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  • Avoiding memory full -> swap full -> crash

    - by Noam
    I'm experiencing an issue when sometimes the memory gets 100% full, and the swap file also, and the server becomes non-responsive and has to be restarted (causing also problems in database). This is what Cacti shows: The server is running a web-app (database + apache) and during that specific moment didn't experience any ir-regular traffic or usage. This scenario happened twice in the last week. What can cause this? How can I resolve the issue?

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  • Issues in Convergence of Sequential minimal optimization for SVM

    - by Amol Joshi
    I have been working on Support Vector Machine for about 2 months now. I have coded SVM myself and for the optimization problem of SVM, I have used Sequential Minimal Optimization(SMO) by Mr. John Platt. Right now I am in the phase where I am going to grid search to find optimal C value for my dataset. ( Please find details of my project application and dataset details here http://stackoverflow.com/questions/2284059/svm-classification-minimum-number-of-input-sets-for-each-class) I have successfully checked my custom implemented SVM`s accuracy for C values ranging from 2^0 to 2^6. But now I am having some issues regarding the convergence of the SMO for C 128. Like I have tried to find the alpha values for C=128 and it is taking long time before it actually converges and successfully gives alpha values. Time taken for the SMO to converge is about 5 hours for C=100. This huge I think ( because SMO is supposed to be fast. ) though I`m getting good accuracy? I am screwed right not because I can not test the accuracy for higher values of C. I am actually displaying number of alphas changed in every pass of SMO and getting 10, 13, 8... alphas changing continuously. The KKT conditions assures convergence so what is so weird happening here? Please note that my implementation is working fine for C<=100 with good accuracy though the execution time is long. Please give me inputs on this issue. Thank You and Cheers.

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  • Am I understanding premature optimization correctly?

    - by Ed Mazur
    I've been struggling with an application I'm writing and I think I'm beginning to see that my problem is premature optimization. The perfectionist side of me wants to make everything optimal and perfect the first time through, but I'm finding this is complicating the design quite a bit. Instead of writing small, testable functions that do one simple thing well, I'm leaning towards cramming in as much functionality as possible in order to be more efficient. For example, I'm avoiding multiple trips to the database for the same piece of information at the cost of my code becoming more complex. One part of me wants to just not worry about redundant database calls. It would make it easier to write correct code and the amount of data being fetched is small anyway. The other part of me feels very dirty and unclean doing this. :-) I'm leaning towards just going to the database multiple times, which I think is the right move here. It's more important that I finish the project and I feel like I'm getting hung up because of optimizations like this. My question is: is this the right strategy to be using when avoiding premature optimization?

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  • ASP.NET Web Optimization - confusion about loading order

    - by Ciel
    Using the ASP.NET Web Optimization Framework, I am attempting to load some javascript files up. It works fine, except I am running into a peculiar situation with either the loading order, the loading speed, or its execution. I cannot figure out which. Basically, I am using ace code editor for javascript, and I also want to include its autocompletion package. This requires two files. /ace.js /ext-language_tools.js This isn't an issue, if I load both of these files the normal way (with <script> tags) it works fine. But when I try to use the web optimization bundles, it seems as if something goes wrong. Trying this out... bundles.Add(new ScriptBundle("~/bundles/js") { .Include("~/js/ace.js") .Include("~/js/ext-language_tools.js") }); and then in the view .. @Scripts.Render("~/bundles/js") I get the error ace is not defined This means that the ace.js file hasn't run, or hasn't loaded. Because if I break it apart into two bundles, it starts working. bundles.Add(new ScriptBundle("~/bundles/js") { .Include("~/js/ace.js") }); bundles.Add(new ScriptBundle("~/bundles/js/language_tools") { .Include("~/js/ext-language_tools.js") }); Can anyone explain why this would behave in this fashion?

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  • Memory optimization while downloading

    - by lboregard
    hello all i have the following piece of code, that im looking forward to optimize, since i'm consuming gobs of memory this routine is heavily used first optimization would be to move the stringbuilder construction out of the download routine and make it a field of the class, then i would clear it inside the routine can you please suggest any other optimization or point me in the direction of some resources that could help me with this (web articles, books, etc). i'm thinking about replacing the stringbuilder by a fixed (much larger) size buffer ... or perhaps create a larger sized stringbuilder thanks in advance. StreamWriter _writer; StreamReader _reader; public string Download(string msgId) { _writer.WriteLine("BODY <" + msgId + ">"); string response = _reader.ReadLine(); if (!response.StartsWith("222")) return null; bool done = false; StringBuilder body = new StringBuilder(256* 1024); do { response = _reader.ReadLine(); if (OnProgress != null) OnProgress(response.Length); if (response == ".") { done = true; } else { if (response.StartsWith("..")) response = response.Remove(0, 1); body.Append(response); body.Append("\r\n"); } } while (!done); return body.ToString(); }

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  • optimization math computation (multiplication and summing)

    - by wiso
    Suppose you want to compute the sum of the square of the differences of items: $\sum_{i=1}^{N-1} (x_i - x_{i+1})^2$, the simplest code (the input is std::vector<double> xs, the ouput sum2) is: double sum2 = 0.; double prev = xs[0]; for (vector::const_iterator i = xs.begin() + 1; i != xs.end(); ++i) { sum2 += (prev - (*i)) * (prev - (*i)); // only 1 - with compiler optimization prev = (*i); } I hope that the compiler do the optimization in the comment above. If N is the length of xs you have N-1 multiplications and 2N-3 sums (sums means + or -). Now suppose you know this variable: sum = $x_1^2 + x_N^2 + 2 sum_{i=2}^{N-1} x_i^2$ Expanding the binomial square: $sum_i^{N-1} (x_i-x_{i+1})^2 = sum - 2\sum_{i=1}^{N-1} x_i x_{i+1}$ so the code becomes: double sum2 = 0.; double prev = xs[0]; for (vector::const_iterator i = xs.begin() + 1; i != xs.end(); ++i) { sum2 += (*i) * prev; prev = (*i); } sum2 = -sum2 * 2. + sum; Here I have N multiplications and N-1 additions. In my case N is about 100. Well, compiling with g++ -O2 I got no speed up (I try calling the inlined function 2M times), why?

