Обсуждение: Debugging shared memory issues on CentOS
I am trying to debug some shared memory issues with Postgres 9.3.1 and CentOS release 6.3 (Final). I have a database machine that probably has some misconfigured shared memory settings. It's getting into 2+ GB of swap. Restarting postgres frees all of the memory, but after a few hours of normal usage it will go back into swap. During light usage, postgres will *very* slowly release some memory, but not all. Using top, I can see that many of the postgres connections are using shared memory:
```
top - 09:38:16 up 1 day, 21:21, 3 users, load average: 0.40, 0.54, 0.45
Tasks: 253 total, 2 running, 251 sleeping, 0 stopped, 0 zombie
Cpu(s): 0.7%us, 0.2%sy, 0.0%ni, 97.8%id, 1.2%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 6998260k total, 6849048k used, 149212k free, 248k buffers
Swap: 440478516k total, 1981912k used, 438496604k free, 1541356k cached
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
3534 postgres 20 0 2330m 1.4g 1.1g S 0.0 20.4 1:06.99 postgres: deploy mtalcott 10.222.154.172(53495) idle
9143 postgres 20 0 2221m 1.1g 983m S 0.0 16.9 0:14.75 postgres: deploy mtalcott 10.222.154.167(35811) idle
6026 postgres 20 0 2341m 1.1g 864m S 0.0 16.4 0:46.56 postgres: deploy mtalcott 10.222.154.167(37110) idle
18538 postgres 20 0 2327m 1.1g 865m S 0.0 16.1 2:06.59 postgres: deploy mtalcott 10.222.154.172(47796) idle
1575 postgres 20 0 2358m 1.1g 858m S 0.0 15.9 1:41.76 postgres: deploy mtalcott 10.222.154.172(52560) idle
```
There are about 29 total idle connections. `sudo ipcs -m` only shows:
```
top - 09:38:16 up 1 day, 21:21, 3 users, load average: 0.40, 0.54, 0.45
Tasks: 253 total, 2 running, 251 sleeping, 0 stopped, 0 zombie
Cpu(s): 0.7%us, 0.2%sy, 0.0%ni, 97.8%id, 1.2%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 6998260k total, 6849048k used, 149212k free, 248k buffers
Swap: 440478516k total, 1981912k used, 438496604k free, 1541356k cached
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
3534 postgres 20 0 2330m 1.4g 1.1g S 0.0 20.4 1:06.99 postgres: deploy mtalcott 10.222.154.172(53495) idle
9143 postgres 20 0 2221m 1.1g 983m S 0.0 16.9 0:14.75 postgres: deploy mtalcott 10.222.154.167(35811) idle
6026 postgres 20 0 2341m 1.1g 864m S 0.0 16.4 0:46.56 postgres: deploy mtalcott 10.222.154.167(37110) idle
18538 postgres 20 0 2327m 1.1g 865m S 0.0 16.1 2:06.59 postgres: deploy mtalcott 10.222.154.172(47796) idle
1575 postgres 20 0 2358m 1.1g 858m S 0.0 15.9 1:41.76 postgres: deploy mtalcott 10.222.154.172(52560) idle
```
There are about 29 total idle connections. `sudo ipcs -m` only shows:
```
------ Shared Memory Segments --------
key shmid owner perms bytes nattch status
0x0052e2c1 163840 postgres 600 48 21
```
Surprisingly, it only shows it using 48 bytes. Any ideas why that would be?
My shared memory settings are:
kernel.shmmax = 8589934592 # 8 GB
kernel.shmall = 2097152 # * 4096 = 8 GB
kernel.shmmni = 4096
Do I need to set lower shared memory limits? In the past, I've run into issues using pg_dump and executing larger transactions with lower values. If I can monitor the shared memory segment I can better understand when postgres is allocating and releasing..
