Hadoop Yarn Container Does Not Allocate Enough Space

Question

I\'m running a Hadoop job, and in my yarn-site.xml file, I have the following configuration:

    
            yarn.scheduler.mini         


        

Answer 1

If any of the above configurations didn't help. If the issue is related to mapper memory, couple of things I would like to suggest that needs to be checked are.

• Check if combiner is enabled or not? If yes, then it means that reduce logic has to be run on all the records (output of mapper). This happens in memory. Based on your application you need to check if enabling combiner helps or not. Trade off is between the network transfer bytes and time taken/memory/CPU for the reduce logic on 'X' number of records.
  • If you feel that combiner is not much of value, just disable it.
  • If you need combiner and 'X' is a huge number (say millions of records) then considering changing your split logic (For default input formats use less block size, normally 1 block size = 1 split) to map less number of records to a single mapper.
• Number of records getting processed in a single mapper. Remember that all these records need to be sorted in memory (output of mapper is sorted). Consider setting mapreduce.task.io.sort.mb (default is 200MB) to a higher value if needed. mapred-configs.xml
• If any of the above didn't help, try to run the mapper logic as a standalone application and profile the application using a Profiler (like JProfiler) and see where the memory getting used. This can give you very good insights.