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  • Clever memory usage through the years

    - by Ben Emmett
    A friend and I were recently talking about the really clever tricks people have used to get the most out of memory. I thought I’d share my favorites, and would love to hear yours too! Interleaving on drum memory Back in the ye olde days before I’d been born (we’re talking the 50s / 60s here), working memory commonly took the form of rotating magnetic drums. These would spin at a constant speed, and a fixed head would read from memory when the correct part of the drum passed it by, a bit like a primitive platter disk. Because each revolution took a few milliseconds, programmers took to manually arranging information non-sequentially on the drum, timing when an instruction or memory address would need to be accessed, then spacing information accordingly around the edge of the drum, thus reducing the access delay. Similar techniques were still used on hard disks and floppy disks into the 90s, but have become irrelevant with modern disk technologies. The Hashlife algorithm Conway’s Game of Life has attracted numerous implementations over the years, but Bill Gosper’s Hashlife algorithm is particularly impressive. Taking advantage of the repetitive nature of many cellular automata, it uses a quadtree structure to store the hashes of pieces of the overall grid. Over time there are fewer and fewer new structures which need to be evaluated, so it starts to run faster with larger grids, drastically outperforming other algorithms both in terms of speed and the size of grid which can be simulated. The actual amount of memory used is huge, but it’s used in a clever way, so makes the list . Elite’s procedural generation Ok, so this isn’t exactly a memory optimization – more a storage optimization – but it gets an honorable mention anyway. When writing Elite, David Braben and Ian Bell wanted to build a rich world which gamers could explore, but their 22K memory was something of a limitation (for comparison that’s about the size of my avatar picture at the top of this page). They procedurally generated all the characteristics of the 2048 planets in their virtual universe, including the names, which were stitched together using a lookup table of parts of names. In fact the original plans were for 2^52 planets, but it was decided that that was probably too many. Oh, and they did that all in assembly language. Other games of the time used similar techniques too – The Sentinel’s landscape generation algorithm being another example. Modern Garbage Collectors Garbage collection in managed languages like Java and .NET ensures that most of the time, developers stop needing to care about how they use and clean up memory as the garbage collector handles it automatically. Achieving this without killing performance is a near-miraculous feet of software engineering. Much like when learning chemistry, you find that every time you think you understand how the garbage collector works, it turns out to be a mere simplification; that there are yet more complexities and heuristics to help it run efficiently. Of course introducing memory problems is still possible (and there are tools like our memory profiler to help if that happens to you) but they’re much, much rarer. A cautionary note In the examples above, there were good and well understood reasons for the optimizations, but cunningly optimized code has usually had to trade away readability and maintainability to achieve its gains. Trying to optimize memory usage without being pretty confident that there’s actually a problem is doing it wrong. So what have I missed? Tell me about the ingenious (or stupid) tricks you’ve seen people use. Ben

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  • Amazon EC2 - Free memory

    - by Damo
    We have an amazon ec2 small instance running and over the past few days we noticed that the memory is going down and down. On the small instance, we are running apache and tomcat6 Tomcat is started with the following JVM parameters -Xms32m -Xmx128m -XX:PermSize=128m -XX:MaxPermSize=256m We use nagios to monitor stuff like updates to apply, free disk space and memory. Everything else is behaving as expected but our memory is going down all the time. Our app receives approx half a million hits a day When I shutdown apache and tomcat, and ran free -m, we had only 594mb of memory free out out of the 1.7gb of memory. Not much else is running on the small instance and when running the top command I cannot see where the memory is going. The app we run on tomcat is a grails webapp. Could there be a possibility that there is a memory leak within our application? I read online and folks say that a small amazon instance is perfect for running apach and tomcat. I found a few posts online that showed how to setup apache and tomcat to limit the memory usage and I have already performed those steps. The memory is not being used up as quick but the memory is still decreasing over time. We have other amazone ec2 small instances running grails apps and the memory is fairly standard on those nodes. But they would not be receiving as much traffic Just to add, when I run the top command on the problem server, I cannot see where all the memory is being used Any help with this is greatly appreciated The output of free -m when run on my server is as follows total used free shared buffers cached Mem: 1657 1380 277 0 158 773 -/+ buffers/cache: 447 1209 Swap: 895 0 895 In your opinion, does this look ok? At what stage would the OS give back memory, would it wait to the memory reaches 0% or is this OS dependent?

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  • Commited memory goes to physical RAM or reserves space in the paging file?