Mack Talcott <mack.talcott@gmail.com> writes: > I am trying to debug some shared memory issues with Postgres 9.3.1 and > CentOS release 6.3 (Final). I have a database machine that probably has > some misconfigured shared memory settings. It's getting into 2+ GB of > swap. Restarting postgres frees all of the memory, but after a few hours > of normal usage it will go back into swap. Are you sure the kernel isn't just swapping out some idle processes because it feels like it? These numbers don't exactly look like a machine under stress: > top - 09:38:16 up 1 day, 21:21, 3 users, load average: 0.40, 0.54, 0.45 > Tasks: 253 total, 2 running, 251 sleeping, 0 stopped, 0 zombie > Cpu(s): 0.7%us, 0.2%sy, 0.0%ni, 97.8%id, 1.2%wa, 0.0%hi, 0.0%si, > 0.0%st > Mem: 6998260k total, 6849048k used, 149212k free, 248k buffers > Swap: 440478516k total, 1981912k used, 438496604k free, 1541356k cached In particular, you've got 1.5 gig of filesystem cache, so you're hardly out of memory. I don't know where the other 5.5 gig of RAM went, but it doesn't look like postgres is eating it; what else is running on this box? These lines look absolutely normal, assuming that you've configured shared_buffers somewhere in the neighborhood of 1GB: > PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND > 3534 postgres 20 0 2330m 1.4g 1.1g S 0.0 20.4 1:06.99 postgres: > deploy mtalcott 10.222.154.172(53495) idle > 9143 postgres 20 0 2221m 1.1g 983m S 0.0 16.9 0:14.75 postgres: > deploy mtalcott 10.222.154.167(35811) idle > 6026 postgres 20 0 2341m 1.1g 864m S 0.0 16.4 0:46.56 postgres: > deploy mtalcott 10.222.154.167(37110) idle > 18538 postgres 20 0 2327m 1.1g 865m S 0.0 16.1 2:06.59 postgres: > deploy mtalcott 10.222.154.172(47796) idle > 1575 postgres 20 0 2358m 1.1g 858m S 0.0 15.9 1:41.76 postgres: > deploy mtalcott 10.222.154.172(52560) idle The key thing to realize about that is that the SHR column is *shared* memory, ie all these processes are referencing the same chunk of about 1GB worth of memory. The process-specific memory is RES minus SHR, and none of those processes seem tremendously out of line on that measure. (Note: the fact that the SHR values aren't all exactly the same is because top doesn't count a shared page until the process has physically touched that page. Even the guy with 1.1g of SHR might not have touched all of the shared storage yet.) I'm not sure you have a problem here. If you do, these figures aren't showing it. Having some stuff shoved out to swap is not a problem unless you have a problem with the swap I/O rate. You might try watching "vmstat 1" for awhile to see if the si/so columns show significant activity. regards, tom lane
On Tue, Dec 10, 2013 at 8:54 PM, Tom Lane <tgl@sss.pgh.pa.us> wrote: > Mack Talcott <mack.talcott@gmail.com> writes: >> I am trying to debug some shared memory issues with Postgres 9.3.1 and >> CentOS release 6.3 (Final). I have a database machine that probably has >> some misconfigured shared memory settings. It's getting into 2+ GB of >> swap. Restarting postgres frees all of the memory, but after a few hours >> of normal usage it will go back into swap. > > Are you sure the kernel isn't just swapping out some idle processes > because it feels like it? These numbers don't exactly look like a > machine under stress: > >> top - 09:38:16 up 1 day, 21:21, 3 users, load average: 0.40, 0.54, 0.45 >> Tasks: 253 total, 2 running, 251 sleeping, 0 stopped, 0 zombie >> Cpu(s): 0.7%us, 0.2%sy, 0.0%ni, 97.8%id, 1.2%wa, 0.0%hi, 0.0%si, >> 0.0%st >> Mem: 6998260k total, 6849048k used, 149212k free, 248k buffers >> Swap: 440478516k total, 1981912k used, 438496604k free, 1541356k cached > > In particular, you've got 1.5 gig of filesystem cache, so you're hardly > out of memory. I don't know where the other 5.5 gig of RAM went, but > it doesn't look like postgres is eating it; what else is running on > this box? > > These lines look absolutely normal, assuming that you've configured > shared_buffers