Prerequisites

  1. Prepare the Jar package of the test program. Assume the package is named mapreduce-examples.jar. The local storage path is data\resources.
    • Create tables:
      create table wc_in (key string, value string);
      create table wc_out(key string, cnt bigint);
    • Add resources:
      add jar data\resources\mapreduce-examples.jar -f;
  2. Prepare tables and resources for testing the WordCount operation.
  3. Run tunnel to import data.
    tunnel upload data wc_in;
    The contents of data file imported into the table wc_in, as follows:
    hello,odps

Procedure

Run WordCount in odpscmd.
jar -resources mapreduce-examples.jar -classpath data\resources\mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.WordCount wc_in wc_out

Expected output

The content of output table wc_out  is as follows:
+------------+------------+
| key | cnt |
+------------+------------+
| hello | 1 |
| odps | 1 |
+------------+------------+

Sample code

    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.data.TableInfo;
    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.InputUtils;
    import com.aliyun.odps.mapred.utils.OutputUtils;
    import com.aliyun.odps.mapred.utils.SchemaUtils;
    public class WordCount {
      public static class TokenizerMapper extends MapperBase {
        private Record word;
        private Record one;
        @Override
        public void setup(TaskContext context) throws IOException{
          word = context.createMapOutputKeyRecord();
          one = context.createMapOutputValueRecord();
          one.set(new Object[] { 1L });
          System.out.println("TaskID:" + context.getTaskID().toString());
        }
        @Override
        public void map(long recordNum, Record record, TaskContext context)
            throws IOException {
          for (int i = 0; i < record.getColumnCount(); i++) {
            word.set(new Object[] { record.get(i).toString() });
            context.write(word, one);
          }
        }
      }
      /**
       * A combiner class that combines map output by sum them.
       **/
      public static class SumCombiner extends ReducerBase {
        private Record count;
        @Override
        public void setup(TaskContext context) throws IOException{
          count = context.createMapOutputValueRecord();
        }
        // Assemblyer implements the same interface as reducer, you can immediately reduce the output of the mapper for a reduce that is performed locally on the mapper.
        @Override
        public void reduce(Record key,Iterator<Record>values,TaskContext context)
            throws IOException {
          long c = 0;
          while(values.hasNext()) {
            Record val = values.next();
            c += (Long) val.get(0);
          }
          count.set(0, c);
          context.write(key, count);
        }
      }
      /**
       * A reducer class that just emits the sum of the input values.
       **/
      public static class SumReducer 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 {
          Long Count = 0;
          while(values.hasNext()) {
            Record val = values.next();
            count += (Long) val.get(0);
          }
          result.set(0, key.get(0));
          result.set(1, count);
          context.write(result);
        }
      }
      public static void main(String[] args) throws Exception {
        if (args.length ! = 2) {
           System.err.println("Usage: WordCount <in_table> <out_table>");
          System.exit(2);
        }
        JobConf job = new JobConf();
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(SumCombiner.class);
        job.setReducerClass(SumReducer.class);
//The schema that sets the key and value of the mapper's intermediate result, the mapper's intermediate output is also the form of a record.
        job.setMapOutputKeySchema(SchemaUtils.fromString("word:string"));
        job.setMapOutputValueSchema(SchemaUtils.fromString("count:bigint"));
        //Set input and output table information
        InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
        OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
        Jobclient. runjob (job );
      }
    }