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From "eric baldeschwieler (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-331) map outputs should be written to a single output file with an index
Date Tue, 17 Oct 2006 21:45:37 GMT
    [ http://issues.apache.org/jira/browse/HADOOP-331?page=comments#action_12443086 ] 
eric baldeschwieler commented on HADOOP-331:

Sounds good.  I think we are converging on something.

A couple of points:

1) When we spill, we don't need to keep any record of the spilled data.  Devaraj maintained
operating on these arrays after spills.  We should not do that.  Everything should be cleared
out.  (Except possibly the index of partitions to file offsets).

2) I like the idea of extending the block compressed sequence file to directly support flushes
at partition boundaries and merges of ranges.  This will be reused in reduce as doug observed.

3) We should not spill based on a number of records.  Don't see any value in that.  We should
just spill based on RAM used.

4) Related, we need to track total RAM used, not just for values, but also for keys and arrays.
 We don't want the system to blow up in the degenerate cases of huge keys or null values and
many, many keys.

> map outputs should be written to a single output file with an index
> -------------------------------------------------------------------
>                 Key: HADOOP-331
>                 URL: http://issues.apache.org/jira/browse/HADOOP-331
>             Project: Hadoop
>          Issue Type: Improvement
>          Components: mapred
>    Affects Versions: 0.3.2
>            Reporter: eric baldeschwieler
>         Assigned To: Devaraj Das
> The current strategy of writing a file per target map is consuming a lot of unused buffer
space (causing out of memory crashes) and puts a lot of burden on the FS (many opens, inodes
used, etc).  
> I propose that we write a single file containing all output and also write an index file
IDing which byte range in the file goes to each reduce.  This will remove the issue of buffer
waste, address scaling issues with number of open files and generally set us up better for
scaling.  It will also have advantages with very small inputs, since the buffer cache will
reduce the number of seeks needed and the data serving node can open a single file and just
keep it open rather than needing to do directory and open ops on every request.
> The only issue I see is that in cases where the task output is substantiallyu larger
than its input, we may need to spill multiple times.  In this case, we can do a merge after
all spills are complete (or during the final spill).

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