somewhere in the neighborhood of 1GB: > >> PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND >> 3534 postgres 20 0 2330m 1.4g 1.1g S 0.0 20.4 1:06.99 postgres: >> deploy mtalcott 10.222.154.172(53495) idle >> 9143 postgres 20 0 2221m 1.1g 983m S 0.0 16.9 0:14.75 postgres: >> deploy mtalcott 10.222.154.167(35811) idle >> 6026 postgres 20 0 2341m 1.1g 864m S 0.0 16.4 0:46.56 postgres: >> deploy mtalcott 10.222.154.167(37110) idle >> 18538 postgres 20 0 2327m 1.1g 865m S 0.0 16.1 2:06.59 postgres: >> deploy mtalcott 10.222.154.172(47796) idle >> 1575 postgres 20 0 2358m 1.1g 858m S 0.0 15.9 1:41.76 postgres: >> deploy mtalcott 10.222.154.172(52560) idle > > The key thing to realize about that is that the SHR column is *shared* > memory, ie all these processes are referencing the same chunk of about 1GB > worth of memory. The process-specific memory is RES minus SHR, and none > of those processes seem tremendously out of line on that measure. (Note: > the fact that the SHR values aren't all exactly the same is because top > doesn't count a shared page until the process has physically touched that > page. Even the guy with 1.1g of SHR might not have touched all of the > shared storage yet.) > > I'm not sure you have a problem here. If you do, these figures aren't > showing it. Having some stuff shoved out to swap is not a problem unless > you have a problem with the swap I/O rate. You might try watching "vmstat > 1" for awhile to see if the si/so columns show significant activity. > > regards, tom lane Thanks for your reply. I've included the rest of the top output below. This is a dedicated postgres box, so nothing else is running. shared_buffers is set to 1.8g, to accommodate some of our larger operations. It looks like this could be lowered a bit, since the max shared usage is only 1.1g. The pattern I am seeing is that postgres processes keep growing in shared (this makes sense as they access more of the shared memory, as you've pointed out) but also process-specific memory as they run more queries. The largest ones are using around 300mb of process-specific memory, even when they're idle and outside of any transactions. As for CentOS using 1.5g for disk caching, I'm at a loss. I have played with the 'swappiness', setting it down to 10 from the default of 60 with sysctl. It didn't have any effect. Once 70-80% of memory is reached, the machine starts using swap, and it keeps growing. At first, queries become slightly slower. Then some larger selects start taking 10, then 20, then 30 seconds. During this, vmstat shows 5-20 procs waiting on both CPU and I/O. All of a sudden, generally after some large transaction, about 1g of swap is released and the number of blocked procs jumps to 50-80. Everything grinds to a halt for a few minutes. Sometimes my app can recover, and sometimes it needs a little kick. As expected, resetting the connection clears the process-specific memory. The same number of connections on the same machine only use 20% of memory (with 0 swap) when I periodically reconnect. What kind of information are these processes holding on to? I would expect long-running, idle postgres processes to have similar memory usage to brand new, idle ones. One thing worth mentioning is that I am heavily using schemas. On every request, I am setting and resetting search_path. This top was captured just before swap was released PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 3534 postgres 20 0 2330m 1.4g 1.1g S 0.0 20.4 1:06.99 postgres: deploy mtalcott 10.222.155.179(53495) idle 9143 postgres 20 0 2221m 1.1g 983m S 0.0 16.9 0:14.75 postgres: deploy mtalcott 10.222.155.164(35811) idle 6026 postgres 20 0 2341m 1.1g 864m S 0.0 16.4 0:46.56 postgres: deploy mtalcott 10.222.155.164(37110) idle 18538 postgres 20 0 2327m 1.1g 865m S 0.0 16.1 2:06.59 postgres: deploy mtalcott 10.222.155.179(47796) idle 1575 postgres 20 0 2358m 1.1g 858m S 0.0 15.9 1:41.76 postgres: deploy mtalcott 10.222.155.179(52560) idle 17931 