本文介绍了不使用 JobConf 运行 Hadoop 作业的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我找不到提交不使用已弃用 JobConf 类的 Hadoop 作业的单个示例.尚未弃用的 JobClient 仍然只支持采用 JobConf 参数的方法.

I can't find a single example of submitting a Hadoop job that does not use the deprecated JobConf class. JobClient, which hasn't been deprecated, still only supports methods that take a JobConf parameter.

谁能指出一个 Java 代码示例,该示例仅使用 Configuration 类(不是 JobConf)提交 Hadoop 映射/减少作业,并使用 mapreduce.lib.input 包而不是 mapred.input?

Can someone please point me at an example of Java code submitting a Hadoop map/reduce job using only the Configuration class (not JobConf), and using the mapreduce.lib.input package instead of mapred.input?

推荐答案

希望对你有帮助

import java.io.File;

import org.apache.commons.io.FileUtils;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class MapReduceExample extends Configured implements Tool {

    static class MyMapper extends Mapper<LongWritable, Text, LongWritable, Text> {
        public MyMapper(){

        }

        protected void map(
                LongWritable key,
                Text value,
                org.apache.hadoop.mapreduce.Mapper<LongWritable, Text, LongWritable, Text>.Context context)
                throws java.io.IOException, InterruptedException {
            context.getCounter("mygroup", "jeff").increment(1);
            context.write(key, value);
        };
    }

    @Override
    public int run(String[] args) throws Exception {
        Job job = new Job();
        job.setMapperClass(MyMapper.class);
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        job.waitForCompletion(true);
        return 0;
    }

    public static void main(String[] args) throws Exception {
        FileUtils.deleteDirectory(new File("data/output"));
        args = new String[] { "data/input", "data/output" };
        ToolRunner.run(new MapReduceExample(), args);
    }
}

这篇关于不使用 JobConf 运行 Hadoop 作业的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

08-24 04:33