使用BulkLoad从HDFS批量导入数据到HBase

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数据发出后首先写入到雨鞋日志WAl中，写入到预写日志中之后，随后写入到内存MemStore中，最后在Flush到Hfile中。这样写数据的方式不会导致数据的丢失，并且道正数据的有序性，但是当遇到大量的数据写入时，写入的速度就难以保证。所以，介绍一种性能更高的写入方式BulkLoad。

使用BulkLoad批量写入数据主要分为两部分：
一、使用HFileOutputFormat2通过自己编写的MapReduce作业将HFile写入到HDFS目录，由于写入到HBase中的数据是按照顺序排序的，HFileOutputFormat2中的configureIncrementalLoad()可以完成所需的配置。
二、将Hfile从HDFS移动到HBase表中，大致过程如图

实例代码pom依赖：

<dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>1.4.0</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.6.4</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>0.99.2</version>
        </dependency>

package com.yangshou;

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

import java.io.IOException;

public class BulkLoadMapper extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //读取文件中的每一条数据，以序号作为行键
        String line = value.toString();
        //将数据进行切分
        //切分后数组中的元素分别为：序号，用户id,商品id,用户行为，商品分类，时间，地址
        String[] str = line.split(" ");
        String id = str[0];
        String user_id = str[1];
        String item_id = str[2];
        String behavior = str[3];
        String item_type = str[4];
        String time = str[5];
        String address = "156";
        //拼接rowkey和put
        ImmutableBytesWritable rowkry = new ImmutableBytesWritable(id.getBytes());
        Put put = new Put(id.getBytes());
        put.add("info".getBytes(),"user_id".getBytes(),user_id.getBytes());
        put.add("info".getBytes(),"item_id".getBytes(),item_id.getBytes());
        put.add("info".getBytes(),"behavior".getBytes(),behavior.getBytes());
        put.add("info".getBytes(),"item_type".getBytes(),item_type.getBytes());
        put.add("info".getBytes(),"time".getBytes(),time.getBytes());
        put.add("info".getBytes(),"address".getBytes(),address.getBytes());
        //将数据写出
        context.write(rowkry,put);
    }
}

package com.yangshou;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.*;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat2;
import org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class BulkLoadDriver  {
    public static void main(String[] args) throws Exception {
        //获取Hbase配置
        Configuration conf = HBaseConfiguration.create();
        Connection conn = ConnectionFactory.createConnection(conf);
        Table table = conn.getTable(TableName.valueOf("BulkLoadDemo"));
        Admin admin = conn.getAdmin();

        //设置job
        Job job = Job.getInstance(conf,"BulkLoad");
        job.setJarByClass(BulkLoadDriver.class);
        job.setMapperClass(BulkLoadMapper.class);
        job.setMapOutputKeyClass(ImmutableBytesWritable.class);
        job.setMapOutputValueClass(Put.class);

        //设置文件的输入输出路径
        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(HFileOutputFormat2.class);
        FileInputFormat.setInputPaths(job,new Path("hdfs://hadoopalone:9000/tmp/000000_0"));
        FileOutputFormat.setOutputPath(job,new Path("hdfs://hadoopalone:9000/demo1"));

        //将数据加载到Hbase表中
        HFileOutputFormat2.configureIncrementalLoad(job,table,conn.getRegionLocator(TableName.valueOf("BulkLoadDemo")));
        if(job.waitForCompletion(true)){
            LoadIncrementalHFiles load = new LoadIncrementalHFiles(conf);
            load.doBulkLoad(new Path("hdfs://hadoopalone:9000/demo1"),admin,table,conn.getRegionLocator(TableName.valueOf("BulkLoadDemo")));

        }

    }
}

实例数据

44979   100640791   134060896   1   5271    2014-12-09  天津市
44980   100640791   96243605    1   13729   2014-12-02  新疆

在Hbase shell 中创建表

create ‘BulkLoadDemo‘,‘info‘

打包后执行
```hadoop jar BulkLoadDemo-1.0-SNAPSHOT.jar com.yangshou.BulkLoadDriver

注意：在执行hadoop jar之前应该先将Hbase中的相关包加载过来

export HADOOP_CLASSPATH=$HBASE_HOME/lib/*

使用BulkLoad从HDFS批量导入数据到HBase

标签：use   throw   classpath   imp   rgs   注意   prot   ide   ima   

原文地址：https://blog.51cto.com/14549997/2460819