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distcp takes lots of time to finish between 2 MapReduces

+1 vote

When I am trying to distcp between 2 MapReduces, the job remains lots of time in this position, and eventually it ends successfully. In other words, the job is quick to reach this position, and then it gets stuck in here for lots of time.

I would like to understand why it takes so much time for distcp job finish properly. How can I see what is going on?

posted May 11, 2015 by Ramakrishnan

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+3 votes

Date date; long start, end; // for recording start and end time of job
date = new Date(); start = date.getTime(); // starting timer


date = new Date(); end = date.getTime(); //end timer"Total Time (in milliseconds) = "+ (end-start));"Total Time (in seconds) = "+ (end-start)*0.001F);

I am not sure this is the correct way to find. Is there any other method or API to find the execution time of a MapReduce job?

+1 vote

I keep encountering an error when running nutch on hadoop YARN:

AttemptID:attempt_1423062241884_9970_m_000009_0 Timed out after 600 secs

Some info on my setup. I'm running a 64 nodes cluster with hadoop 2.4.1. Each node has 4 cores, 1 disk and 24Gb of RAM, and the namenode/resourcemanager has the same specs only with 8 cores.

I am pretty sure one of these parameters is to the threshold I'm hitting: 

but I would like to understand why.

The issue usually appears under heavier load, and most of the time the on the next attempts it is successful. Also if I restart the Hadoop cluster the error goes away for some time.

+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();

       if(sum < min_sum)
              min_sum= sum;

       if(sum > max_sum) {
           max_sum = sum;


 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

Let we change the default block size to 32 MB and replication factor to 1. Let Hadoop cluster consists of 4 DNs. Let input data size is 192 MB. Now I want to place data on DNs as following. DN1 and DN2 contain 2 blocks (32+32 = 64 MB) each and DN3 and DN4 contain 1 block (32 MB) each. Can it be possible? How to accomplish it?

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