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pipeline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pipeline的测试表和资源;

  • 创建表

    create table wc_in (key string, value string);
    create table wc_out(key string, cnt bigint);
    
  • 添加资源

    add jar mapreduce-examples.jar -f;
    

(3)使用tunnel导入数据;

   tunnel upload data wc_in;
  • 导入wc_in表的数据文件data内容为:
    hello,odps

测试步骤

在odpscmd中执行WordCountPipeline

jar -resources mapreduce-examples.jar -classpath mapreduce-examples.jar
    com.aliyun.odps.mapred.open.example.WordCountPipeline wc_in wc_out;

预期结果

作业成功结束。 输出表wc_out中内容为:

+------------+------------+
| key        | cnt        |
+------------+------------+
| hello      | 1          |
| odps       | 1          |
+------------+------------+

代码示例

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

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

    import com.aliyun.odps.Column;
    import com.aliyun.odps.OdpsException;
    import com.aliyun.odps.OdpsType;
    import com.aliyun.odps.data.Record;
    import com.aliyun.odps.data.TableInfo;
    import com.aliyun.odps.mapred.Job;
    import com.aliyun.odps.mapred.MapperBase;
    import com.aliyun.odps.mapred.ReducerBase;
    import com.aliyun.odps.pipeline.Pipeline;

    public class WordCountPipelineTest {

      public static class TokenizerMapper extends MapperBase {

        Record word;
        Record one;

        @Override
        public void setup(TaskContext context) throws IOException {
          word = context.createMapOutputKeyRecord();
          one = context.createMapOutputValueRecord();
          one.setBigint(0, 1L);
        }

        @Override
        public void map(long recordNum, Record record, TaskContext context)
            throws IOException {
          for (int i = 0; i < record.getColumnCount(); i++) {
            String[] words = record.get(i).toString().split("\\s+");
            for (String w : words) {
              word.setString(0, w);
              context.write(word, one);
            }
          }
        }
      }

      public static class SumReducer extends ReducerBase {
        private Record value;

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

        @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);
          }
          value.set(0, count);
          context.write(key, value);
        }
      }

      public static class IdentityReducer extends ReducerBase {
        private Record result;

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

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

      public static void main(String[] args) throws OdpsException {
        if (args.length != 2) {
          System.err.println("Usage: WordCountPipeline <in_table> <out_table>");
          System.exit(2);
        }

        Job job = new Job();


        /***
         * 构造Pipeline的过程中,如果不指定Mapper的OutputKeySortColumns,PartitionColumns,OutputGroupingColumns,
         * 框架会默认使用其OutputKey作为此三者的默认配置
         ***/
        Pipeline pipeline = Pipeline.builder()
            .addMapper(TokenizerMapper.class)
            .setOutputKeySchema(
                    new Column[] { new Column("word", OdpsType.STRING) })
            .setOutputValueSchema(
                    new Column[] { new Column("count", OdpsType.BIGINT) })
            .setOutputKeySortColumns(new String[] { "word" })
            .setPartitionColumns(new String[] { "word" })
            .setOutputGroupingColumns(new String[] { "word" })

            .addReducer(SumReducer.class)
            .setOutputKeySchema(
                    new Column[] { new Column("word", OdpsType.STRING) })
            .setOutputValueSchema(
                    new Column[] { new Column("count", OdpsType.BIGINT)})

            .addReducer(IdentityReducer.class).createPipeline();

        job.setPipeline(pipeline);

        job.addInput(TableInfo.builder().tableName(args[0]).build());
        job.addOutput(TableInfo.builder().tableName(args[1]).build());

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

    }
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