Once it is ready, I'd like to replace our traditional SQL servers with Drill.
Our use case is realtime statistical analytics (Average, standard deviation,
sum, etc.) on user specified groups of data.
Our traditional SQL solution works okay up to about 300k rows but starts to
become slow (> 3 seconds) beyond that. We've worked around it by having
multiple SQL servers and sending the queries to them asynchronously, collecting
the varied responses and then returning the results. We need to be able to
handle 12 million rows, still hopefully in a real-time manner. In addition, the
drill approach would shift the complexity from the sharding data.
I've attached a sample query as an attachment.
-Shawn
On Dec 6, 2012, at 10:36 AM, Jacques Nadeau <[email protected]> wrote:
>
> While comments like "Faster Hive" or "more compliant SQL" are useful, it
> would be more helpful if you spent more time describing the particular data
> flows that you run today (including data sources), what your pain points
> are and things that you can't do today but would like to do.
