buwenbuhuo.hbase.mr - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class Driver {

public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {

Configuration conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum", "hadoop002,hadoop003,hadoop004");
conf.set("hbase.zookeeper.property.clientPort", "2181");

Job job = Job.getInstance();

job.setJarByClass(Driver.class);

Scan scan = new Scan();

TableMapReduceUtil.initTableMapperJob(
"fruit",
scan,
ReadMapper.class,
ImmutableBytesWritable.class,
Put.class,
job
);

job.setNumReduceTasks(100);

TableMapReduceUtil.initTableReducerJob("fruit_mr",WriteReducer.class,job,HRegionPartitioner.class);

job.waitForCompletion(true);

}

}
  • 4. 打包并上传
    HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_09
    HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_hadoop_10
  • 5. 创建表
hbase(main):003:0> create 'fruit_mr','info'

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_11

  • 6. 运行验证
[bigdata@hadoop002 hbase]$ hadoop jar hbase-0512-1.0-SNAPSHOT.jar com.buwenbuhuo.hbase.mr.Driver

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_apache_12

hbase(main):005:0> scan 'fruit_mr'

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_13

3. 自定义HBase-MapReduce2

目标:实现将HDFS中的数据写入到HBase表中。

  • 1. 构建ReadFruitFromHDFSMapper于读取HDFS中的文件数据
package com.buwenbuhuo.hbase.mr2;

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

import java.io.IOException;

/**
* @author 卜温不火
* @create 2020-05-12 22:41
* com.buwenbuhuo.hbase.mr2 - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class ReadMapper extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {

@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

String[] split = value.toString().split("\t");

if (split.length <= 3){
return;
}

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]));

context.write(new ImmutableBytesWritable(Bytes.toBytes(split[0])),put);

}
}
  • 2. 构建WriteFruitMRFromTxtReducer类
package com.buwenbuhuo.hbase.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;

/**
* @author 卜温不火
* @create 2020-05-12 23:09
* com.buwenbuhuo.hbase.mr2 - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class WriteReducer extends TableReducer<ImmutableBytesWritable, Put, NullWritable> {
@Override
protected void reduce(ImmutableBytesWritable key, Iterable<Put> values, Context context) throws IOException, InterruptedException {

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

}
}
  • 3.创建Driver
package com.buwenbuhuo.hbase.mr2;

import com.buwenbuhuo.hbase.mr.WriteReducer;
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.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.HRegionPartitioner;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import java.io.IOException;

/**
* @author 卜温不火
* @create 2020-05-12 23:09
* com.buwenbuhuo.hbase.mr2 - the name of the target package where the new class or interface will be created.
* hbase0512 - the name of the current project.
*/
public class Driver {

public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum", "hadoop002,hadoop003,hadoop004");
Job job = Job.getInstance(conf);

job.setJarByClass(Driver.class);

job.setMapperClass(ReadMapper.class);

job.setMapOutputKeyClass(ImmutableBytesWritable.class);
job.setMapOutputValueClass(Put.class);

FileInputFormat.setInputPaths(job,new Path("/input_fruit"));

job.setNumReduceTasks(10);

TableMapReduceUtil.initTableReducerJob("fruit_mr", WriteReducer.class,job, HRegionPartitioner.class);

job.waitForCompletion(true);
}

}
  • 4. 打包上传
    HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_hbase_14
    HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_mapreduce_15
  • 5.测试运行
[bigdata@hadoop002 hbase]$ hadoop jar hbase-0512-1.0-SNAPSHOT.jar com.buwenbuhuo.hbase.mr2.Driver

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_16

HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_大数据_17

  本次的分享就到这里了,


HBase快速入门系列(7) | 官方HBase-MapReduce与自定义_hadoop_18


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