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Explain about the partitioning, shuffle and sort phase in Hadoop?

+2 votes
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Explain about the partitioning, shuffle and sort phase in Hadoop?
posted Jun 30, 2017 by Karthick.c

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+3 votes

As I studied that data distribution, load balancing, fault tolerance are implicit in Hadoop. But I need to customize it, can we do that?

+1 vote

A mapreduce job can be run as jar file from terminal or directly from eclipse IDE. When a job run as jar file from terminal it uses multiple jvm and all resources of cluster. Does the same thing happen when we run from IDE. I have run a job on both and it takes less time on IDE than jar file on terminal.

+2 votes
public class MaxMinReducer extends Reducer {
int max_sum=0; 
int mean=0;
int count=0;
Text max_occured_key=new Text();
Text mean_key=new Text("Mean : ");
Text count_key=new Text("Count : ");
int min_sum=Integer.MAX_VALUE; 
Text min_occured_key=new Text();

 public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
       int sum = 0;           

       for (IntWritable value : values) {
             sum += value.get();
             count++;
       }

       if(sum < min_sum)
          {
              min_sum= sum;
              min_occured_key.set(key);        
          }     


       if(sum > max_sum) {
           max_sum = sum;
           max_occured_key.set(key);
       }          

       mean=max_sum+min_sum/count;
  }

 @Override
 protected void cleanup(Context context) throws IOException, InterruptedException {
       context.write(max_occured_key, new IntWritable(max_sum));   
       context.write(min_occured_key, new IntWritable(min_sum));   
       context.write(mean_key , new IntWritable(mean));   
       context.write(count_key , new IntWritable(count));   
 }
}

Here I am writing minimum,maximum and mean of wordcount.

My input file :

high low medium high low high low large small medium

Actual output is :

high - 3------maximum

low - 3--------maximum

large - 1------minimum

small - 1------minimum

but i am not getting above output ...can anyone please help me?

+2 votes

I declared a variable and incremented/modified it inside Mapper class. Now I need to use the modified value of that variable in Driver class. I declared a static variable inside Mapper class and its modified value works in Driver class when I run the code in Eclipse IDE. But after creating that code as a runable jar from Eclipse and run jar file as “$ hadoop jar filename.jar input output” modified value does not reflect (value is 0) in Driver class.

+2 votes

I need your help in writing the map reduce program in Java. I am creating a mapper and reducer classes for reading and processing a log file. I also have many other class files which acts as supporting classes to mapper and will be instantiated from mapper class within the map function.

PROBLEM STATEMENT :
Since there are 20 other objects which will be instantiated from mapper class within the map function, we think this could create a performance hit because of multiple object creation .

Please let us know what could be best approach/design to instantiate these 20 classes from Mapper class without compromising on the performance.

Your suggestions/comments are welcome.

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