postgres 20 0 2343m 1.1g 834m S 0.0 15.8 2:04.61 postgres: deploy mtalcott 10.222.155.164(54439) idle 18286 postgres 20 0 2363m 1.0g 797m S 1.3 15.6 1:54.97 postgres: deploy mtalcott 10.222.155.179(47588) idle 4541 postgres 20 0 2343m 1.0g 783m S 0.0 15.2 1:20.75 postgres: deploy mtalcott 10.222.155.179(53938) idle 18763 postgres 20 0 2347m 1.0g 772m S 0.0 14.9 1:49.83 postgres: deploy mtalcott 10.222.155.164(32853) idle 1088 postgres 20 0 2336m 1.0g 778m S 0.3 14.9 1:35.40 postgres: deploy mtalcott 10.222.155.179(52312) idle 17933 postgres 20 0 2343m 996m 800m S 0.0 14.6 2:11.68 postgres: deploy mtalcott 10.222.155.164(54443) idle 1089 postgres 20 0 2310m 970m 776m S 1.7 14.2 1:18.34 postgres: deploy mtalcott 10.222.155.164(46130) idle 3535 postgres 20 0 2354m 950m 779m S 0.0 13.9 1:18.44 postgres: deploy mtalcott 10.222.155.164(33599) idle 1708 postgres 20 0 2308m 940m 760m S 0.0 13.8 1:08.72 postgres: deploy mtalcott 10.222.155.164(49552) idle 18540 postgres 20 0 2337m 932m 784m S 0.7 13.6 1:50.66 postgres: deploy mtalcott 10.222.155.164(59856) idle 8471 postgres 20 0 2312m 683m 429m S 0.0 10.0 0:54.35 postgres: deploy mtalcott 10.222.155.179(57867) idle 5931 postgres 20 0 2327m 589m 340m S 0.0 8.6 0:40.07 postgres: deploy mtalcott 10.222.155.179(55092) idle 6070 postgres 20 0 2306m 568m 358m S 0.0 8.3 0:42.56 postgres: deploy mtalcott 10.222.155.179(55307) idle 9135 postgres 20 0 2235m 523m 341m S 0.0 7.7 0:19.65 postgres: deploy mtalcott 10.222.155.164(35140) idle 10996 postgres 20 0 2103m 229m 169m S 0.0 3.4 0:01.65 postgres: deploy mtalcott 10.222.155.179(60798) idle 11001 postgres 20 0 2062m 163m 144m S 0.7 2.4 0:01.90 postgres: deploy mtalcott 10.222.155.164(44039) idle 17697 postgres 20 0 2038m 151m 150m S 0.0 2.2 0:09.82 postgres: checkpointer process 10869 postgres 20 0 2045m 82m 76m S 3.3 1.2 0:12.19 postgres: deploy mtalcott 10.197.52.158(43556) idle in transaction 10994 postgres 20 0 2052m 61m 50m S 0.0 0.9 0:00.77 postgres: deploy mtalcott 10.222.155.179(60757) idle 17680 postgres 20 0 2037m 37m 37m S 0.0 0.6 0:03.34 /usr/local/pgsql9.3/bin/postgres -D /db/pgsql/9.3/data 17698 postgres 20 0 2038m 36m 35m S 0.0 0.5 0:02.85 postgres: writer process 10993 postgres 20 0 2045m 29m 22m S 0.0 0.4 0:00.26 postgres: deploy mtalcott 10.222.155.164(42908) idle 17701 postgres 20 0 134m 21m 272 S 0.0 0.3 1:21.61 postgres: stats collector process 4905 postgres 20 0 2045m 13m 8408 S 0.0 0.2 0:00.44 postgres: deploy mtalcott 10.222.155.164(47193) idle 5041 postgres 20 0 2044m 13m 8124 S 0.0 0.2 0:00.54 postgres: deploy mtalcott 10.222.155.164(49813) idle 5036 postgres 20 0 2044m 12m 7808 S 0.0 0.2 0:00.50 postgres: deploy mtalcott 10.222.155.164(49380) idle 6452 postgres 20 0 2044m 10m 6112 S 0.0 0.2 0:00.26 postgres: deploy mtalcott 10.222.155.164(44313) idle 5023 postgres 20 0 2044m 10m 5868 S 0.0 0.2 0:00.50 postgres: deploy mtalcott 10.222.155.164(47882) idle 5029 postgres 20 0 2045m 10m 6732 S 0.0 0.1 0:00.81 postgres: deploy mtalcott 10.222.155.164(48498) idle 5808 postgres 20 0 2044m 9408 7040 S 0.0 0.1 0:00.30 postgres: deploy mtalcott 10.222.155.164(33987) idle 17700 postgres 20 0 2039m 4728 4432 S 0.0 0.1 0:00.71 postgres: autovacuum launcher process 10567 deploy 20 0 97820 1372 432 S 0.0 0.0 0:00.02 sshd: deploy@pts/2 10564 root 20 0 97820 1192 284 S 0.0 0.0 0:00.04 sshd: deploy [priv] 10998 deploy 20 0 15168 1044 604 R 0.7 0.0 0:00.59 top -c
