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#!html
<div style="text-align: center; color:#151B8D"><big style="font-weight: bold;"><big><big>
HBase 進階課程 
</big></big></big></div> <div style="text-align: center; color:#7E2217"><big style="font-weight: bold;"><big>
程式範例練習
</big></big></div>
}}}

[wiki:NCHCCloudCourse100929_4_HBEX6 上一關 < ] 最後一關 [wiki:NCHCCloudCourse110721#第二天 >> 回課程大綱]

 = 範例七： LoadHBaseMapper = 

 == 說明：  == 
	此程式碼將HBase的資料取出來，再將結果塞回hdfs上
{{{
$ bin/hadoop jar TCRCExample.jar LoadHBaseMapper output
}}}

== 注意： ==
1.	請注意之前已經run 過 範例六

2.	運算完後，程式將執行結果放在你指定 hdfs的<hdfs_output> 內
 		請注意 沒有 <hdfs_output> 資料夾


{{{
#!java

package org.nchc.hbase;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableInputFormat;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class LoadHBaseMapper {
  public static class HtMap extends TableMapper<Text, Text> {

    public void map(ImmutableBytesWritable key, Result value,
        Context context) throws IOException, InterruptedException {
//    	content:count
      String res = Bytes.toString(value.getValue(Bytes.toBytes("content"),
          Bytes.toBytes("count")));

      context.write(new Text(key.toString()), new Text(res));

    }
  }

  // TableReducer<KEYIN,VALUEIN,KEYOUT>
  // 原本為 TableReducer<Text, IntWritable, NullWritable >
  // 但在此改成 LongWritable 也可以
  // 因此證明在此的Class可以很多,org.apache.hadoop.io.* 內有write()的Writable class應該皆可
  public static class HtReduce extends Reducer<Text, Text, Text, Text> {

    public void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {

      String str = new String("");
      Text final_key = new Text(key);
      Text final_value = new Text();
      // 將key值相同的values，透過 && 符號分隔之
      for (Text tmp : values) {
        str += tmp.toString();
      }
      final_value.set(str);
      context.write(final_key, final_value);
    }
  }

  public static void main(String args[]) throws Exception {
    // debug
//    String[] argv = { "output-lhm" };
//    args = argv;

    String tablename = "wordcount";

    Configuration conf = new Configuration();

    Job job = new Job(conf, tablename + " hbase data to hdfs");
    job.setJarByClass(LoadHBaseMapper.class);

    // // 設定哪張hbase的table為輸入
    conf.set(TableInputFormat.INPUT_TABLE, tablename);
    Scan myScan = new Scan("".getBytes(), "12".getBytes());
    myScan.addColumn("content:count".getBytes());

    // 先用 TableMapReduceUtil 的 initTableMapperJob 與 initTableReducerJob 來做設定
    TableMapReduceUtil.initTableMapperJob(tablename, myScan, HtMap.class,
        Text.class, Text.class, job);

    job.setMapperClass(HtMap.class);
    job.setReducerClass(HtReduce.class);

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

    job.setInputFormatClass(TableInputFormat.class);
    job.setOutputFormatClass(TextOutputFormat.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);

    FileOutputFormat.setOutputPath(job, new Path(args[0]));

    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}


}}}

 * 執行結果

觀察 /user/hadoop/output-lhm/part-r-00000 檔案的結果