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  • hadoop mapreduce实现数据去重

    实现原理分析:

      map函数数将输入的文本按照行读取,   并将Key--每一行的内容   输出    value--空。

      reduce  会自动统计所有的key,我们让reduce输出key->输入的key    value->空,这样就利用reduce自动合并相同的key的原理实现了数据去重。

    源代码:

    package com.duking.hadoop;
    
    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.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;
    import org.apache.hadoop.util.GenericOptionsParser;
    
    public class Dedup {
    
    	// map将输入中的value复制到输出数据的key上,并直接输出
    
    	public static class Map extends Mapper<Object, Text, Text, Text> {
    
    		private static Text line = new Text();// 每行数据
    
    		// 实现map函数
    		public void map(Object key, Text value, Context context)
    
    		throws IOException, InterruptedException {
    
    			line = value;
    
    			context.write(line, new Text(""));
    		}
    	}
    
    	// reduce将输入中的key复制到输出数据的key上,并直接输出    这是数据区重的思想
    	public static class Reduce extends Reducer<Text, Text, Text, Text> {
    
    		// 实现reduce函数
    
    		public void reduce(Text key, Iterable<Text> values, Context context)
    
    		throws IOException, InterruptedException {
    
    			context.write(key, new Text(""));
    
    		}
    
    	}
    
    	public static void main(String[] args) throws Exception {
    
    		Configuration conf = new Configuration();
    
    		// 这句话很关键
    		conf.set("mapred.job.tracker", "192.168.60.129:9000");
    
    		//指定带运行参数的目录为输入输出目录
    		String[] otherArgs = new GenericOptionsParser(conf, args)
    		.getRemainingArgs();
    		
    		/*      指定工程下的input2为文件输入目录    output2为文件输出目录
    		String[] ioArgs = new String[] { "input2", "output2" };
    
    		String[] otherArgs = new GenericOptionsParser(conf, ioArgs)
    				.getRemainingArgs();*/
    
    		if (otherArgs.length != 2) {    //判断路径参数是否为2个
    
    			System.err.println("Usage: Data Deduplication <in> <out>");
    
    			System.exit(2);
    
    		}
    
    		//set maprduce job name
    		Job job = new Job(conf, "Data Deduplication");
    
    		job.setJarByClass(Dedup.class);
    
    		// 设置Map、Combine和Reduce处理类
    
    		job.setMapperClass(Map.class);
    
    		job.setCombinerClass(Reduce.class);
    
    		job.setReducerClass(Reduce.class);
    
    		// 设置输出类型
    
    		job.setOutputKeyClass(Text.class);
    
    		job.setOutputValueClass(Text.class);
    
    		// 设置输入和输出目录
    
    		FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
    
    		FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
    
    		System.exit(job.waitForCompletion(true) ? 0 : 1);
    
    	}
    
    }
    

      

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  • 原文地址:https://www.cnblogs.com/duking1991/p/6064625.html
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