On Tue, Feb 9, 2021 at 10:48 AM Bossart, Nathan <bossa...@amazon.com> wrote: > I'm hoping to gather some early feedback on a heap optimization I've > been working on. In short, I'm hoping to add "partial heap only > tuple" (PHOT) support, which would allow you to skip updating indexes > for unchanged columns even when other indexes require updates. Today, > HOT works wonders when no indexed columns are updated. However, as > soon as you touch one indexed column, you lose that optimization > entirely, as you must update every index on the table. The resulting > performance impact is a pain point for many of our (AWS's) enterprise > customers, so we'd like to lend a hand for some improvements in this > area. For workloads involving a lot of columns and a lot of indexes, > an optimization like PHOT can make a huge difference. I'm aware that > there was a previous attempt a few years ago to add a similar > optimization called WARM [0] [1]. However, I only noticed this > previous effort after coming up with the design for PHOT, so I ended > up taking a slightly different approach. I am also aware of a couple > of recent nbtree improvements that may mitigate some of the impact of > non-HOT updates [2] [3], but I am hoping that PHOT serves as a nice > complement to those. I've attached a very early proof-of-concept > patch with the design described below.
I would like to share some thoughts that I have about how I think about optimizations like PHOT, and how they might fit together with my own work -- particularly the nbtree bottom-up index deletion feature you referenced. My remarks could equally well apply to WARM. Ordinarily this is the kind of thing that would be too hand-wavey for the mailing list, but we don't have the luxury of in-person communication right now. Everybody tends to talk about HOT as if it works perfectly once you make some modest assumptions, such as "there are no long-running transactions", and "no UPDATEs will logically modify indexed columns". But I tend to doubt that that's truly the case -- I think that there are still pathological cases where HOT cannot keep the total table size stable in the long run due to subtle effects that eventually aggregate into significant issues, like heap fragmentation. Ask Jan Wieck about the stability of some of the TPC-C/BenchmarkSQL tables to get one example of this. There is no reason to believe that PHOT will help with that. Maybe that's okay, but I would think carefully about what that means if I were undertaking this work. Ensuring stability in the on-disk size of tables in cases where the size of the logical database is stable should be an important goal of a project like PHOT or HOT. If you want to get a better sense of how these inefficiencies might happen, I suggest looking into using recently added autovacuum logging to analyze how well HOT works today, using the technique that I go into here: https://postgr.es/m/cah2-wzkju+nibskzunbdpz6trse+aqvupae+xgm8zvob4wq...@mail.gmail.com Small inefficiencies in the on-disk structure have a tendency to aggregate over time, at least when there is no possible way to reverse them. The bottom-up index deletion stuff is very effective as a backstop against index bloat, because things are generally very non-linear. The cost of an unnecessary page split is very high, and permanent. But we can make it cheap to *try* to avoid that using fairly simple heuristics. We can be reasonably confident that we're about to split the page unnecessarily, and use cues that ramp up the number of heap page accesses as needed. We ramp up during a bottom-up index deletion, as we manage to free some index tuples as a result of previous heap page accesses. This works very well because we can intervene very selectively. We aren't interested in deleting index tuples unless and until we really have to, and in general there tends to be quite a bit of free space to temporarily store extra version duplicates -- that's what most index pages look like, even on the busiest of databases. It's possible for the bottom-up index deletion mechanism to be invoked very infrequently, and yet make a huge difference. And when it fails to free anything, it fails permanently for that particular leaf page (because it splits) -- so now we have lots of space for future index tuple insertions that cover the original page's key space. We won't thrash. My intuition is that similar principles can be applied inside heapam. Failing to fit related versions on a heap page (having managed to do so for hours or days before that point) is more or less the heap page equivalent of a leaf page split from version churn (this is the pathology that bottom-up index deletion targets). For example, we could have a fall back mode that compresses old versions that is used if and only if heap pruning was attempted but then failed. We should always try to avoid migrating to a new heap page, because that amounts to a permanent solution to a temporary problem. We should perhaps make the updater work to prove that that's truly necessary, rather than giving up immediately (i.e. assuming that it must be necessary at the first sign of trouble). We might have successfully fit the successor heap tuple version a million times before just by HOT pruning, and yet currently we give up just because it didn't work on the one millionth and first occasion -- don't you think that's kind of silly? We may be able to afford having a fallback strategy that is relatively expensive, provided it is rarely used. And it might be very effective in the aggregate, despite being rarely used -- it might provide us just what we were missing before. Just try harder when you run into a problem every once in a blue moon! A diversity of strategies with fallback behavior is sometimes the best strategy. Don't underestimate the contribution of rare and seemingly insignificant adverse events. Consider the lifecycle of the data over time. If we quit trying to fit new versions on the same heap page at the first sign of real trouble, then it's only a matter of time until widespread heap fragmentation results -- each heap page only has to be unlucky once, and in the long run it's inevitable that they all will. We could probably do better at nipping it in the bud at the level of individual heap pages and opportunistic prune operations. I'm sure that it would be useful to not have to rely on bottom-up index deletion in more cases -- I think that the idea of "a better HOT" might still be very helpful. Bottom-up index deletion is only supposed to be a backstop against pathological behavior (version churn page splits), which is probably always going to be possible with a sufficiently extreme workload. I don't believe that the current levels of version churn/write amplification that we still see with Postgres must be addressed through totally eliminating multiple versions of the same logical row that live together in the same heap page. This idea is a false dichotomy. And it fails to acknowledge how the current design often works very well. When and how it fails to work well with a real workload and real tuning (especially heap fill factor tuning) is probably not well understood. Why not start with that? Our default heap fill factor is 100. Maybe that's the right decision, but it significantly impedes the ability of HOT to keep the size of tables stable over time. Just because heap fill factor 90 also has issues today doesn't mean that each pathological behavior cannot be fixed through targeted intervention. Maybe the myth that HOT works perfectly once you make some modest assumptions could come true. -- Peter Geoghegan
