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Re: Approximate query processing in Calcite


Hi Michael,

AQP is valuable in our business scenarios. Often time our data scientist would issue exploratory queries to get a basic sense of the data (means, aggregation on certain groupings, etc). But from my understanding, Verdict DB is independent to the database system and the query planner/optimizer. I wonder what you want to achieve specifically through Calcite integration?


> On May 7, 2018, at 10:05 AM, Michael Mior <mmior@xxxxxxxxxxxx> wrote:
> 
> Edmon (and others),
> 
> I'd be curious to hear more about your specific use cases if you're able to
> share. Especially those who have companies which may benefit from using AQP
> with Calcite to lower costs.
> 
> --
> Michael Mior
> mmior@xxxxxxxxxxxx
> 
> 
> Le jeu. 3 mai 2018 à 18:58, Edmon Begoli <ebegoli@xxxxxxxxx> a écrit :
> 
>> I am excited that you are considering taking Calcite in this direction.
>> 
>> Approximate querying and probabilistic databases are of great interest to
>> me, and I might be able to provide some applied research scenarios.
>> 
>> One domain that comes to mind where we had some use cases is a sensor data
>> analysis.
>> 
>> Thank you,
>> Edmon
>> 
>> On Thu, May 3, 2018 at 6:54 PM, Michael Mior <mmior@xxxxxxxxxxxx> wrote:
>> 
>>> Hi all,
>>> 
>>> I recently had a chat with the VerdictDB (http://verdictdb.org/) team
>>> about
>>> possible integration with Calcite. VerdictDB sits between an application
>>> and a database to enable the approximation of query results which are
>>> expected to be highly accurate while consuming significantly fewer
>>> resources on the backend.
>>> 
>>> I'm curious to talk to anyone who might have a use case for this.
>>> Particularly those using Calcite to power analytics systems that can
>>> tolerate approximate results. We'll likely be looking at putting
>> together a
>>> proof of concept in the next few weeks if there's any interest. Let me
>>> know!
>>> 
>>> --
>>> Michael Mior
>>> mmior@xxxxxxxxxxxx
>>> 
>>