Moving from NUMERIC to FLOAT(8) did indeed lower query times by about
20%.
I will try fixeddecimal and agg() as time permits.
On 25 Jan 2016, at 4:44, David Rowley wrote:
> On 25 January 2016 at 15:45, Matt <bsg075@gmail.com> wrote:
>> I have a warehousing case where data is bucketed by a key of an
>> hourly
>> timestamp and 3 other columns. In addition there are 32 numeric
>> columns. The
>> tables are partitioned on regular date ranges, and aggregated to the
>> lowest
>> resolution usable.
>>
>> The principal use case is to select over a range of dates or hours,
>> filter
>> by the other key columns, and SUM() all 32 of the other columns. The
>> execution plan shows the primary key index limits row selection
>> efficiently,
>> but the query appears CPU bound in performing all of those 32 SUM()
>> aggregates.
>>
>
> SUM(numeric) also has to work quite a bit harder than an an aggregate
> like sum(float8) too since the addition in numeric is implemented in
> software.
> It depends on the use case, but for some cases the float4 or float8
> types might be an option and it will offer much faster aggregation.
> There is also https://github.com/2ndQuadrant/fixeddecimal which may be
> of some use if you need fixed precision up to a predefined scale. We
> found that using fixeddecimal instead of numeric for the TPC-H
> benchmark improved performance of query 1 significantly.
>
> --
> David Rowley http://www.2ndQuadrant.com/
> PostgreSQL Development, 24x7 Support, Training & Services
