31-hadoop-hbase-mapreduce操作hbase

有一些大的文件，需要存入HBase中，其思想是先把文件传到HDFS上，利用map阶段读取<key,value>对，可在reduce把这些键值对上传到HBase中。

HbaseMapper:

package com.wenbronk.hbase.hbase;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class HbaseMapper extends Mapper<LongWritable, Text, Text, Text> {

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String[] split = value.toString().split(",");
        String k = split[];
        String v = split[];
        context.write(new Text(k), new Text(v));
    }
}

HbaseReducer

package com.wenbronk.hbase.hbase;

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.mapreduce.Reducer;

import javax.xml.soap.Text;
import java.io.IOException;

/**
 *

继承 TableReducer<KeyIn,Values,KeyOut>, 因此 Hbase中的key是ImmutableBytesWritable
*/
public class HbaseReducer extends TableReducer<Text, Text, ImmutableBytesWritable> { 

　　@Override 
　　protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
　　　　String k = key.toString(); 
　　　　StringBuilder sb = new StringBuilder(); 
　　　　for (Text value : values) { 
　　　　　　sb.append(value.toString()).append(","); 
　　　　} 
　　　　if (sb.length() > ) { 
　　　　　　sb.deleteCharAt(sb.length() - ); 
　　　　} 
　　　　// rowkey 
　　　　Put put = new Put(k.getBytes()); 
　　　　put.addColumn("cf1".getBytes(), "name".getBytes(), sb.toString().getBytes()); 
　　} 
}

job

package com.wenbronk.hbase.hbase;

import com.wenbronk.hbase.mapreduce.ReducerClass;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;

import java.io.IOException;

public class JobTest {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration config = new Configuration();
        config.set("fs.defaultFS", "hdfs://192.168.208.106:8020");
        config.set("yarn.resourcemanager.hostname", "192.168.208.106");
        config.set("mapred.job.tracker", "192.168.208.106:9001");
        config.set("ha.zookeeper.quorum", "192.168.208.106,192.168.208.107,192.168.208.108");

        Job job = new Job(config, "Hbase");
        job.setJarByClass(JobTest.class);

        FileSystem fileSystem = FileSystem.get(config);
        Path inPath = new Path("/usr/test/test.txt");
        job.setInputFormatClass(TextInputFormat.class);

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

        TableMapReduceUtil.initTableReducerJob("t_user", ReducerClass.class, job, null, null, null, null, false);

        boolean b = job.waitForCompletion(true);
        if (b) {
            System.out.println("mapreduce 执行成功");
        }

    }
}

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