Tom Lane <tgl@xxxxxxxxxxxxx> wrote:
> Gavin Wahl wrote:
>> It seems trivial to accelerate a MAX or MIN query with a BRIN index. You
>> just find the page range with the largest/smallest value, and then only
>> scan that one. Would that be hard to implement? I'm interested in working
>> on it if someone can give me some pointers.
I think this proposal is fairly broken anyway. The page range with the
largest max-value may once have contained the largest live row, but
there's no guarantee that it still does. It might even be completely
empty. You could imagine an algorithm like this:
1. Find page-range with largest max. Scan it to identify live row with
largest value. If *no* live values, find page-range with next largest
max, repeat until no page ranges remain (whereupon return NULL).
2. For each remaining page-range whose indexed max exceeds the value
currently in hand, scan that page-range to see if any value exceeds
the one in hand, replacing the value if so.
This'd probably allow you to omit scanning some of the page-ranges
in the table, but in a lot of cases you'd end up scanning many of them;
and you'd need a lot of working state to remember which ranges you'd
already looked at. It'd certainly always be a lot more expensive than
answering the same question with a btree index, because in no case do
you get to avoid scanning the entire contents of the index.
regards, tom lane
Thanks Tom,
A b-tree index would certainly be faster for ordering. But in scenarios where you have huge datasets that can't afford the space or update time required for b-tree, could such a BRIN-accelerated ordering algorithm at least be faster than ordering with no index?
Darren Lafreniere
