Thanks - Basically our IDS are just postfixed with UUIDs to get them unique -
we use a prefix to group data that is often read together - so this would be
a great performance improvement for us!



Ryan Rawson wrote:
> 
> hey,
> 
> there is no API calls right now, but no strong reasons why there could
> not be.  Not likely for 0.20.0, but maybe for .1, and more likely for
> 0.21.
> 
> Batching is only as effective as how clustered your keys on regions
> are for your calls.  If you are only seeing 1 key per region per
> batch, you aren't getting any efficiencies.  If you have a deeper
> density, yeah you are going to get better performance.
> 
> 
> On Thu, Jul 16, 2009 at 10:49 PM, Peter
> Rietzler<[email protected]> wrote:
>>
>> Hi
>>
>> First of all thanks for your great work! We are enjoying using HBase in
>> our
>> project :)
>>
>> One of our HBase tables uses UUIDs for keys. The character of the data is
>> random access and we are indexing the rows with an external indexer. The
>> access characteristic is much like you would do with a traditional SQL
>> statement - Issue a query to the index and then get all associated rows
>> using the list of returned ids (typically from a few 100 up to around
>> 100.000 rows ...). The same applies for deletion.
>>
>> While batch updating is available I miss an opportunity to batch fetch
>> and
>> batch delete rows by id. I currently use HTable.getRow() and
>> HTable.deleteAll() for these operations - however - both of the
>> operations
>> perform pretty poor for more than a couple of 100 rows (I guess it's
>> because
>> an IPC call needs to be send for each call...). Unfortunately scanning is
>> not an issue for this use case.
>>
>> Is it planned to provide batch random access batch fetches ? Something
>> like
>> HTable.getRows(list of ids) and HTable.deleteAll(list of ids) would be
>> perfect :)
>>
>> Cheers,
>> Peter
>>
>>
>> --
>> View this message in context:
>> http://www.nabble.com/Batched-Gets-and-Deletes-by-Id---Performance-Issues---tp24528949p24528949.html
>> Sent from the HBase User mailing list archive at Nabble.com.
>>
>>
> 
> 

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