僞分佈模式hadoop運行java源程序

寫好源代碼以後，首先要編譯： javac -classpath /usr/local/hadoop/hadoop-core-1.2.1.jar:/usr/local/hadoop/lib/commons-cli-1.2.jar count.java -d org 在org目錄下生成三個class文件： count.class count\ Map.class count\ Reduce.class 以後將三個class文件打包： jar -cvf count.jar -C org/ . 以後在hadoop根目錄下生成count.jar文件 建立分佈式文件夾，並把要分析的數據放入之中： bin/hadoop fs -mkdir input bin/hadoop fs --put ~/Downloads/Gowalla_totalCheckins.txt input （~/Downloads/Gowalla_totalCheckins.txt爲我文件所在位置） 經過localhost:50070能夠查看： 能夠看到txt中的數據已經考到了input下。 接下來運行程序： bin/hadoop jar count.jar count input output 運行完以後會發現：生成一個output文件夾，其下有三個文件，輸出的信息保存在part-r-00000中 文件內容： 196514 2010-07-24T13:45:06Z 53.3648119 -2.2723465833 145064 196514 2010-07-24T13:44:58Z 53.360511233 -2.276369017 1275991 196514 2010-07-24T13:44:46Z 53.3653895945 -2.2754087046 376497 196514 2010-07-24T13:44:38Z 53.3663709833 -2.2700764333 98503 196514 2010-07-24T13:44:26Z 53.3674087524 -2.2783813477 1043431 196514 2010-07-24T13:44:08Z 53.3675663377 -2.278631763 881734 196514 2010-07-24T13:43:18Z 53.3679640626 -2.2792943689 207763 196514 2010-07-24T13:41:10Z 53.364905 -2.270824 1042822 其中第一列爲用戶iｄ ，第二列爲登陸時間，第三列是用戶的緯度，第四列我爲用戶的經度，第五列爲用戶的地址iｄ 文件源地址：http://snap.stanford.edu/data/loc-gowalla.html 本次程序是分析用戶的登陸時間，並分時間段進行統計。 源代碼：

<!-- lang: java -->
import java.io.IOException; 
import java.util.*; 
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 count { 
public static class Map extends Mapper<Object, Text, IntWritable, IntWritable> { 
    // 實現map函數 
    	public void map(Object key, Text value, Context context)throws IOException, InterruptedException { 
		String line = value.toString(); 
   			int k; 
		StringTokenizer itr = new StringTokenizer(line); 
		int i = 0; 
		int hour = 0,minute = 0,second = 0; 
    	    	while (itr.hasMoreTokens()) { 
			String token = itr.nextToken(); 
	                i++; 
			if(i == 2){ 
				int indexOfT = token.indexOf('T'); 
				int indexOfZ = token.indexOf('Z',indexOfT + 1); 
	        		String substr = token.substring(indexOfT + 1,indexOfZ); 
				int blank1 = substr.indexOf(':'); 
				int blank2 = substr.indexOf(':',blank1 + 1); 
				hour =  Integer.parseInt(substr.substring(0,blank1),10);  
				minute = Integer.parseInt(substr.substring(blank1 + 1,blank2),10); 
				second = Integer.parseInt(substr.substring(blank2 + 1),10); 
			} 
    	    	} 
    	        k = (hour * 60 * 60 + minute * 60 + second) / （3600  * 4） ; 
		context.write(new IntWritable( k ), new IntWritable(1)); 
    	} 
} 

public static class Reduce extends Reducer< IntWritable, IntWritable, IntWritable, IntWritable> { 
    	// 實現reduce函數 
	public void reduce(IntWritable key, Iterable<IntWritable> values, Context context) 
    		throws IOException, InterruptedException { 
		int sum = 0;			 
		for(IntWritable val : values){ 
			sum += val.get(); 
		} 
		context.write( key, new IntWritable(sum)); 
    	} 
}	 

public static void main(String[] args) throws Exception { 
	Configuration conf = new Configuration(); 
    	String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();    
	if (otherArgs.length != 2) { 
    		System.err.println("Usage: Multiple Table Join <in> <out>"); 
    	        System.exit(2); 
    	} 
    	Job job = new Job(conf, "count"); 
    	job.setJarByClass(count.class); 
    	// 設置Map和Reduce處理類 
    	job.setMapperClass(Map.class); 
	job.setCombinerClass(Reduce.class); 
    	job.setReducerClass(Reduce.class); 
    	// 設置輸出類型 
	job.setOutputKeyClass(IntWritable.class); 
    	job.setOutputValueClass(IntWritable.class); 
    	FileInputFormat.addInputPath(job, new Path(otherArgs[0])); 
    	FileOutputFormat.setOutputPath(job, new Path(otherArgs[1])); 
    	System.exit(job.waitForCompletion(true) ? 0 : 1); 
} 
   }