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Hadoop / HBase hotspotting / overloading specific nodes

+4 votes
463 views

I am having a problem with Hadoop maxing out drive space on a select few nodes when I am running an HBase job. The scenario is this:

  • The job is a data import using Map/Reduce / HBase
  • The data is being imported to one table
  • The table only has a couple of regions
  • As the job runs, HBase? / Hadoop? begins placing the data in HDFS on the datanode / regionserver that is hosting the regions
  • As the job progresses (and more data is imported) the two datanodes hosting the regions start to get full and eventually drive space hits 100% utilization whilst the other nodes in the cluster are at 40% or less drive space utilization
  • The job in Hadoop then begins to hang with multiple "out of space" errors and eventually fails.

I have tried running hadoop balancer during the job run and this helped but only really succeeded in prolonging the eventual job failure.

How can I get Hadoop / HBase to distribute the data to HDFS more evenly when it is favoring the nodes that the regions are on?

Am I missing something here?

posted Oct 9, 2014 by anonymous

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can you set a reserved room for non-dfs usage? Just to avoid the disk gets full.
dfs.datanode.du.reserved
Reserved space in bytes per volume. Always leave this much space free for non dfs use.

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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?

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