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二次排序示例

更新时间:2017-06-07 13:26:11   分享:   

(1)准备好测试程序jar包,假设名字为mapreduce-examples.jar;

(2)准备好SecondarySort的测试表和资源;

  • 创建表

    create table ss_in(key bigint, value bigint);
    create table ss_out(key bigint, value bigint)
    
  • 添加资源

    add jar mapreduce-examples.jar -f;
    

(3)使用tunnel导入数据;

   tunnel upload data ss_in;
  • 导入ss_in表的数据文件data内容为:

    1,2
    2,1
    1,1
    2,2
    

测试步骤

在odpscmd中执行SecondarySort

jar -resources mapreduce-examples.jar -classpath mapreduce-examples.jar 
    com.aliyun.odps.mapred.open.example.SecondarySort ss_in ss_out;

预期结果

作业成功结束。 输出表ss_out中内容为:

+------------+------------+
| key        | value      |
+------------+------------+
| 1          | 1          |
| 1          | 2          |
| 2          | 1          |
| 2          | 2          |
+------------+------------+

代码示例

    package com.aliyun.odps.mapred.open.example;

    import java.io.IOException;
    import java.util.Iterator;

    import com.aliyun.odps.data.Record;
    import com.aliyun.odps.mapred.JobClient;
    import com.aliyun.odps.mapred.MapperBase;
    import com.aliyun.odps.mapred.ReducerBase;
    import com.aliyun.odps.mapred.TaskContext;
    import com.aliyun.odps.mapred.conf.JobConf;
    import com.aliyun.odps.mapred.utils.SchemaUtils;
    import com.aliyun.odps.mapred.utils.InputUtils;
    import com.aliyun.odps.mapred.utils.OutputUtils;
    import com.aliyun.odps.data.TableInfo;

    /**
     * 
     * This is an example ODPS Map/Reduce application. It reads the input table that
     * must contain two integers per record. The output is sorted by the first and
     * second number and grouped on the first number.
     *
     **/
    public class SecondarySort {

      /**
       * Read two integers from each line and generate a key, value pair as ((left,
       * right), right).
       **/
      public static class MapClass extends MapperBase {
        private Record key;
        private Record value;

        @Override
        public void setup(TaskContext context) throws IOException {
          key = context.createMapOutputKeyRecord();
          value = context.createMapOutputValueRecord();
        }

        @Override
        public void map(long recordNum, Record record, TaskContext context)
            throws IOException {
          long left = 0;
          long right = 0;

          if (record.getColumnCount() > 0) {
            left = (Long) record.get(0);
            if (record.getColumnCount() > 1) {
              right = (Long) record.get(1);
            }

            key.set(new Object[] { (Long) left, (Long) right });
            value.set(new Object[] { (Long) right });

            context.write(key, value);
          }
        }
      }

      /**
       * A reducer class that just emits the sum of the input values.
       **/
      public static class ReduceClass extends ReducerBase {

        private Record result = null;

        @Override
        public void setup(TaskContext context) throws IOException {
          result = context.createOutputRecord();
        }

        @Override
        public void reduce(Record key, Iterator<Record> values, TaskContext context)
            throws IOException {
          result.set(0, key.get(0));
          while (values.hasNext()) {
            Record value = values.next();
            result.set(1, value.get(0));
            context.write(result);
          }
        }

      }

      public static void main(String[] args) throws Exception {
        if (args.length != 2) {
          System.err.println("Usage: secondarysrot <in> <out>");
          System.exit(2);
        }

        JobConf job = new JobConf();
        job.setMapperClass(MapClass.class);
        job.setReducerClass(ReduceClass.class);

        //将多列设置为Key
        // compare first and second parts of the pair
        job.setOutputKeySortColumns(new String[] { "i1", "i2" });

        // partition based on the first part of the pair
        job.setPartitionColumns(new String[] { "i1" });

        // grouping comparator based on the first part of the pair
        job.setOutputGroupingColumns(new String[] { "i1" });

        // the map output is LongPair, Long
        job.setMapOutputKeySchema(SchemaUtils.fromString("i1:bigint,i2:bigint"));
        job.setMapOutputValueSchema(SchemaUtils.fromString("i2x:bigint"));

        InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
        OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);

        JobClient.runJob(job);
        System.exit(0);
      }

    }
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