mapreduce与spark的效率对比

最新推荐文章于 2025-02-16 21:41:21 发布

转载最新推荐文章于 2025-02-16 21:41:21 发布 · 294 阅读

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原文链接：https://my.oschina.net/u/4010291/blog/3009546

文章标签：

#大数据 #java

本文介绍了一种使用MapReduce编程模型来模仿Hive的rank功能的方法，具体实现了选择每个customer_id对应的首次分配id的功能。通过自定义Mapper和Reducer类，文章详细展示了如何解析输入数据、处理业务逻辑以及配置并运行MapReduce作业。

数据文件格式

根据上述数据文件编写的mapreduce代码

package first.first_maven;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
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.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/*
 * 模仿hive的rank功能，选择第一个
 */

public class AllocateLog {
	public static class MyMapper extends Mapper<LongWritable, Text, IntWritable, IntWritable>{
		

		@Override
		protected void map(LongWritable key, Text value, Context context)
				throws IOException, InterruptedException {

			String words[]=value.toString().split(",");
			// 获取customer_id和分配的id
			context.write(new IntWritable(Integer.parseInt(words[2])), new IntWritable(Integer.parseInt(words[0])));
			
		}
		
	}

	
	public static class MyReducer extends Reducer<IntWritable, IntWritable, IntWritable, IntWritable>{
		
		@Override
		protected void reduce(IntWritable key, Iterable<IntWritable> value,Context context)
				throws IOException, InterruptedException {
			     //选取每个customer_id的首次分配id
			    int tmp=99999999;
			    for(IntWritable v:value){
			    	if(tmp>v.get()){
			    		tmp=v.get();
			    	}
			    }
			    
			    context.write(key, new IntWritable(tmp));
		}

	}
	
	
	public static void main(String[] args) throws Exception {
        Configuration conf=new Configuration();
        Job job = Job.getInstance(conf, "myjob");
        job.setJarByClass(WordCount.class);

        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(IntWritable.class);
        job.setMapOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job,new Path(args[0]));

        
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(IntWritable.class);
        job.setOutputValueClass(IntWritable.class);
        FileOutputFormat.setOutputPath(job,new Path(args[1]));

        int isok=job.waitForCompletion(true)?0:1;

        System.exit(isok);
        }

}

转载于:https://my.oschina.net/u/4010291/blog/3009546