    - by Sil
    When I do VirtualAlloc with MEM_COMMIT this "Allocates physical storage in memory or in the paging file on disk for the specified reserved memory pages" (quote from MSDN article http://msdn.microsoft.com/en-us/library/aa366887%28VS.85%29.aspx). All is fine up until now BUT: the description of Commited Bytes Counter says that "Committed memory is the physical memory which has space reserved on the disk paging file(s)." I also read "Windows via C/C++ 5th edition" and this book says that commiting memory means reserving space in the page file.... The last two cases don't make sense to me... If you commit memory, doesn't that mean that you commit to physical storage (RAM)? The page file being there for swaping out currently unused pages of memory in case memory gets low. The book says that when you commit memory you actually reserve space in the paging file. If this were true than that would mean that for a committed page there is space reserved in the paging file and a page frame in physical in memory... So twice as much space is needed ?! Isn't the page file's purpose to make the total physical memory larger than it actually is? If I have a 1G of RAM with a 1G page file = 2G of usable "physical memory"(the book also states this but right after that it says what I discribed at point 2). What am I missing? Thanks.

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  • RedHat 5.5 server does not show per processor memory utilization

    - by Mike S
    I have been searching all over internet but not finding any leads. I have a system with a memory leak that I am trying to troubleshoot. Unfortunately I am not able to see per processor memory utilization. Here are the outputs of TOP and PS commands. Linux SERVER_NAME 2.6.18-194.8.1.el5 #1 SMP Wed Jun 23 10:52:51 EDT 2010 x86_64 x86_64 x86_64 GNU/Linux top - 09:17:13 up 18:43, 3 users, load average: 0.00, 0.00, 0.00 Tasks: 375 total, 1 running, 373 sleeping, 0 stopped, 1 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 32922828k total, 32776712k used, 146116k free, 267128k buffers Swap: 5245212k total, 0k used, 5245212k free, 32141044k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 1 root 15 0 10348 744 620 S 0.0 0.0 0:05.65 init 2 root RT -5 0 0 0 S 0.0 0.0 0:00.05 migration/0 3 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/0 4 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/0 5 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/1 6 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/1 7 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/1 8 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/2 9 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/2 10 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/2 11 root RT -5 0 0 0 S 0.0 0.0 0:00.01 migration/3 12 root 34 19 0 0 0 S 0.0 0.0 0:00.01 ksoftirqd/3 13 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/3 14 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/4 15 root 34 19 0 0 0 S 0.0 0.0 0:00.01 ksoftirqd/4 16 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/4 17 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/5 18 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/5 19 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/5 20 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/6 % ps -auxf | sort -nr -k 4 | head -10 Warning: bad syntax, perhaps a bogus '-'? See /usr/share/doc/procps-3.2.7/FAQ xfs 6205 0.0 0.0 23316 3892 ? Ss Aug19 0:00 xfs -droppriv -daemon uuidd 6101 0.0 0.0 60976 224 ? Ss Aug19 0:00 /usr/sbin/uuidd USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND smmsp 6130 0.0 0.0 57900 1784 ? Ss Aug19 0:00 sendmail: Queue runner@01:00:00 for /var/spool/clientmqueue rpc 5126 0.0 0.0 8052 632 ? Ss Aug19 0:00 portmap root 99 0.0 0.0 0 0 ? S< Aug19 0:00 [events/1] root 98 0.0 0.0 0 0 ? S< Aug19 0:00 [events/0] root 97 0.0 0.0 0 0 ? S< Aug19 0:00 [watchdog/31] root 96 0.0 0.0 0 0 ? SN Aug19 0:00 [ksoftirqd/31] root 95 0.0 0.0 0 0 ? S< Aug19 0:00 [migration/31] Any help with this is appretiate.

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  • c++ overloading delete, retrieve size

    - by user300713
    Hi, I am currently writing a small custom memory Allocator in c++, and want to use it together with operator overloading of new/delete. Anyways, my memory Allocator basicall checks if the requested memory is over a certain threshold, and if so uses malloc to allocate the requested memory chunk. Otherwise the memory will be provided by some fixedPool allocators. that generally works, but for my deallocation function looks like this: void MemoryManager::deallocate(void * _ptr, size_t _size){ if(_size heapThreshold) deallocHeap(_ptr); else deallocFixedPool(_ptr, _size); } so I need to provide the size of the chunk pointed to, to deallocate from the right place. No the problem is that the delete keyword does not provide any hint on the size of the deleted chunk, so I would need something like this: void operator delete(void * _ptr, size_t _size){ MemoryManager::deallocate(_ptr, _size); } But as far as I can see, there is no way to determine the size inside the delete operator.- If I want to keep things the way it is right now, would I have to save the size of the memory chunks myself? Any ideas on how to solve this are welcome! Thanks!

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  • Justifying a memory upgrade

    - by AngryHacker
    My employer has over a thousand servers (running SQL Server 2005 x64 and a couple of other apps) all across the country. And in my opinion they are all massively underpowered for what they need to do. Specifically, I feel that the servers simply do not have enough RAM for the amount of volume the machines are asked to do. All the servers currently have 6GB of RAM. The users are pretty much always complaining about performance (mostly because, immo, the server dips into the paging file quite often). I finally convinced the powers that be to at least try out a memory upgrade on one box and see the results. However, they want before and after metrics, so that they can see that the expense will be justified. My question is what metrics should I collect to see whether the performance truly improves on the box? I am a dev, so I am not sure how and what to collect (i have a passing knowledge of Perfmon).

