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https://issues.apache.org/jira/browse/HBASE-9556?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15181788#comment-15181788
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beeshma commented on HBASE-9556:
--------------------------------
How about below logic to find start keys of regions?
HTable ht=new HTable(con,"test"); // Table object
NavigableMap<HRegionInfo,ServerName> np=ht.getRegionLocations();
Set<HRegionInfo> setinfo=np.keySet();
List<HRegionInfo> lis=new ArrayList<HRegionInfo>();
lis.addAll(setinfo);
for(org.apache.hadoop.hbase.HRegionInfo h :lis)
{
System.out.println(h.getRegionId() + "getRegionId");
String s = new String(h.getStartKey());
System.out.println(s.toString()+"-------start key");
}
Please suggest if anything wrong in this
> 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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