Mack Talcott <mack.talcott@gmail.com> writes: > The pattern I am seeing is that postgres processes keep growing in > shared (this makes sense as they access more of the shared memory, as > you've pointed out) but also process-specific memory as they run more > queries. The largest ones are using around 300mb of process-specific > memory, even when they're idle and outside of any transactions. There's quite a lot of stuff that a PG process will cache in local memory once it's acquired the info, for example: - relcache (relation descriptors) - catcache (system catalog entries) - compiled trees for plpgsql functions 300mb worth of that stuff seems on the high side, but perhaps you have lots and lots of tables, or lots and lots of functions? If this is the explanation then flushing that info just results in restarting from a cold-cache situation, which doesn't seem likely to be a win. You're just going to be paying to read it in again. > As for CentOS using 1.5g for disk caching, I'm at a loss. I have > played with the 'swappiness', setting it down to 10 from the default > of 60 with sysctl. It didn't have any effect. Swappiness has nothing to do with disk cache. Disk cache just means that the kernel is free to use any spare memory for copies of file pages it's read from disk lately. This is almost always a good thing, because it saves reading those pages again if they're needed again. And the key word there is "spare" --- the kernel is at liberty to drop those cached pages if it needs the memory for something more pressing. So there's really no downside. Trying to reduce that number is completely counterproductive. Rather, my observation was that if you had a gig and a half worth of RAM that the kernel felt it could afford to use for disk caching, then you weren't having much of a memory problem. However, apparently that snapshot wasn't representative of your problem case: > Once 70-80% of memory is reached, the machine starts using swap, and > it keeps growing. At first, queries become slightly slower. Then > some larger selects start taking 10, then 20, then 30 seconds. During > this, vmstat shows 5-20 procs waiting on both CPU and I/O. I wonder if the short answer for this isn't that you should be using fewer backends by running a connection pooler. If the backends want to cache a couple hundred meg worth of stuff, it's probably wise to let them do so. Or maybe you should just buy some more RAM. 8GB is pretty puny for a server these days (heck, the obsolete laptop I'm typing this mail on has half that much). regards, tom lane
On Wed, Dec 11, 2013 at 9:39 PM, Tom Lane <tgl@sss.pgh.pa.us> wrote: > Mack Talcott <mack.talcott@gmail.com> writes: >> The pattern I am seeing is that postgres processes keep growing in >> shared (this makes sense as they access more of the shared memory, as >> you've pointed out) but also process-specific memory as they run more >> queries. The largest ones are using around 300mb of process-specific >> memory, even when they're idle and outside of any transactions. > > There's quite a lot of stuff that a PG process will cache in local memory > once it's acquired the info, for example: > - relcache (relation descriptors) > - catcache (system catalog entries) > - compiled trees for plpgsql functions > > 300mb worth of that stuff seems on the high side, but perhaps you have > lots and lots of tables, or lots and lots of functions? This has got to be the problem. It's known that pathological workloads (lots and lots of tables,views, and functions) abuse the cache memory segment. There's no cap to cache memory so over time it will just accumulate entries until there's nothing left to cache. For most applications, this doesn't even show up on the radar. However, 300mb per postgres backend will burn through that 8gb pretty quickly. It's tempting to say, "there should be a limit to backend local cache" but it's not clear if the extra tracking is really worth it all things considered. There was some discussion about this (see the archives). Workarounds: *) install connection pooler (as Tom noted), in particular pgbouncer. For workloads like this you will want to be spartan on the number of physical connections -- say, 1 * number of cores. For this option to work you need to use transaction mode which in turn limits use of session dependent features (advisory locks, NOTIFY, prepared statements). Also if your client stack is java you need to take some extra steps. *) add memory *) force connections to recycle every X period of time merlin
