简单的 MapReduce 程序的示例代码，用于统计 HBase 中的成绩表中的单科排名和总分排名，并将结果上传到 HDFS 中。

下面是一个简单的 MapReduce 程序的示例代码，用于统计 HBase 中的成绩表中的单科排名和总分排名，并将结果上传到 HDFS 中：

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
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.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Reducer;

public class RankCalculator {

  public static class RankMapper
      extends TableMapper<Text, IntWritable> {

    private Text subject = new Text();
    private final static IntWritable score = new IntWritable(1);

    public void map(ImmutableBytesWritable row, Result value, Context context)
        throws IOException, InterruptedException {
      String subjectStr = Bytes.toString(value.getValue(Bytes.toBytes("grades"),
          Bytes.toBytes("subject")));
      subject.set(subjectStr);
      int scoreInt = Bytes.toInt(value.getValue(Bytes.toBytes("grades"),
          Bytes.toBytes("score")));
      score.set(scoreInt);
      context.write(subject, score);
    }
  }

  public static class RankReducer
      extends Reducer<Text, IntWritable, Text, IntWritable> {

    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values,
        Context context) throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      result.set(sum);
      context.write(key, result);
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = HBaseConfiguration.create();
    Job job = Job.getInstance(conf, "rank calculator");
    job.setJarByClass(RankCalculator.class);
    Scan scan = new Scan();
    scan.setCaching(500);
    scan.setCacheBlocks(false);
    TableMapReduceUtil.initTableMapperJob("grades", scan, RankMapper.class,
        Text.class, IntWritable.