LinuxQuestions.org
Support LQ: Use code LQ3 and save $3 on Domain Registration
Go Back   LinuxQuestions.org > Articles > Technical
User Name
Password

Notices

By mlsx at 2006-12-12 08:24
This entry is for those people who have ever wondered, “Why the hell is a simple KDE text editor taking up 25 megabytes of memory?” Many people are led to believe that many Linux applications, especially KDE or Gnome programs, are “bloated” based solely upon what tools like ps report. While this may or may not be true, depending on the program, it is not generally true — many programs are much more memory efficient than they seem.

What ps reports The ps tool can output various pieces of information about a process, such as its process id, current running state, and resource utilization. Two of the possible outputs are VSZ and RSS, which stand for “virtual set size” and “resident set size”, which are commonly used by geeks around the world to see how much memory processes are taking up.

For example, here is the output of ps aux for KEdit on my computer:

USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
dbunker 3468 0.0 2.7 25400 14452 ? S 20:19 0:00 kdeinit:
kedit

According to ps, KEdit has a virtual size of about 25 megabytes and a resident size of about 14 megabytes (both numbers above are reported in kilobytes). It seems that most people like to randomly choose to accept one number or the other as representing the real memory usage of a process. I’m not going to explain the difference between VSZ and RSS right now but, needless to say, this is the wrong approach; neither number is an accurate picture of what the memory cost of running KEdit is.

Why ps is “wrong” Depending on how you look at it, ps is not reporting the real memory usage of processes. What it is really doing is showing how much real memory each process would take up if it were the only process running. Of course, a typical Linux machine has several dozen processes running at any given time, which means that the VSZ and RSS numbers reported by ps are almost definitely “wrong”. In order to understand why, it is necessary to learn how Linux handles shared libraries in programs.

Most major programs on Linux use shared libraries to facilitate certain functionality. For example, a KDE text editing program will use several KDE shared libraries (to allow for interaction with other KDE components), several X libraries (to allow it to display images and copy and pasting), and several general system libraries (to allow it to perform basic
operations). Many of these shared libraries, especially commonly used ones like libc, are used by many of the programs running on a Linux system. Due to this sharing, Linux is able to use a great trick: it will load a single copy of the shared libraries into memory and use that one copy for every program that references it.

For better or worse, many tools don’t care very much about this very common trick; they simply report how much memory a process uses, regardless of whether that memory is shared with other processes as well. Two programs could therefore use a large shared library and yet have its size count towards both of their memory usage totals; the library is being double-counted, which can be very misleading if you don’t know what is
going on.

Unfortunately, a perfect representation of process memory usage isn’t easy to obtain. Not only do you need to understand how the system really works, but you need to decide how you want to deal with some hard questions. Should a shared library that is only needed for one process be counted in that process’s memory usage? If a shared library is used my multiple processes, should its memory usage be evenly distributed among the
different processes, or just ignored? There isn’t a hard and fast rule here; you might have different answers depending on the situation you’re facing. It’s easy to see why ps doesn’t try harder to report “correct” memory usage totals, given the ambiguity.

Seeing a process’s memory map Enough talk; let’s see what the situation is with that “huge” KEdit process.
To see what KEdit’s memory looks like, we’ll use the pmap program (with the -d flag):

Address Kbytes Mode Offset Device Mapping
08048000 40 r-x– 0000000000000000 0fe:00000 kdeinit
08052000 4 rw— 0000000000009000 0fe:00000 kdeinit
08053000 1164 rw— 0000000008053000 000:00000 [ anon ]
40000000 84 r-x– 0000000000000000 0fe:00000 ld-2.3.5.so
40015000 8 rw— 0000000000014000 0fe:00000 ld-2.3.5.so
40017000 4 rw— 0000000040017000 000:00000 [ anon ]
40018000 4 r-x– 0000000000000000 0fe:00000 kedit.so
40019000 4 rw— 0000000000000000 0fe:00000 kedit.so
40027000 252 r-x– 0000000000000000 0fe:00000 libkparts.so.2.1.0
40066000 20 rw— 000000000003e000 0fe:00000 libkparts.so.2.1.0
4006b000 3108 r-x– 0000000000000000 0fe:00000 libkio.so.4.2.0
40374000 116 rw— 0000000000309000 0fe:00000 libkio.so.4.2.0
40391000 8 rw— 0000000040391000 000:00000 [ anon ]
40393000 2644 r-x– 0000000000000000 0fe:00000 libkdeui.so.4.2.0
40628000 164 rw— 0000000000295000 0fe:00000 libkdeui.so.4.2.0
40651000 4 rw— 0000000040651000 000:00000 [ anon ]
40652000 100 r-x– 0000000000000000 0fe:00000 libkdesu.so.4.2.0
4066b000 4 rw— 0000000000019000 0fe:00000 libkdesu.so.4.2.0
4066c000 68 r-x– 0000000000000000 0fe:00000 libkwalletclient.so.1.0.0
4067d000 4 rw— 0000000000011000 0fe:00000 libkwalletclient.so.1.0.0
4067e000 4 rw— 000000004067e000 000:00000 [ anon ]
4067f000 2148 r-x– 0000000000000000 0fe:00000 libkdecore.so.4.2.0
40898000 64 rw— 0000000000219000 0fe:00000 libkdecore.so.4.2.0
408a8000 8 rw— 00000000408a8000 000:00000 [ anon ]
…. (trimmed) …
mapped: 25404K writeable/private: 2432K shared: 0K

I cut out a lot of the output; the rest is similar to what is shown. Even without the complete output, we can see some very interesting things. One important thing to note about the output is that each shared library is listed twice; once for its code segment and once for its data segment. The code segments have a mode of “r-x–”, while the data is set to “rw—”. The Kbytes, Mode, and Mapping columns are the only ones we will care about, as the rest are unimportant to the discussion.

