Indeed! A big part of our implementation is based on the Neumann
paper. There are also a few other papers that impacted our
implemented:
A. Ailamaki, D. DeWitt, M. Hill, D. Wood. DBMSs On A Modern Processor:
Where Does Time Go?
Peter Boncz, Marcin Zukowski, Niels Nes. MonetDB/X100:
Hyper-Pipelining Query Execution
M. Zukowski el al. Super-Scalar RAM-CPU Cache Compression
Of course, we need to adapt a lot of the design to Postgres to make
something that could stand up harmoniously with the Postgres system,
and also to take care that we would be able to merge easily with
future versions of Postgres -- the implementation needs to be as
non-invasive as possible.
Regards,
-cktan
On Fri, Oct 17, 2014 at 8:40 PM, David Gould <daveg@sonic.net> wrote:
> On Fri, 17 Oct 2014 13:12:27 -0400
> Tom Lane <tgl@sss.pgh.pa.us> wrote:
>
>> CK Tan <cktan@vitessedata.com> writes:
>> > The bigint sum,avg,count case in the example you tried has some optimization. We use int128 to accumulate the
bigintinstead of numeric in pg. Hence the big speed up. Try the same query on int4 for the improvement where both pg
andvitessedb are using int4 in the execution.
>>
>> Well, that's pretty much cheating: it's too hard to disentangle what's
>> coming from JIT vs what's coming from using a different accumulator
>> datatype. If we wanted to depend on having int128 available we could
>> get that speedup with a couple hours' work.
>>
>> But what exactly are you "compiling" here? I trust not the actual data
>> accesses; that seems far too complicated to try to inline.
>>
>> regards, tom lane
>>
>>
>
> I don't have any inside knowledge, but from the presentation given at the
> recent SFPUG followed by a bit of google-fu I think these papers are
> relevant:
>
> http://www.vldb.org/pvldb/vol4/p539-neumann.pdf
> http://sites.computer.org/debull/A14mar/p3.pdf
>
> -dg
>
> --
> David Gould 510 282 0869 daveg@sonic.net
> If simplicity worked, the world would be overrun with insects.