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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (ACCUMULO-3602) BatchScanner optimization for AccumuloInputFormat
Date Wed, 08 Apr 2015 21:13:12 GMT

    [ https://issues.apache.org/jira/browse/ACCUMULO-3602?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14486053#comment-14486053
] 

ASF GitHub Bot commented on ACCUMULO-3602:
------------------------------------------

Github user keith-turner commented on the pull request:

    https://github.com/apache/accumulo/pull/25#issuecomment-91038638
  
    > Agreed, but is this a new issue?
    
    I think the intent of this PR is new.  I think the intent is to efficiently support a
map reduce job that reads from many small ranges.  If we are going to do that, then lets do
it in a way that scales better.     
    
    > However, I still think that for many things, it's probably better to simply use an
iterator with some filter criteria.
    
    This approach would work well for existing input format.  The only drawback to this approach
is it requires adding custom iterators to tservers classpaths.   The batch scanner approach
allows efficient reads of many small ranges from a tablet w/o custom iterators.  Just need
a custom function in the map reduce job to generate the ranges.


> BatchScanner optimization for AccumuloInputFormat
> -------------------------------------------------
>
>                 Key: ACCUMULO-3602
>                 URL: https://issues.apache.org/jira/browse/ACCUMULO-3602
>             Project: Accumulo
>          Issue Type: Improvement
>          Components: client
>    Affects Versions: 1.6.1, 1.6.2
>            Reporter: Eugene Cheipesh
>            Assignee: Eugene Cheipesh
>              Labels: performance
>             Fix For: 1.7.0
>
>
> Currently {{AccumuloInputFormat}} produces a split for reach {{Range}} specified in the
configuration. Some table indexing schemes, for instance z-order geospacial index, produce
large number of small ranges resulting in large number of splits. This is specifically a concern
when using {{AccumuloInputFormat}} as a source for Spark RDD where each Split is mapped to
an RDD partition.
> Large number of small RDD partitions leads to poor parallism on read and high overhead
on processing. A desirable alternative is to group ranges by tablet into a single split and
use {{BatchScanner}} to produce the records. Grouping by tablets is useful because it represents
Accumulos attempt to distributed stored records and can be influance by the user through table
splits.
> The grouping functionality already exists in the internal {{TabletLocator}} class. 
> Current proposal is to modify {{AbstractInputFormat}} such that it generates either {{RangeInputSplit}}
or {{MultiRangeInputSplit}} based on a new setting in {{InputConfigurator}}.  {{AccumuloInputFormat}}
would then be able to inspect the type of the split and instantiate an appropriate reader.
> The functinality of {{TabletLocator}} should be exposed as a public API in 1.7 as it
is useful for optimizations.



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