使用 MapReduce 统计 HBase 表中单科最高单科排名和总分排名的代码

这里是一个使用 MapReduce 统计 HBase 表中单科最高单科排名和总分排名的示例代码：

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;

public class HBaseRankCalculator {

  public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
    Configuration conf = HBaseConfiguration.create();
    Job job = Job.getInstance(conf, "HBase Rank Calculator");
    job.setJarByClass(HBaseRankCalculator.class);

    Scan scan = new Scan();
    scan.setCaching(500);
    scan.setCacheBlocks(false);

    TableMapReduceUtil.initTableMapperJob(
        "student_scores", // 表名
        scan,
        RankMapper.class, // Mapper 类
        Text.class, // Mapper 输出 key 类型
        IntWritable.class, // Mapper 输出 value 类型
        job
    );
    TableMapReduceUtil.initTableReducerJob(
        "student_ranks", // 输出表名
        RankReducer.class, // Reducer 类
        job
    );

    job.setNumReduceTasks(1); // 设置 Reducer 个数

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

Mapper 类 RankMapper 的代码：

import java.io.IOException;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;

public class RankMapper extends TableMapper<Text, IntWritable> {

  private final IntWritable ONE = new IntWritable(1);

  @Override
  public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {
    // 从 value 中获取学生的单科成绩和总分
    // 并将其作为 key 输出，将 value