On Wed, Oct 5, 2016 at 3:27 PM, Stephen Frost <sfrost@xxxxxxxxxxx> wrote: > Darren, > > * Darren Lafreniere (dlafreniere@xxxxxxxxxxx) wrote: >> 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. > [...] >> 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? > > For at least some of the common BRIN use-cases, where the rows are > inserted in-order and never/very-rarely modified or deleted, this > approach would work very well. > > Certainly, using this would be much cheaper than a seqscan/top-N sort, > for small values of 'N', relative to the number of rows in the table, > in those cases. > > In general, I like the idea of supporting this as BRIN indexes strike me > as very good for very large tables which have highly clumped data in > them and being able to do a top-N query on those can be very useful at > times. Yeah. If the brin average page overlap and % dead tuple coefficients are low it absolutely makes sense to drive top N with brin. It will never beat a btree but typically brin is used when the btree index is no good for various reasons. brin indexes are pretty neat; they can provide stupefying amounts of optimization in many common warehousing workloads. They even beat out index only scans for a tiny fraction of the storage. Of course, you have to work around the limitations... :-) merlin -- Sent via pgsql-general mailing list (pgsql-general@xxxxxxxxxxxxxx) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-general
