On 1/5/12 1:19 AM, David Fetter wrote:
To achieve efficiency, the checkpoint writer and bgwriter should batch writes to multiple pages together. Currently, there is an option "batched_buffer_writes" that specifies how many buffers to batch at a time. However, we may want to remove that option from view, and just force batched_buffer_writes to a default (32) if double_writes is enabled.
The idea that PostgreSQL has better information about how to batch writes than the layers below it is controversial, and has failed to match expectations altogether for me in many cases. The nastiest regressions here I ran into were in VACUUM, where the ring buffer implementation means the database has extremely limited room to work. Just dumping the whole write mess of that into a large OS cache as quickly as possible, and letting it sort things out, was dramatically faster in some of my test cases. If you don't have one already, I'd recommend adding a performance test that dirties a lot of pages and then runs VACUUM against them to your test suite. Since you're not crippling the OS cache to the same extent I was the problem may not be so bad, but it's something worth checking.
I scribbled some notes on this problem area at http://blog.2ndquadrant.com/en/2011/01/tuning-linux-for-low-postgresq.html ; the links that are broken due to our web site being rearranged are now at http://highperfpostgres.com/pgbench-results/index.htm (test summary) and http://www.highperfpostgres.com/pgbench-results/435/index.html (Really bad latency spike example)
Given the batching functionality, double writes by the checkpoint writer (and bgwriter) is implemented efficiently by writing a batch of pages to the double-write file and fsyncing, and then writing the pages to the appropriate data files, and fsyncing all the necessary data files. While the data fsyncing might be viewed as expensive, it does help eliminate a lot of the fsync overhead at the end of checkpoints. FlushRelationBuffers() and FlushDatabaseBuffers() can be similarly batched.
There's a fundamental struggle here between latency and throughput. The longer you delay between writes and their subsequent sync, the more the OS gets a chance to reorder and combine them for better throughput. Ditto for any storage level optimizations, controller write caches and the like. All that increases throughput, and more batching helps move in that direction. But when you overload those caches and writes won't squeeze into them anymore...now there's a latency spike. And as throughput increases, with it goes the amount of dirty cache that needs to be cleared per unit of time.
Eventually, all this disk I/O turns into a series of random writes. You can postpone those in various ways, resequence them in ways that help some tests. But if they're the true bottleneck, eventually all caches will fill, and clients will be stuck waiting for them. And it's hard to imagine anything that causes the amount of data written to increase to ever move that problem in the right direction for the worst case. Adjusting the sync sequence just moves the problem to somewhere else. If you get lucky, that's a better place most of the time; how that bet turns out will be very workload dependent though. I've lost a lot of those bets when trying to resequence syncs in the last two years, where benefits were extremely test dependent.
We have some other code (not included) that sorts buffers to be checkpointed in file/block order -- this can reduce fsync overhead further by ensuring that each batch writes to only one or a few data files.
Again, the database doesn't necessarily have the information to make this level of decision better than the underlying layers do. We've been through two runs at this idea already that ended inconclusively. The one I did last year you can see at http://highperfpostgres.com/pgbench-results/index.htm ; set 9 and 11 are the same test without (9) and with (11) write sorting. If there's really a difference there, it's below the noise floor as far as I could see. Whether sorting helps or hurts is both workload and hardware dependent.
As Jignesh has mentioned on this list, we see significant performance gains when enabling double writes& disabling full_page_writes for OLTP runs with sufficient buffer cache size. We are now trying to measure some runs where the dirty buffer eviction rate by the backends is high.
We'd need to have positive results published along with a publicly reproducible benchmark to go at this usefully. I aimed for a much smaller goal than this in a similar area, around this same time last year. I didn't get very far down that path before 9.1 development closed; it just takes too long to run enough benchmarks to really validate performance code in the write path. This is a pretty obtrusive change to drop into the codebase for 9.2 at this point in the development cycle.
P.S. I got the impression you're testing these changes primarily against a modified 9.0. One of the things that came out of the 9.1 performance testing was the "compact fsync queue" modification. That significant improvement rippled out enough that several things that used to matter in my tests didn't anymore, once it was committed. If your baseline doesn't include that feature already, you may have an uphill battle to prove any performance gains you've been seeing will still happen in the current 9.2 code. Performance for that version has advanced even further forward in ways 9.0 can't emulate.
-- Greg Smith 2ndQuadrant US g...@2ndquadrant.com Baltimore, MD PostgreSQL Training, Services, and 24x7 Support www.2ndQuadrant.com -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
