Re: Additional Statistics Hooks

On Tue, Mar 13, 2018 at 4:14 AM, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> wrote:
> Mat Arye <mat(at)timescale(dot)com> writes:
>> So the use-case is an analytical query like
>
>> SELECT date_trunc('hour', time) AS MetricMinuteTs, AVG(value) as avg
>> FROM hyper
>> WHERE time >= '2001-01-04T00:00:00' AND time <= '2001-01-05T01:00:00'
>> GROUP BY MetricMinuteTs
>> ORDER BY MetricMinuteTs DESC;
>
>> Right now this query will choose a much-less-efficient GroupAggregate plan
>> instead of a HashAggregate. It will choose this because it thinks the
>> number of groups
>> produced here is 9,000,000 because that's the number of distinct time
>> values there are.
>> But, because date_trunc "buckets" the values there will be about 24 groups
>> (1 for each hour).
>
> While it would certainly be nice to have better behavior for that,
> "add a hook so users who can write C can fix it by hand" doesn't seem
> like a great solution. On top of the sheer difficulty of writing a
> hook function, you'd have the problem that no pre-written hook could
> know about all available functions. I think somehow we'd need a way
> to add per-function knowledge, perhaps roughly like the protransform
> feature.

Like cost associated with a function, we may associate mapping
cardinality with a function. It tells how many distinct input values
map to 1 output value. By input value, I mean input argument tuple. In
Mat's case the mapping cardinality will be 12. The number of distinct
values that function may output is estimated as number of estimated
rows / mapping cardinality of that function.

--
Best Wishes,
Ashutosh Bapat
EnterpriseDB Corporation
The Postgres Database Company