黑猴子的家：HBase 自定义HBase-MapReduce案列二

实现将HDFS中的数据写入到HBase表中

1、Code -> GitHub

https://github.com/liufengji/hbase_mapreduce_two.git

2、构建ReadFruitFromHDFSMapper类用于读取HDFS中的文件数据

import java.io.IOException;

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;


public class ReadFruitFromHDFSMapper extends Mapper<LongWritable, Text,
                                              ImmutableBytesWritable, Put> {
    
    @SuppressWarnings("deprecation")
    @Override
    protected void map(LongWritable key, Text value, Context context) 
                                      throws IOException, InterruptedException {
        
        //从HDFS中读取的数据
        String lineValue = value.toString();
        
        //读取出来的每行数据使用\t进行分割，存于String数组
        String[] values = lineValue.split("\t");
        
        //根据数据中值的含义取值
        String rowKey = values[0];
        String name = values[1];
        String color = values[2];
        
        //初始化rowKey
        ImmutableBytesWritable rowKeyWritable = 
                                  new ImmutableBytesWritable(Bytes.toBytes(rowKey));
        
        //初始化put对象
        Put put = new Put(Bytes.toBytes(rowKey));
        
        //参数分别:列族、列、值  
        put.add(Bytes.toBytes("info"), Bytes.toBytes("name"),
                                            Bytes.toBytes(name)); 
        put.add(Bytes.toBytes("info"), Bytes.toBytes("color"), 
                                            Bytes.toBytes(color)); 
        
        context.write(rowKeyWritable, put);
    }
}

3、构建WriteFruitMRFromTxtReducer类用于写入到HBase表中

import java.io.IOException;
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;


public class WriteFruitMRFromTxtReducer extends TableReducer<ImmutableBytesWritable,
                                                                Put, NullWritable> {
    
    @Override
    protected void reduce(ImmutableBytesWritable key, Iterable<Put> values,
                        Context context) throws IOException, InterruptedException {
        //读出来的每一行数据写入到fruit_hdfs表中
        for(Put put: values){
            context.write(NullWritable.get(), put);
        }
    }
    
}

4、创建Txt2FruitRunner组装Job

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.TableMapReduceUtil;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class Txt2FruitRunner extends Configured implements Tool {

    @Override
    public int run(String[] args) throws Exception {

        // 得到Configuration
        Configuration conf = this.getConf();

        // 创建Job任务
        Job job = Job.getInstance(conf, this.getClass().getSimpleName());
        job.setJarByClass(Txt2FruitRunner.class);
        Path inPath = new Path("hdfs://node1:9000/input_fruit/fruit.tsv");
        FileInputFormat.addInputPath(job, inPath);

        // 设置Mapper
        job.setMapperClass(ReadFruitFromHDFSMapper.class);
        job.setMapOutputKeyClass(ImmutableBytesWritable.class);
        job.setMapOutputValueClass(Put.class);

        // 设置Reducer
        TableMapReduceUtil.initTableReducerJob("fruit_mr",
                                     WriteFruitMRFromTxtReducer.class, job);

        // 设置Reduce数量，最少1个
        job.setNumReduceTasks(1);

        boolean isSuccess = job.waitForCompletion(true);
        if (!isSuccess) {
            throw new IOException("Job running with error");
        }

        return isSuccess ? 0 : 1;
    }
}

5、主函数中调用运行该Job任务

    public static void main(String[] args) throws Exception {
        Configuration conf = HBaseConfiguration.create();
        int status = ToolRunner.run(conf, new Txt2FruitRunner(), args);
        System.exit(status);
    }

6、打包运行任务

[victor@node1 hbase-1.3.1]$ /opt/module/hadoop-2.7.2/bin/yarn jar \
hbase-0.0.1-SNAPSHOT.jar com.victor.hbase.mr2.Txt2FruitRunner

尖叫提示：运行任务前，如果待数据导入的表不存在，则需要提前创建之。
尖叫提示：maven打包命令：-P local clean package或-P dev clean package install（将第三方jar包一同打包，需要插件：maven-shade-plugin）