On Tue, Sep 13, 2016 at 4:06 PM, Robert Haas <robertmh...@gmail.com> wrote: > On Tue, Sep 13, 2016 at 2:59 PM, Claudio Freire <klaussfre...@gmail.com> > wrote: >> I've finished writing that patch, I'm in the process of testing its CPU >> impact. >> >> First test seemed to hint at a 40% increase in CPU usage, which seems >> rather steep compared to what I expected, so I'm trying to rule out >> some methodology error here. > > Hmm, wow. That's pretty steep. Maybe lazy_heap_reaptid() is hotter > than I think it is, but even if it accounts for 10% of total CPU usage > within a vacuum, which seems like an awful lot, you'd have to make it > 4x as expensive, which also seems like an awful lot.
IIRC perf top reported a combined 45% between layz_heap_reaptid + vac_cmp_itemptr (after patching). vac_cmp_itemptr was around 15% on its own Debug build of couse (I need the assertions and the debug symbols), I'll retest with optimizations once debug tests make sense. >>> For example, we could keep a bitmap with one bit per K >>> pages. If the bit is set, there is at least 1 dead tuple on that >>> page; if clear, there are none. When we see an index tuple, we >>> consult the bitmap to determine whether we need to search the TID >>> list. We select K to be the smallest power of 2 such that the bitmap >>> uses less memory than some threshold, perhaps 64kB. >> >> I've been pondering something like that, but that's an optimization >> that's quite orthogonal to the multiarray stuff. > > Sure, but if this really does increase CPU time, it'd be reasonable to > do something to decrease it again in order to get the other benefits > of this patch - i.e. increasing the maintenance_work_mem limit while > reducing the chances that overallocation will cause OOM. I was hoping it wouldn't regress performance so much. I'd rather micro-optimize the multiarray implementation until it doesn't and then think of orthogonal optimizations. >>> Assuming that >>> updates and deletes to the table have some locality, we should be able >>> to skip a large percentage of the TID searches with a probe into this >>> very compact bitmap. >> >> I don't think you can assume locality > > Really? If you have a 1TB table, how many 2MB ranges of that table do > you think will contain dead tuples for a typical vacuum? I think most > tables of that size are going to be mostly static, and the all-visible > and all-frozen bits are going to be mostly set. You *could* have > something like a pgbench-type workload that does scattered updates > across the entire table, but that's going to perform pretty poorly > because you'll constantly be updating blocks that have to be pulled in > from disk. I have a few dozen of those in my biggest database. They do updates and deletes all over the place and, even if they were few, they're scattered almost uniformly. Thing is, I think we really need to not worsen that case, which seems rather common (almost any OLTP with a big enough user base, or a K-V type of table, or TOAST tables). -- Sent via pgsql-hackers mailing list (firstname.lastname@example.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers