Re: [PERFORM] Shared memory for large PostGIS operations
Hi Kevin, List, others... On Mar 16, 2012, at 7:17 AM, Kevin Grittner wrote: Andy Colson a...@squeakycode.net wrote: I tried shared_buffers at both 2400M and 18000M, and it took 4.5 hours both times. ... (weak attempts at humor omitted) All else being the same, adjusting shared_buffers affects how much of your cache is managed by PostgreSQL and how much of your cache is managed by the OS; it doesn't exactly change how much you have cached or necessarily affect disk waits. (There's a lot more that can be said about the fine points of this, but you don't seem to have sorted out the big picture yet.) Linux caching is aggressive already.. so I think this example points out that Postgres caching is not contributing here.. thats why I posted this short example to this list.. I thought ti was a useful data point.. that it might be useful to others... and to the PostgreSQL project devs... I heard of this program called vmstat that I'll read up on and post some results for. -ignore- I dont take advice with vinegar well... That's a good way to get a handle on whether your bottleneck is currently CPU or disk access. (attempted insults omitted) If you're looking to make things faster (a fact not yet exactly in evidence), you might want to start with the query which runs the longest, or perhaps the one which most surprises you with its run time, and get the EXPLAIN ANALYZE output for that query. There is other information you should include; this page should help: http://wiki.postgresql.org/wiki/SlowQueryQuestions some of the queries have been gone over fairly well, other not.. Its a complex sequence and we are in production mode here, so I dont get a chance to do everything I might do with regard to one particular query... I just learned about http://explain.depesz.com/ and figure it might help me. It is a nice way to present EXPLAIN ANALYZE output from complex queries. explain.depesz.com definitely a good reference, thank you for that.. == Brian Hamlin GeoCal OSGeo California Chapter 415-717-4462 cell -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Shared memory for large PostGIS operations
On 03/16/2012 05:30 PM, Kevin Grittner wrote: Brian Hamlinmapl...@light42.com wrote: On Mar 16, 2012, at 7:17 AM, Kevin Grittner wrote: Andy Colsona...@squeakycode.net wrote: I tried shared_buffers at both 2400M and 18000M, and it took 4.5 hours both times. ... (weak attempts at humor omitted) Ah, I didn't pick up on the attempts at humor; perhaps that's why you mistook something I said as an attempt at an insult. It wasn't you Kevin, it was me that insulted him. (Although I was trying to be funny, and not mean). Sorry again Brian. -Andy -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Shared memory for large PostGIS operations
Andy Colson wrote: On 03/16/2012 05:30 PM, Kevin Grittner wrote: Ah, I didn't pick up on the attempts at humor; perhaps that's why you mistook something I said as an attempt at an insult. It wasn't you Kevin, it was me that insulted him. (Although I was trying to be funny, and not mean). Adding to the confusion, I think I missed one of the emails/posts. Oh, well, it sounds like mostly people need to use more smiley-faces, since humor can be so easy to miss in this medium. Brian, I hope this doesn't put you off from posting -- we try to be helpful here. -Kevin -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
[PERFORM] Shared memory for large PostGIS operations
(from #postgresql IRC on freenode) darkblue_b I did an interesting experiment the other day davidfetter_vmw .. davidfetter_vmw do tell darkblue_b well you know I do these huge monolithic postGIS queries on an otherwise idle linux machine.. and there was a persistant thought in my head that Postgresql+PostGIS did not make good use of memory allocation 2G darkblue_b so I had this long, python driven analysis.. 15 steps.. some, unusual for me, are multiple queries running at once on the same data ... and others are just one labor intensive thing then the next (one result table is 1.8M rows for 745M on disk, others are smaller) darkblue_b I finally got the kinks worked out.. so I ran it twice.. 4.5 hours on our hardware.. once with shared_buffers set to 2400M and the second time with shared_buffers set to 18000M darkblue_b work_mem was unchanged at 640M and.. the run times were within seconds of each other.. no improvement, no penalty darkblue_b I have been wondering about this for the last two years davidfetter_vmw darkblue_b, have you gone over any of this on -performance or -hackers? darkblue_b no - though I think I should start a blog .. I have a couple of things like this now darkblue_b good story though eh ? davidfetter_vmw darkblue_b, um, it's a story that hasn't really gotten started until you've gotten some feedback from -performance darkblue_b ok - true... darkblue_b pg 9.1 PostGIS 1.5.3 Ubuntu Server Oneiric 64bit Dual Xeons one Western Digital black label for pg_default; one 3-disk RAID 5 for the database tablespace == Brian Hamlin GeoCal OSGeo California Chapter 415-717-4462 cell -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Shared memory for large PostGIS operations
