[jira] [Comment Edited] (HBASE-9556) Provide key range support to bulkload to avoid too many reducers even the data belongs to few regions

["rajeshbabu (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HBASE-9556?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13769676#comment-13769676 ] 

rajeshbabu edited comment on HBASE-9556 at 9/17/13 5:29 PM:
------------------------------------------------------------

Yes Nick, while configuring job setting the regions count as number of reducers and regions start keys as partition points. If user known the range beforehand then we can identify the proper split points within the range and reduce number of reducers.
{code}
    List<ImmutableBytesWritable> startKeys = getRegionStartKeys(table);
    LOG.info("Configuring " + startKeys.size() + " reduce partitions " +
        "to match current region count");
    job.setNumReduceTasks(startKeys.size());

    configurePartitioner(job, startKeys);
{code}
                
      was (Author: rajesh23):
    if user not specify the start and/or end key range then we are setting the regions count as number of reducers and regions start keys as split points. If user known the range beforehand then we can identify the proper split points within the range and reduce number of reducers.
{code}
    List<ImmutableBytesWritable> startKeys = getRegionStartKeys(table);
    LOG.info("Configuring " + startKeys.size() + " reduce partitions " +
        "to match current region count");
    job.setNumReduceTasks(startKeys.size());

    configurePartitioner(job, startKeys);
{code}
                  
> Provide key range support to bulkload to avoid too many reducers even the data belongs to few regions
> -----------------------------------------------------------------------------------------------------
>
>                 Key: HBASE-9556
>                 URL: https://issues.apache.org/jira/browse/HBASE-9556
>             Project: HBase
>          Issue Type: Improvement
>          Components: mapreduce
>            Reporter: rajeshbabu
>            Assignee: rajeshbabu
>            Priority: Minor
>
> Presently the number of reducers in bulk load are equal to number of regions.
> Lets suppose a table has 500 regions and import data only belongs 10 regions, still we are starting 500(equal to no. of regions) reducers instead of 10. Which will consume more time and resources. 
> If user knows the row key range of import data, then we can pass startkey and/or endkey as input and based on the key range we can define the partitions and number of reducers(regions to which the data belongs). This helps to avoid too many reducers to start and do nothing and also avoids contention in shuffling.

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