determine the MaxClient
決定 web server 效能一個最重要的因素就是記憶體的量,而藉由調整 MaxClient,可以避免 Apache 產生過多無用的 child process。這個數字到底要調到多少,老實說也沒有一個標準答案,網路上大家比較建議的算法都是用機器有的記憶體和每個 child process 的 size 去做粗估。但事實上,要估計 apache child process 的 size 也不是一件容易的事,如果你用 ps aux
這個指令去看,出來的 VSZ or RSS value,其實都會把 shared memory 重覆記算(詳細內容請參考: Understanding memory usage on Linux , Memory usage determination with the ps command ),所以後來我採用的作法是:先將 MaxClent 設成一個比較小的值 (e.g. 30),然後再定期去看 error log 是否有 run out of clients 的情形,如果有的話,就再幫 MaxClients 加個 5。
原文来自:http://brooky.cc/2011/06/30/practical-guide-on-setup-wordpress-on-amazon-ec2-free-tier/
disable “AllowOverride”
理論上,AllowOverride 會造成 Apache 在路徑的每一層去找找看是否有 .htaccess 這個 file。
例如說:如果 virtual host 的設定是:
DocumentRoot /www/htdocs AllowOverride all
那任何一個 /index.html 的 request, Apache 都會試著去找 /.htaccess, /www/.htaccess, and /www/htdocs/.htaccess.
所以除非必要,是可以將 AllowOverride 設成 None.
但如果你用了 wordpress Pretty Permalinks”這個功能,那就會需要 rewrite rule 的功能。在這種情況下,可以考慮將 AllowOverride 的設定直接寫在 config 檔裡。
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上文中的链接:Memory usage determination with the ps command
The ps command can also be used to monitor memory usage of individual processes.
The ps v PID command provides the most comprehensive report on memory-related statistics for an individual process, such as:
- Page faults
- Size of working segment that has been touched
- Size of working segment and code segment in memory
- Size of text segment
- Size of resident set
- Percentage of real memory used by this process
# ps v
PID TTY STAT TIME PGIN SIZE RSS LIM TSIZ TRS %CPU %MEM COMMAND
36626 pts/3 A 0:00 0 316 408 32768 51 60 0.0 0.0 ps v
The most important columns on the resulting ps report are described as follows:
- PGIN
- Number of page-ins caused by page faults. Since all I/O is classified as page faults, this is basically a measure of I/O volume.
- SIZE
- Virtual size (in paging space) in kilobytes of the data section of the process (displayed as SZ by other flags). This number is equal to the number of working segment pages of the process that have been touched times 4. If some working segment pages are currently paged out, this number is larger than the amount of real memory being used. SIZE includes pages in the private segment and the shared-library data segment of the process.
- RSS
- Real-memory (resident set) size in kilobytes of the process. This number is equal to the sum of the number of working segment and code segment pages in memory times 4. Remember that code segment pages are shared among all of the currently running instances of the program. If 26 ksh processes are running, only one copy of any given page of the ksh executable program would be in memory, but the ps command would report that code segment size as part of the RSS of each instance of the ksh program.
- TSIZ
- Size of text (shared-program) image. This is the size of the text section of the executable file. Pages of the text section of the executable program are only brought into memory when they are touched, that is, branched to or loaded from. This number represents only an upper bound on the amount of text that could be loaded. The TSIZ value does not reflect actual memory usage. This TSIZ value can also be seen by executing the dump -ov command against an executable program (for example, dump -ov /usr/bin/ls).
- TRS
- Size of the resident set (real memory) of text. This is the number of code segment pages times 4. This number exaggerates memory use for programs of which multiple instances are running. The TRS value can be higher than the TSIZ value because other pages may be included in the code segment such as the XCOFF header and the loader section.
- %MEM
- Calculated as the sum of the number of working segment and code segment pages in memory times 4 (that is, the RSS value), divided by the size of the real memory in use, in the machine in KB, times 100, rounded to the nearest full percentage point. This value attempts to convey the percentage of real memory being used by the process. Unfortunately, like RSS, it tends the exaggerate the cost of a process that is sharing program text with other processes. Further, the rounding to the nearest percentage point causes all of the processes in the system that have RSS values under 0.005 times real memory size to have a %MEM of 0.0.
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第二篇:http://virtualthreads.blogspot.com/2006/02/understanding-memory-usage-on-linux.html
这篇文章来自blogspot,一般情况下打不开,所幸我用Read it later,直接用广本模式,让他帮我打开了。HOHO,有点长,慢慢看:
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).