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  • Applying memory limits to screen sessions

    - by CollinJSimpson
    You can set memory usage limits for standard Linux applications in: /etc/security/limits.conf Unfortunately, I previously thought these limits only apply to user applications and not system services. This means that users can by bypass their limits by launching applications through a system service such as screen. I'd like to know if it's possible to let users use screen but still enforce application limits. Jeff had the great idea of using nohup which obeys user limits (wonderful!), but I would still like to know if it's possible to mimic the useful windowing features of screen. EDIT: It seems my screen sessions are now obeying my hard address space limits defined in /etc/security/limits.conf. I must have been making some mistake. I recently installed cpulimit, but I doubt that's the solution.Thanks for the nohup tip, Jeff! It's very useful. Link to CPU Limit package

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  • postgres memory allocation tuning 2

    - by pstanton
    i've got a Ubuntu Linux system with 12Gb memory most of which (at least 10Gb) can be allocated solely to postgres. the system also has a 6 disk 15k SCSI RAID 10 setup. The process i'm trying to optimise is twofold. firstly a single threaded, single connection will do many inserts into 2-4 tables linked by foreign key. secondly many different complex queries are run against the resulting data, using group by extensively. this part especially needs to be optimised. i have four of these processes running at once in order to make use of the quad core CPU, therefore there will generally be no more than 5 concurrent connections (1 spare for admin tasks). what configuration changes to the default Postgres config would you recommend? I'm looking for the optimum values for things like work_mem, shared_buffers etc. relevant doco thanks!

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  • Will more memory help my CPU-peaking SQL Server 2008 R2

    - by Tor Haugen
    I'm supporting a system running against a SQL Server 2008 R2. The server is a single-CPU box with 8 GB of memory. As traffic has increased, the server has started saturating, peaking to 100% CPU ever more often. Disk I/O remains moderate (somewhat surprisingly). Obviously, a new server would be the best option. But failing that, can I expect a noticable improvement from installing more RAM? Or does RAM only help for I/O issues (through caching)?

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  • Unusually high memory usage on a CentOS VPS with 512 guaranteed RAM

    - by Andrei Bârsan
    I'm working on a medium-sized web application written in PHP that's running on a VPS with 512mb ram. The webapp hasn't been officially launched yet, so there isn't too much traffic going on, just me and a few other people working on it. There is another slightly smaller webapp also hosted on this machine, among 4-5 other small static sites. We are running Centos 5 32-bit & cPanel/WHM. This is the result of running ps aux and, as you can see, it's not using 100% of the RAM. However, on the hypanel overview, it's always shown as using aroun 500MB ram, just for running apache, mysql, and the lowest-memory-footprint versions of the mail server, ftp server etc. -bash-3.2# ps aux USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND root 1 0.0 0.0 2156 664 ? Ss 12:08 0:00 init [3] root 1123 0.0 0.0 2260 548 ? S<s 12:08 0:00 /sbin/udevd -d root 1462 0.0 0.0 1812 568 ? Ss 12:08 0:00 syslogd -m 0 named 1496 0.0 0.0 3808 820 ? Ss 12:08 0:00 nsd named 1497 0.0 0.0 10672 756 ? S 12:08 0:00 nsd named 1499 0.0 0.0 3880 584 ? S 12:08 0:00 nsd root 1514 0.0 0.1 7240 1064 ? Ss 12:08 0:00 /usr/sbin/sshd root 1522 0.0 0.0 2832 832 ? Ss 12:08 0:00 xinetd -stayalive -pidfile /var/run/xinetd.pid root 1534 0.0 0.1 3712 1328 ? S 12:08 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql - mysql 1667 0.0 2.9 225680 30884 ? Sl 12:08 0:00 /usr/sbin/mysqld --basedir=/ --datadir=/var/lib/mysql - mailnull 1766 0.0 0.1 9352 1100 ? Ss 12:08 0:00 /usr/sbin/exim -bd -q60m root 1797 0.0 0.0 2156 708 ? Ss 12:08 0:00 /usr/sbin/dovecot root 1798 0.0 0.0 2632 1012 ? S 12:08 0:00 dovecot-auth root 1816 0.0 3.0 38580 32456 ? Ss 12:08 0:01 /usr/local/bin/spamd -d --allowed-ips=127.0.0.1 --pidfi root 1839 0.0 1.6 63200 17496 ? Ss 12:08 0:00 /usr/local/apache/bin/httpd -k start -DSSL root 1846 0.0 0.1 5416 1468 ? Ss 12:08 0:00 pure-ftpd (SERVER) root 1848 0.0 0.1 6212 1244 ? S 12:08 0:00 /usr/sbin/pure-authd -s /var/run/ftpd.sock -r /usr/sbin root 1856 0.0 0.1 4492 1112 ? Ss 12:08 0:00 crond root 1864 0.0 0.0 2356 428 ? Ss 12:08 0:00 /usr/sbin/atd dovecot 1927 0.0 0.1 5196 1952 ? S 12:08 0:00 pop3-login dovecot 1928 0.0 0.1 5196 1948 ? S 12:08 0:00 pop3-login dovecot 1929 0.0 0.1 5316 2012 ? S 12:08 0:00 imap-login dovecot 1930 0.0 0.2 5416 2228 ? S 12:08 0:00 imap-login root 1939 0.0 0.1 3936 1964 ? S 12:08 0:00 cPhulkd - processor root 1963 0.0 0.8 15876 8564 ? S 12:08 0:00 cpsrvd (SSL) - waiting for connections root 1966 0.0 0.7 15172 7748 ? S 12:08 0:00 cpdavd - accepting connections on 2077 and 2078 root 1990 0.0 0.2 5008 3136 ? S 12:08 0:00 queueprocd - wait to process a task root 2017 0.0 2.9 38580 31020 ? S 12:08 0:00 spamd child root 2018 0.0 0.5 8904 5636 ? S 12:08 0:00 /usr/bin/perl /usr/local/cpanel/bin/leechprotect nobody 2021 0.0 3.2 66512 33724 ? S 12:08 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 2022 0.0 3.1 67812 33024 ? S 12:08 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 2024 0.0 1.9 64364 20680 ? S 12:08 0:00 /usr/local/apache/bin/httpd -k start -DSSL root 2027 0.0 0.4 9000 4540 ? S 12:08 0:00 tailwatchd root 2032 0.0 0.1 4176 1836 ? SN 12:08 0:00 cpanellogd - sleeping for logs nobody 3096 0.0 1.9 64572 20264 ? S 12:09 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 3097 0.0 2.8 66008 30136 ? S 12:09 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 3098 0.0 2.8 65704 29752 ? S 12:09 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 3099 0.0 3.1 67260 32816 ? S 12:09 0:00 /usr/local/apache/bin/httpd -k start -DSSL andrei 3448 0.0 0.1 3204 1632 ? S 12:50 0:00 imap nobody 3537 0.0 1.9 64308 20108 ? S 13:01 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 3614 0.0 1.9 64576 20628 ? S 13:10 0:00 /usr/local/apache/bin/httpd -k start -DSSL nobody 3615 0.0 1.3 63200 14672 ? S 13:10 0:00 /usr/local/apache/bin/httpd -k start -DSSL root 3626 0.0 0.2 10232 2964 ? Rs 13:14 0:00 sshd: root@pts/0 root 3648 0.0 0.1 3844 1600 pts/0 Ss 13:14 0:00 -bash root 3826 0.0 0.0 2532 908 pts/0 R+ 13:21 0:00 ps aux Lately, without any significant changes to the configuration, the memory usage started peaking and going over 512, causing the virtual server to kill apache, basically murdering our site in the process. Do you have any idea if this is normal and more resources should be acquired? I don't think... since there isn't too much data or traffic online yet.

