本文为您介绍MapReduce的使用资源示例。

测试准备

  1. 准备好测试程序的Jar包,假设名字为mapreduce-examples.jar,本地存放路径为data\resources
  2. 在MaxCompute客户端中执行如下操作,准备好测试表和资源。
    1. 创建测试表。
      create table mr_upload_src(key bigint, value string);
    2. 添加测试资源。
      add jar data\resources\mapreduce-examples.jar -f;
      add file data\resources\import.txt -f;
    3. import.txt的数据内容如下。
      1000,odps

测试步骤

在MaxCompute客户端中执行Upload。
jar -resources mapreduce-examples.jar,import.txt -classpath data\resources\mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.Upload import.txt mr_upload_src;

预期结果

作业成功结束后,输出表mr_upload_src中的内容如下。
+------------+------------+
| key        | value      |
+------------+------------+
| 1000       | odps       |
+------------+------------+

代码示例

Pom依赖信息,请参见注意事项

package com.aliyun.odps.mapred.open.example;
import java.io.BufferedInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
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.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;
/**
     * Upload
     *
     * Import data from text file into table
     *
     **/
public class Upload {
    public static class UploadMapper extends MapperBase {
        @Override
            public void setup(TaskContext context) throws IOException {
            Record record = context.createOutputRecord();
            StringBuilder importdata = new StringBuilder();
            BufferedInputStream bufferedInput = null;
            try {
                byte[] buffer = new byte[1024];
                int bytesRead = 0;
                String filename = context.getJobConf().get("import.filename");
                bufferedInput = context.readResourceFileAsStream(filename);
                while ((bytesRead = bufferedInput.read(buffer)) != -1) {
                    String chunk = new String(buffer, 0, bytesRead);
                    importdata.append(chunk);
                }
                String lines[] = importdata.toString().split("\n");
                for (int i = 0; i < lines.length; i++) {
                    String[] ss = lines[i].split(",");
                    record.set(0, Long.parseLong(ss[0].trim()));
                    record.set(1, ss[1].trim());
                    context.write(record);
                }
            } catch (FileNotFoundException ex) {
                throw new IOException(ex);
            } catch (IOException ex) {
                throw new IOException(ex);
            } finally {
            }
        }
        @Override
            public void map(long recordNum, Record record, TaskContext context)
            throws IOException {
        }
    }
    public static void main(String[] args) throws Exception {
        if (args.length != 2) {
            System.err.println("Usage: Upload <import_txt> <out_table>");
            System.exit(2);
        }
        JobConf job = new JobConf();
        job.setMapperClass(UploadMapper.class);
        /**设置资源名字, 可以在map中通过jobconf获取到。*/
        job.set("import.filename", args[0]);
        /**maponly作业需要显式设置reducer的数目为0。*/
        job.setNumReduceTasks(0);
        job.setMapOutputKeySchema(SchemaUtils.fromString("key:bigint"));
        job.setMapOutputValueSchema(SchemaUtils.fromString("value:string"));
        InputUtils.addTable(TableInfo.builder().tableName("mr_empty").build(), job);
        OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
        JobClient.runJob(job);
    }
}

您可以通过以下两种方式设置JobConf。

  • 通过SDK中JobConf的接口设置,本示例即是通过此方法实现。
  • 在Jar命令行中,通过–conf参数指定新的JobConf文件。