On Fri, Jan 23, 2026 at 10:45 PM Corey Huinker <corey.huinker@gmail.com> wrote:
>>
>> >> There's an advantage if we can combine stats across multiple relations
>> >> - we don't have to sample children twice when analyzing the parent
>> >> without ONLY. Instead we could produce parent statistics by combining
>> >> statistics across children and the parent. To me this looks like
>> >> altogether a different beast just like partial aggregates.
>> >
>> >
>> > I think this patch is only ever going to get us out of 1 of the 2 samples, which isn't ideal but it is a savings.
>> >
>>
>> I am not suggesting to synthesize sample rows. Calculate the
>> statistics of the parent table from that of its children.
>
>
> I'm not sure we can actually do that. The functions that compute the statistics are all based off of row samples, not
alreadycomputed statistics. I don't think we can synthesize a rowsample from the imported statistics, at least not
accurately.If I'm misunderstanding what you're suggesting, please correct me.
I am comparing the calculation of statistics to the calculation of
aggregates. We have code to compute aggregates on a partitioned table
from the partial aggregates computed from the individual partitions.
(Even though I am mentioning the partitioned table, the technique can
be used for an inheritance hierarchy.) Similarly if we could come up
with a representation of partial statistics, we could get partial
statistics computed for the children (and the parent in
non-partitioned inheritance). Use the partial statistics to compute
the statistics for the parent without the need to synthesize row
samples from the children. I haven't looked at all the kinds of
statistics to see whether this is feasible.
--
Best Wishes,
Ashutosh Bapat