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  • Where is all the memory being consumed?

    - by Mark L
    Hello, I have a Dell R300 Ubuntu 9.10 box with 4GB of memory. All I'm running on there is haproxy, nagios and postfix yet there is ~2.7GB of memory being consumed. I've run ps and I can't get the sums to add up. Could anyone shed any light on where all the memory is being used? Cheers, Mark $ sudo free -m total used free shared buffers cached Mem: 3957 2746 1211 0 169 2320 -/+ buffers/cache: 256 3701 Swap: 6212 0 6212 Sorry for pasting all of ps' output but I'm keen to get to the bottom of this. $ sudo ps aux [sudo] password for mark: USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND root 1 0.0 0.0 19320 1656 ? Ss May20 0:05 /sbin/init root 2 0.0 0.0 0 0 ? S< May20 0:00 [kthreadd] root 3 0.0 0.0 0 0 ? S< May20 0:00 [migration/0] root 4 0.0 0.0 0 0 ? S< May20 0:16 [ksoftirqd/0] root 5 0.0 0.0 0 0 ? S< May20 0:00 [watchdog/0] root 6 0.0 0.0 0 0 ? S< May20 0:03 [migration/1] root 7 0.0 0.0 0 0 ? S< May20 3:10 [ksoftirqd/1] root 8 0.0 0.0 0 0 ? S< May20 0:00 [watchdog/1] root 9 0.0 0.0 0 0 ? S< May20 0:00 [migration/2] root 10 0.0 0.0 0 0 ? S< May20 0:19 [ksoftirqd/2] root 11 0.0 0.0 0 0 ? S< May20 0:00 [watchdog/2] root 12 0.0 0.0 0 0 ? S< May20 0:01 [migration/3] root 13 0.0 0.0 0 0 ? S< May20 0:41 [ksoftirqd/3] root 14 0.0 0.0 0 0 ? S< May20 0:00 [watchdog/3] root 15 0.0 0.0 0 0 ? S< May20 0:03 [events/0] root 16 0.0 0.0 0 0 ? S< May20 0:10 [events/1] root 17 0.0 0.0 0 0 ? S< May20 0:08 [events/2] root 18 0.0 0.0 0 0 ? S< May20 0:08 [events/3] root 19 0.0 0.0 0 0 ? S< May20 0:00 [cpuset] root 20 0.0 0.0 0 0 ? S< May20 0:00 [khelper] root 21 0.0 0.0 0 0 ? S< May20 0:00 [netns] root 22 0.0 0.0 0 0 ? S< May20 0:00 [async/mgr] root 23 0.0 0.0 0 0 ? S< May20 0:00 [kintegrityd/0] root 24 0.0 0.0 0 0 ? S< May20 0:00 [kintegrityd/1] root 25 0.0 0.0 0 0 ? S< May20 0:00 [kintegrityd/2] root 26 0.0 0.0 0 0 ? S< May20 0:00 [kintegrityd/3] root 27 0.0 0.0 0 0 ? S< May20 0:00 [kblockd/0] root 28 0.0 0.0 0 0 ? S< May20 0:01 [kblockd/1] root 29 0.0 0.0 0 0 ? S< May20 0:04 [kblockd/2] root 30 0.0 0.0 0 0 ? S< May20 0:02 [kblockd/3] root 31 0.0 0.0 0 0 ? S< May20 0:00 [kacpid] root 32 0.0 0.0 0 0 ? S< May20 0:00 [kacpi_notify] root 33 0.0 0.0 0 0 ? S< May20 0:00 [kacpi_hotplug] root 34 0.0 0.0 0 0 ? S< May20 0:00 [ata/0] root 35 0.0 0.0 0 0 ? S< May20 0:00 [ata/1] root 36 0.0 0.0 0 0 ? S< May20 0:00 [ata/2] root 37 0.0 0.0 0 0 ? S< May20 0:00 [ata/3] root 38 0.0 0.0 0 0 ? S< May20 0:00 [ata_aux] root 39 0.0 0.0 0 0 ? S< May20 0:00 [ksuspend_usbd] root 40 0.0 0.0 0 0 ? S< May20 0:00 [khubd] root 41 0.0 0.0 0 0 ? S< May20 0:00 [kseriod] root 42 0.0 0.0 0 0 ? S< May20 0:00 [kmmcd] root 43 0.0 0.0 0 0 ? S< May20 0:00 [bluetooth] root 44 0.0 0.0 0 0 ? S May20 0:00 [khungtaskd] root 45 0.0 0.0 0 0 ? S May20 0:00 [pdflush] root 46 0.0 0.0 0 0 ? S May20 0:09 [pdflush] root 47 0.0 0.0 0 0 ? S< May20 0:00 [kswapd0] root 48 0.0 0.0 0 0 ? S< May20 0:00 [aio/0] root 49 0.0 0.0 0 0 ? S< May20 0:00 [aio/1] root 50 0.0 0.0 0 0 ? S< May20 0:00 [aio/2] root 51 0.0 0.0 0 0 ? S< May20 0:00 [aio/3] root 52 0.0 0.0 0 0 ? S< May20 0:00 [ecryptfs-kthrea] root 53 0.0 0.0 0 0 ? S< May20 0:00 [crypto/0] root 54 0.0 0.0 0 0 ? S< May20 0:00 [crypto/1] root 55 0.0 0.0 0 0 ? S< May20 0:00 [crypto/2] root 56 0.0 0.0 0 0 ? S< May20 0:00 [crypto/3] root 70 0.0 0.0 0 0 ? S< May20 0:00 [scsi_eh_0] root 71 0.0 0.0 0 0 ? S< May20 0:00 [scsi_eh_1] root 74 0.0 0.0 0 0 ? S< May20 0:00 [scsi_eh_2] root 75 0.0 0.0 0 0 ? S< May20 0:00 [scsi_eh_3] root 82 0.0 0.0 0 0 ? S< May20 0:00 [kstriped] root 83 0.0 0.0 0 0 ? S< May20 0:00 [kmpathd/0] root 84 0.0 0.0 0 0 ? S< May20 0:00 [kmpathd/1] root 85 0.0 0.0 0 0 ? S< May20 0:00 [kmpathd/2] root 86 0.0 0.0 0 0 ? S< May20 0:00 [kmpathd/3] root 87 0.0 0.0 0 0 ? S< May20 0:00 [kmpath_handlerd] root 88 0.0 0.0 0 0 ? S< May20 0:00 [ksnapd] root 89 0.0 0.0 0 0 ? S< May20 0:00 [kondemand/0] root 90 0.0 0.0 0 0 ? S< May20 0:00 [kondemand/1] root 91 0.0 0.0 0 0 ? S< May20 0:00 [kondemand/2] root 92 0.0 0.0 0 0 ? S< May20 0:00 [kondemand/3] root 93 0.0 0.0 0 0 ? S< May20 0:00 [kconservative/0] root 94 0.0 0.0 0 0 ? S< May20 0:00 [kconservative/1] root 95 0.0 0.0 0 0 ? S< May20 0:00 [kconservative/2] root 96 0.0 0.0 0 0 ? S< May20 0:00 [kconservative/3] root 97 0.0 0.0 0 0 ? S< May20 0:00 [krfcommd] root 315 0.0 0.0 0 0 ? S< May20 0:09 [mpt_poll_0] root 317 0.0 0.0 0 0 ? S< May20 0:00 [mpt/0] root 547 0.0 0.0 0 0 ? S< May20 0:00 [scsi_eh_4] root 587 0.0 0.0 0 0 ? S< May20 0:11 [kjournald2] root 636 0.0 0.0 12748 860 ? S May20 0:00 upstart-udev-bridge --daemon root 657 0.0 0.0 17064 924 ? S<s May20 0:00 udevd --daemon root 666 0.0 0.0 8192 612 ? Ss May20 0:00 dd bs=1 if=/proc/kmsg of=/var/run/rsyslog/kmsg root 774 0.0 0.0 17060 888 ? S< May20 0:00 udevd --daemon root 775 0.0 0.0 17060 888 ? S< May20 0:00 udevd --daemon syslog 825 0.0 0.0 191696 1988 ? Sl May20 0:31 rsyslogd -c4 root 839 0.0 0.0 0 0 ? S< May20 0:00 [edac-poller] root 870 0.0 0.0 0 0 ? S< May20 0:00 [kpsmoused] root 1006 0.0 0.0 5988 604 tty4 Ss+ May20 0:00 /sbin/getty -8 38400 tty4 root 1008 0.0 0.0 5988 604 tty5 Ss+ May20 0:00 /sbin/getty -8 38400 tty5 root 1015 0.0 0.0 5988 604 tty2 Ss+ May20 0:00 /sbin/getty -8 38400 tty2 root 1016 0.0 0.0 5988 608 tty3 Ss+ May20 0:00 /sbin/getty -8 38400 tty3 root 1018 0.0 0.0 5988 604 tty6 Ss+ May20 0:00 /sbin/getty -8 38400 tty6 daemon 1025 0.0 0.0 16512 472 ? Ss May20 0:00 atd root 1026 0.0 0.0 18708 1000 ? Ss May20 0:03 cron root 1052 0.0 0.0 49072 1252 ? Ss May20 0:25 /usr/sbin/sshd root 1084 0.0 0.0 5988 604 tty1 Ss+ May20 0:00 /sbin/getty -8 38400 tty1 root 6320 0.0 0.0 19440 956 ? Ss May21 0:00 /usr/sbin/xinetd -pidfile /var/run/xinetd.pid -stayalive -inetd_compat -inetd_ipv6 nagios 8197 0.0 0.0 27452 1696 ? SNs May21 2:57 /usr/sbin/nagios3 -d /etc/nagios3/nagios.cfg root 10882 0.1 0.0 70280 3104 ? Ss 10:30 0:00 sshd: mark [priv] mark 10934 0.0 0.0 70432 1776 ? S 10:30 0:00 sshd: mark@pts/0 mark 10935 1.4 0.1 21572 4336 pts/0 Ss 10:30 0:00 -bash root 10953 1.0 0.0 15164 1136 pts/0 R+ 10:30 0:00 ps aux haproxy 12738 0.0 0.0 17208 992 ? Ss Jun08 0:49 /usr/sbin/haproxy -f /etc/haproxy/haproxy.cfg root 23953 0.0 0.0 37012 2192 ? Ss Jun04 0:03 /usr/lib/postfix/master postfix 23955 0.0 0.0 39232 2356 ? S Jun04 0:00 qmgr -l -t fifo -u postfix 32603 0.0 0.0 39072 2132 ? S 09:05 0:00 pickup -l -t fifo -u -c Here's meminfo: $ cat /proc/meminfo MemTotal: 4052852 kB MemFree: 1240488 kB Buffers: 173172 kB Cached: 2376420 kB SwapCached: 0 kB Active: 1479288 kB Inactive: 1081876 kB Active(anon): 11792 kB Inactive(anon): 0 kB Active(file): 1467496 kB Inactive(file): 1081876 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 6361700 kB SwapFree: 6361700 kB Dirty: 44 kB Writeback: 0 kB AnonPages: 11568 kB Mapped: 5844 kB Slab: 155032 kB SReclaimable: 145804 kB SUnreclaim: 9228 kB PageTables: 1592 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 8388124 kB Committed_AS: 51732 kB VmallocTotal: 34359738367 kB VmallocUsed: 282604 kB VmallocChunk: 34359453499 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 6784 kB DirectMap2M: 4182016 kB Here's slabinfo: $ cat /proc/slabinfo slabinfo - version: 2.1 # name <active_objs> <num_objs> <objsize> <objperslab> <pagesperslab> : tunables <limit> <batchcount> <sharedfactor> : slabdata <active_slabs> <num_slabs> <sharedavail> ip6_dst_cache 50 50 320 25 2 : tunables 0 0 0 : slabdata 2 2 0 UDPLITEv6 0 0 960 17 4 : tunables 0 0 0 : slabdata 0 0 0 UDPv6 68 68 960 17 4 : tunables 0 0 0 : slabdata 4 4 0 tw_sock_TCPv6 0 0 320 25 2 : tunables 0 0 0 : slabdata 0 0 0 TCPv6 72 72 1792 18 8 : tunables 0 0 0 : slabdata 4 4 0 dm_raid1_read_record 0 0 1064 30 8 : tunables 0 0 0 : slabdata 0 0 0 kcopyd_job 0 0 368 22 2 : tunables 0 0 0 : slabdata 0 0 0 dm_uevent 0 0 2608 12 8 : tunables 0 0 0 : slabdata 0 0 0 dm_rq_target_io 0 0 376 21 2 : tunables 0 0 0 : slabdata 0 0 0 uhci_urb_priv 0 0 56 73 1 : tunables 0 0 0 : slabdata 0 0 0 cfq_queue 0 0 168 24 1 : tunables 0 0 0 : slabdata 0 0 0 mqueue_inode_cache 18 18 896 18 4 : tunables 0 0 0 : slabdata 1 1 0 fuse_request 0 0 632 25 4 : tunables 0 0 0 : slabdata 0 0 0 fuse_inode 0 0 768 21 4 : tunables 0 0 0 : slabdata 0 0 0 ecryptfs_inode_cache 0 0 1024 16 4 : tunables 0 0 0 : slabdata 0 0 0 hugetlbfs_inode_cache 26 26 608 26 4 : tunables 0 0 0 : slabdata 1 1 0 journal_handle 680 680 24 170 1 : tunables 0 0 0 : slabdata 4 4 0 journal_head 144 144 112 36 1 : tunables 0 0 0 : slabdata 4 4 0 revoke_table 256 256 16 256 1 : tunables 0 0 0 : slabdata 1 1 0 revoke_record 512 512 32 128 1 : tunables 0 0 0 : slabdata 4 4 0 ext4_inode_cache 53306 53424 888 18 4 : tunables 0 0 0 : slabdata 2968 2968 0 ext4_free_block_extents 292 292 56 73 1 : tunables 0 0 0 : slabdata 4 4 0 ext4_alloc_context 112 112 144 28 1 : tunables 0 0 0 : slabdata 4 4 0 ext4_prealloc_space 156 156 104 39 1 : tunables 0 0 0 : slabdata 4 4 0 ext4_system_zone 0 0 40 102 1 : tunables 0 0 0 : slabdata 0 0 0 ext2_inode_cache 0 0 776 21 4 : tunables 0 0 0 : slabdata 0 0 0 ext3_inode_cache 0 0 784 20 4 : tunables 0 0 0 : slabdata 0 0 0 ext3_xattr 0 0 88 46 1 : tunables 0 0 0 : slabdata 0 0 0 dquot 0 0 256 16 1 : tunables 0 0 0 : slabdata 0 0 0 shmem_inode_cache 606 620 800 