Merlin Moncure <mmoncure@gmail.com> writes: > It's tempting to say, "there should be a limit to backend local cache" > but it's not clear if the extra tracking is really worth it all things > considered. There was some discussion about this (see the archives). Yeah --- there actually was a limit on total catcache size once, long ago. We took it out because it was (a) expensive to enforce and (b) either pointless or counterproductive on most workloads. The catcache is probably the least of the memory hogs anyway, so it might be that limiting the size of relcache or function caches would be more useful. But that memory is likely to discourage most hackers from investigating. regards, tom lane
> There's quite a lot of stuff that a PG process will cache in local memory > once it's acquired the info, for example: > - relcache (relation descriptors) > - catcache (system catalog entries) > - compiled trees for plpgsql functions > > 300mb worth of that stuff seems on the high side, but perhaps you have > lots and lots of tables, or lots and lots of functions? > > If this is the explanation then flushing that info just results in > restarting from a cold-cache situation, which doesn't seem likely to > be a win. You're just going to be paying to read it in again. It does seem a bit on the high side, but that makes sense. There are about 90 tables and 5 functions in each schema (all are identical), but there are several infrequent queries for overall statistics that do a union over all schemas (using UNION ALL). That seems like the most likely culprit, as there are ~500 of these schemas. However, as the app serves a variety of customers, each request makes queries in a different schema. Seems like eventually these caches would get pretty large even without the all-schema queries. > Swappiness has nothing to do with disk cache. Disk cache just means that > the kernel is free to use any spare memory for copies of file pages it's > read from disk lately. This is almost always a good thing, because it > saves reading those pages again if they're needed again. And the key word > there is "spare" --- the kernel is at liberty to drop those cached pages > if it needs the memory for something more pressing. So there's really no > downside. Trying to reduce that number is completely counterproductive. > Rather, my observation was that if you had a gig and a half worth of RAM > that the kernel felt it could afford to use for disk caching, then you > weren't having much of a memory problem. However, apparently that > snapshot wasn't representative of your problem case: I see. So, maybe the kernel is _first_ determining that some of the inactive processes' memory should be swapped out. Then, since there is free memory, it's being used for disk cache? > I wonder if the short answer for this isn't that you should be using fewer > backends by running a connection pooler. If I can figure out the maximum number of connections that my server can handle, that's definitely a possibility. > If the backends want to cache a > couple hundred meg worth of stuff, it's probably wise to let them do so. > Or maybe you should just buy some more RAM. 8GB is pretty puny for a > server these days (heck, the obsolete laptop I'm typing this mail on > has half that much). More memory is definitely a good solution. This server is on EC2, and I'm working on replacing it with an instance with twice as much. However, my concern is that if I double the number of app servers to handle higher load, I will run into the same issue. I assume the memory of each process grows until it has all 90 tables from all 500 schemas cached in some way. Any ideas for optimizations that would allow less memory usage in this case with many identical schemas? I'm guessing using views rather than select statements wouldn't help. Any postgres configs concerning caching I should take a look at? Different approaches to data organization? Thanks, Tom. I really appreciate your feedback! > > regards, tom lane