在Linux中用ps命令看到的每个进程使用的内存是该进程所用到的内存之和,是假定当系统只有该进程运行时,该进程使用的内存。
之所以用ps看的内存报告是“错误的”是因为Linux系统对共享库的处理。系统只装载一份共享库代码,所有使用该库的进程都可以在自己的地址空间中访问到该共享库代码。
比如ps命令报告每个Apache进程可能都用了10M内存,而实际上每个进程的边际代价为1M内存,其余9M是在所有的Apache进程之间共享的。
Understanding memory usage on Linux
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).
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