On Mon, 2018-06-11 at 11:55 -0400, Robert Haas wrote:
> performance degradation is not necessarily much better than OOM. I
> suspect that part of the reason why both Andres and David proposed
> algorithms that combined hashing and sorting is out of a desire to
> cater somewhat to both few-tuples-per-group and many-tuples-per-
> group.
>
I think average group size is the wrong way to look at it, because
averages are only useful for a normal distribution. The two most
interesting cases are:
1. Fairly uniform group size (e.g. normal dist)
2. Skew values, power law distribution, etc., where some groups are
very large and most are tiny by comparison. I am calling the very large
groups "skewed groups".
For #1, hashing and sorting are both reasonable, and it depends on a
lot of factors (number of groups, clustering, available memory).
For #2, hashing is really good and sorting is really bad. That's
because (at present) we sort all of the tuples before doing any
aggregation, so it expends a lot of effort on the skewed groups.
Hashing can keep skewed groups in memory and avoid spilling a large
fraction of the input tuples at all.
If we get the skewed groups into the hash table, and avoid OOM, I think
that is a success. My patch did that, except it didn't account for two
cases:
(a) clustered input, where skewed groups may not appear until the
hash table is already full; and
(b) variable-sized transition values that grow with the group size
> One big advantage to just partitioning the input tuples by hash code
> and then proceeding batch by batch is that it works for any aggregate
> that can support hash aggregation in the first place. You do not
Agreed, but I think we should evaluate Andres's idea of feeding spilled
tuples to a Sort, because the overall complexity might be lower even
accounting for the special cases you're worried about.
Also, I am not sure we should really be designing around data types
where it makes sense to group and then don't supply a btree opclass.
Seems like they are likely to hit a problem soon anyway.
Regards,
Jeff Davis