If you go through the output, you will find that the lines with the largest Kbytes number are usually the code segments of the included shared libraries (the ones that start with “lib” are the shared libraries). What is great about that is that they are the ones that can be shared between processes. If you factor out all of the parts that are shared between
processes, you end up with the “writeable/private” total, which is shown at the bottom of the output. This is what can be considered the incremental cost of this process, factoring out the shared libraries. Therefore, the cost to run this instance of KEdit (assuming that all of the shared libraries were already loaded) is around 2 megabytes. That is quite a
different story from the 14 or 25 megabytes that ps reported.

What does it all mean?
The moral of this story is that process memory usage on Linux is a complex matter; you can’t just run ps and know what is going on. This is especially true when you deal with programs that create a lot of identical children processes, like Apache. ps might report that each Apache process uses 10 megabytes of memory, when the reality might be that the marginal cost of each Apache process is 1 megabyte of memory. This information becomes critial when tuning Apache’s MaxClients setting, which determines how many
simultaneous requests your server can handle (although see one of my past postings for another way of increasing Apache’s performance).

It also shows that it pays to stick with one desktop’s software as much as possible. If you run KDE for your desktop, but mostly use Gnome applications, then you are paying a large price for a lot of redundant (but different) shared libraries. By sticking to just KDE or just Gnome apps as much as possible, you reduce your overall memory usage due to the reduced marginal memory cost of running new KDE or Gnome applications, which allows Linux to use more memory for other interesting things (like the file cache, which speeds up file accesses immensely).

Please note that this article is a copy of an article from the Virtual Threads Blog. Permalink is http://virtualthreads.blogspot.com/2006/02/understanding-memory-usage-on-linux.html

by vangelis on Wed, 2007-02-21 02:07
The article is great, thanks for clearing up many things.

One of them was that I couldn't find a single X text editor that would consume less memory than windows notepad. I really thought that it wasn't possible..no I see

by unksi on Sun, 2007-04-15 07:09
This article cleared it up a lot for me, thank you

by PhillipHuang on Wed, 2007-04-25 05:01
Very good article. Thanks a lot.

by haxpor on Fri, 2007-07-13 02:27
Great, very useful.
THANKS again.

by XavierP on Fri, 2007-07-13 06:28
I have added a note at the bottom of the article to ensure that it is clear that this is a copy of a post on the Virtual Threads blog. we should always attribute whenever this happens.

by BHABANIPRASADPATI on Mon, 2009-07-20 06:23
Wow... nice one.

by johnsfine on Mon, 2009-07-20 07:35
Quote:
Originally Posted by BHABANIPRASADPATI View Post
Wow... nice one.
Did you notice the thread was old and the linked content was effectively very old (nearly obsolete even when it was posted).

It is even more true now that there is no way of providing memory use statistics that are both simple and correct. But the reasons have evolved.

It is still true that a lot of code is shareable and there are no good statistics on how much it is shared. When a process uses shareable code, that gets entirely counted in that process's memory use statistics regardless of whether it is also counted in other processes' memory use statistics.

But that has become a very small share of virtual memory use, especially on 64 bit systems.

For example, I just looked at the biggest virtual memory users on one of the shared systems I'm logged into at the moment. The biggest one, at 419MB, is identified in top as /usr/bin/sealer but is actually /usr/bin/python (I assume python sets its argv[0] based on what python program it is running).

I've seen many questions online (without great answers) about what that process is and why it is using so much virtual memory. I'm curious myself but don't have time for a serious investigation.

On my system, I see that only 11MB of that 419MB is resident and only 4.6MB is shareable. The entire moderately loaded multi user Centos system is using only 128MB of swap space, which I expect is mainly other tasks, not that 419MB task. But anyway, after including all the .so mappings (which are in that shareable 4.6MB) plus all of the resident memory (which already double counts some of the .so mappings) plus all of the swapped out memory, most of the 419MB is still unaccounted for.

In many cases the large blocks of memory that are in virtual size but no where else are "demand zero" memory. I haven't taken the trouble to figure out where the invisible majority of the 419MB is in this example.

Maybe long ago, the level of actual sharing of .so mappings was a significant fraction of the cause of confusing memory statistics. Maybe long ago influencing that level of sharing, as suggested in that article, by sticking to one version/type of desktop software, was a significant factor in improving memory efficiency.

But now, physical and virtual memory sizes have both grown so much faster than .so mapping sizes, that those things really don't matter.

by icegood on Tue, 2010-09-14 07:51
Anyway it still doesn't understood why there is no program that shows number and amount of nonshared pages to at least estimate 'clear' usage of program

by suhas! on Mon, 2011-03-07 04:36
On my system, pmap's last line shows this..

pmap -d 4282 | grep mapped
mapped: 69368K writeable/private: 276K shared: 28K


shared is 28K.. So IIUC, shared + writeable/private should equal to mapped right? can you please explain about shared in above context?

Thanks and Regards,


  



All times are GMT -5. The time now is 09:21 AM.

Main Menu
Advertisement

Advertisement
My LQ
Write for LQ
LinuxQuestions.org is looking for people interested in writing Editorials, Articles, Reviews, and more. If you'd like to contribute content, let us know.
Main Menu
Syndicate
RSS1  Latest Threads
RSS1  LQ News
Twitter: @linuxquestions
identi.ca: @linuxquestions
Facebook: linuxquestions Google+: linuxquestions
Open Source Consulting | Domain Registration