20 4 : tunables 0 0 0 : slabdata 31 31 0 pid_namespace 0 0 2112 15 8 : tunables 0 0 0 : slabdata 0 0 0 UDP-Lite 0 0 832 19 4 : tunables 0 0 0 : slabdata 0 0 0 RAW 183 210 768 21 4 : tunables 0 0 0 : slabdata 10 10 0 UDP 76 76 832 19 4 : tunables 0 0 0 : slabdata 4 4 0 tw_sock_TCP 80 80 256 16 1 : tunables 0 0 0 : slabdata 5 5 0 TCP 81 114 1664 19 8 : tunables 0 0 0 : slabdata 6 6 0 blkdev_integrity 144 144 112 36 1 : tunables 0 0 0 : slabdata 4 4 0 blkdev_queue 64 64 2024 16 8 : tunables 0 0 0 : slabdata 4 4 0 blkdev_requests 120 120 336 24 2 : tunables 0 0 0 : slabdata 5 5 0 fsnotify_event 156 156 104 39 1 : tunables 0 0 0 : slabdata 4 4 0 bip-256 7 7 4224 7 8 : tunables 0 0 0 : slabdata 1 1 0 bip-128 0 0 2176 15 8 : tunables 0 0 0 : slabdata 0 0 0 bip-64 0 0 1152 28 8 : tunables 0 0 0 : slabdata 0 0 0 bip-16 84 84 384 21 2 : tunables 0 0 0 : slabdata 4 4 0 sock_inode_cache 224 276 704 23 4 : tunables 0 0 0 : slabdata 12 12 0 file_lock_cache 88 88 184 22 1 : tunables 0 0 0 : slabdata 4 4 0 net_namespace 0 0 1920 17 8 : tunables 0 0 0 : slabdata 0 0 0 Acpi-ParseExt 640 672 72 56 1 : tunables 0 0 0 : slabdata 12 12 0 taskstats 48 48 328 24 2 : tunables 0 0 0 : slabdata 2 2 0 proc_inode_cache 1613 1750 640 25 4 : tunables 0 0 0 : slabdata 70 70 0 sigqueue 100 100 160 25 1 : tunables 0 0 0 : slabdata 4 4 0 radix_tree_node 22443 22475 560 29 4 : tunables 0 0 0 : slabdata 775 775 0 bdev_cache 72 72 896 18 4 : tunables 0 0 0 : slabdata 4 4 0 sysfs_dir_cache 9866 9894 80 51 1 : tunables 0 0 0 : slabdata 194 194 0 inode_cache 2268 2268 592 27 4 : tunables 0 0 0 : slabdata 84 84 0 dentry 285907 286062 192 21 1 : tunables 0 0 0 : slabdata 13622 13622 0 buffer_head 256447 257472 112 36 1 : tunables 0 0 0 : slabdata 7152 7152 0 vm_area_struct 1469 1541 176 23 1 : tunables 0 0 0 : slabdata 67 67 0 mm_struct 82 95 832 19 4 : tunables 0 0 0 : slabdata 5 5 0 files_cache 104 161 704 23 4 : tunables 0 0 0 : slabdata 7 7 0 signal_cache 163 187 960 17 4 : tunables 0 0 0 : slabdata 11 11 0 sighand_cache 145 165 2112 15 8 : tunables 0 0 0 : slabdata 11 11 0 task_xstate 118 140 576 28 4 : tunables 0 0 0 : slabdata 5 5 0 task_struct 128 165 5808 5 8 : tunables 0 0 0 : slabdata 33 33 0 anon_vma 731 896 32 128 1 : tunables 0 0 0 : slabdata 7 7 0 shared_policy_node 85 85 48 85 1 : tunables 0 0 0 : slabdata 1 1 0 numa_policy 170 170 24 170 1 : tunables 0 0 0 : slabdata 1 1 0 idr_layer_cache 240 240 544 30 4 : tunables 0 0 0 : slabdata 8 8 0 kmalloc-8192 27 32 8192 4 8 : tunables 0 0 0 : slabdata 8 8 0 kmalloc-4096 291 344 4096 8 8 : tunables 0 0 0 : slabdata 43 43 0 kmalloc-2048 225 240 2048 16 8 : tunables 0 0 0 : slabdata 15 15 0 kmalloc-1024 366 432 1024 16 4 : tunables 0 0 0 : slabdata 27 27 0 kmalloc-512 536 544 512 16 2 : tunables 0 0 0 : slabdata 34 34 0 kmalloc-256 406 528 256 16 1 : tunables 0 0 0 : slabdata 33 33 0 kmalloc-128 503 576 128 32 1 : tunables 0 0 0 : slabdata 18 18 0 kmalloc-64 3467 3712 64 64 1 : tunables 0 0 0 : slabdata 58 58 0 kmalloc-32 1520 1920 32 128 1 : tunables 0 0 0 : slabdata 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