So let me clean that up for you: On 3/14/2012 11:29 PM, mapl...@light42.com wrote: Hello list, my name is Brian Hamlin, but I prefer to go by darkblue, its mysterious and dangerous! I run PG 9.1, PostGIS 1.5.3, Linux 64 on Dual Xeons, OS on a single drive, and db is on 3-disk raid 5. I'm the only user. work_mem = 640M I do these huge monolithic postGIS queries on an otherwise idle linux machine. python driven analysis.. 15 steps.. some, unusual for me, are multiple queries running at once on the same data ... and others are just one labor intensive thing then the next (one result table is 1.8M rows for 745M on disk, others are smaller) I tried shared_buffers at both 2400M and 18000M, and it took 4.5 hours both times. I dont know if I am CPU bound or IO bound, but since giving PG more ram didnt help much, I'll assume I'm CPU bound. I heard of this program called vmstat that I'll read up on and post some results for. I don't know how much memory my box has, and I've never run explain analyze, but I'll try it out and post some. I just learned about http://explain.depesz.com/ and figure it might help me. This is the best list ever! Thanks all! (especially that poetic Dave Fetter, and that somewhat mean, but helpful, Andy Colson) Shout outs to my friends Garlynn, Nick and Rush (best band ever!). Party, my house, next week! == (Virtually) Brian Hamlin GeoCal OSGeo California Chapter 415-717-4462 cell -Andy -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Shared memory for large PostGIS operations
Andy Colson a...@squeakycode.net wrote: I tried shared_buffers at both 2400M and 18000M, and it took 4.5 hours both times. I dont know if I am CPU bound or IO bound, but since giving PG more ram didnt help much, I'll assume I'm CPU bound. All else being the same, adjusting shared_buffers affects how much of your cache is managed by PostgreSQL and how much of your cache is managed by the OS; it doesn't exactly change how much you have cached or necessarily affect disk waits. (There's a lot more that can be said about the fine points of this, but you don't seem to have sorted out the big picture yet.) I heard of this program called vmstat that I'll read up on and post some results for. That's a good way to get a handle on whether your bottleneck is currently CPU or disk access. I don't know how much memory my box has That's pretty basic information when it comes to tuning. What does `free -m` show? (Copy/paste is a good thing.) and I've never run explain analyze If you're looking to make things faster (a fact not yet exactly in evidence), you might want to start with the query which runs the longest, or perhaps the one which most surprises you with its run time, and get the EXPLAIN ANALYZE output for that query. There is other information you should include; this page should help: http://wiki.postgresql.org/wiki/SlowQueryQuestions I just learned about http://explain.depesz.com/ and figure it might help me. It is a nice way to present EXPLAIN ANALYZE output from complex queries. -Kevin -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Shared memory for large PostGIS operations
Brian Hamlin mapl...@light42.com wrote: On Mar 16, 2012, at 7:17 AM, Kevin Grittner wrote: Andy Colson a...@squeakycode.net wrote: I tried shared_buffers at both 2400M and 18000M, and it took 4.5 hours both times. ... (weak attempts at humor omitted) Ah, I didn't pick up on the attempts at humor; perhaps that's why you mistook something I said as an attempt at an insult. We get posts here from people at all different levels of experience, and many people are grateful for pointers on what various utilities can do for them or how best to formulate a post so they can get help when they need it. Attempts to help don't constitute insults, even if the need is feigned. All else being the same, adjusting shared_buffers affects how much of your cache is managed by PostgreSQL and how much of your cache is managed by the OS; it doesn't exactly change how much you have cached or necessarily affect disk waits. Linux caching is aggressive already.. so I think this example points out that Postgres caching is not contributing here.. thats why I posted this short example to this list.. I thought ti was a useful data point.. that it might be useful to others... and to the PostgreSQL project devs... Yeah, guidelines for shared_buffers in the docs are vague because the best setting varies so much with the workload. While the docs hint at setting it at 25% of the computer's RAM, most benchmarks posted on this list have found throughput to peak at around 8GB to 10GB on system where 25% would be more than that. (Far less on Windows, as the docs mention.) There can be a point well before that where there are latency spikes. In our shop we have a multi-TB database backing a web site, and to prevent these latency spikes we keep shared_buffers down to 2GB even though the system has 128GB RAM. Forcing dirty pages out to the OS cache helps them to be written in a more timely manner by code which knows something about the hardware and what order of writes will be most efficient. PostgreSQL has, as a matter of a design choice, decided to leave a lot to the OS caching, file systems, and device drivers, and a key part of tuning is to discover what balance of that versus the DBMS caching performs best for your workload. some of the queries have been gone over fairly well, other not.. Its a complex sequence and we are in production mode here, so I dont get a chance to do everything I might do with regard to one particular query... You may want to take a look at auto_explain: http://www.postgresql.org/docs/current/interactive/auto-explain.html Since you're already in production it may be hard to test the performance of your disk system, but it's a pretty safe bet that if you are at all disk-bound you would benefit greatly from adding one more drive and converting your 3 drive RAID 5 to a 4 drive RAID 10, preferably with a RAID controller with BBU cache configured for write-back. -Kevin -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
