PHP/MySql/Jquery script vs RAM - php

Hi guys I have a question about server's RAM and PHP/MySQL/Jquery script.
Can scripts kills RAM when script doesn't take extra RAM? (I know it could happen when RAM grow up to maximum or because of memory limit. But it isn't this case.)
I'm testing script but everytime when I do that RAM goes quickly down.
Script doesn't show error for memory limit and it's correctly loading all data. When I don't test script RAM is still down.
In database is a couple records - maybe 350 records in 9 tables (the bigges tables has 147 records).
(I haven't any logs just simply (really simple) graph for running server.)
Thank for your time.

If you're not getting errors in your PHP error log about failing to allocate memory, and you're not seeing other problems with your server running out of RAM (such as extreme performance degradation due to memory pages being written to disk for demand paging) you probably don't need to really worry about it. Any use case where a web server uses up that much memory in a single request is going to be pretty rare.
As for trying to profile the actual memory usage, trying to profile it by watching something like the task manager is going to be pretty unreliable. Most PHP scripts are going to complete in milliseconds, which isn't enough time for the memory allocations to really even register in the task manager.
Even if you have a more reliable method of profiling the memory usage (I don't recall if PHP has built in functions for this, but probably does), bear in mind that memory usage is going to flucuate tremendously for reasons that may be hard to understand. PHP in particular is very high level: you can open a database connection, which involves everything down to the OS opening network sockets, creating internal datastructures, caching things, and much more all in a single line of code. The script may allocate many megabytes of memory for such a thing for a single database row, but may then deallocate it a millisecond later.
Those database sizes are pretty neglibible. Depending on the row sizes it's possibly under a megabyte of data which is a tiny drop in a bucket for memory on anything remotely modern. Don't worry about memory usage for something like that. Only if you see your scripts failing and your error log reports running out of memory should you really worry about it.

Related

Optimal memory for page loading in hosted environment?

In PHP, shared hosting environment, what shall be an optimal memory consumption to load a page. My current PHP script is consuming 3,183,440 bytes of memory. What shall I consider a good memory usage, to entertain say, 10000 users parallely?
Please be detailed, as I am a novice in optimization part.
Thanks in advance
3MB isn't that bad - keep in mind that parts of PHP are shared, depending on which server is used (IIS, ngx, apache etc.) you can specify pools and clusters as well when having to scale up.
But the old adage testing is knowledge goes well here, try load tests on the site, concurrent 10 -> 100 -> 1000 connections and look at the performance metrics, it wil give you more insight on how much memory is required.
For comparison, the site I normally work on has an average of 300+ users concurrently online and the memory usage is just under 600MB, however I run certain processes locally it will easily use up 16MB.

Drawbacks of increasing PHP memory limit

Recently my app started throwing fatal errors regarding exhaustion of the max allowed memory. After some research, I found out that the limit is set in the .htaccess file and it sets to 64m.
The tried allocation is of around 80MB, and we are able to provide these resources, but I wanted to ask the community if increasing the value of this variable is a good solution to the problem.
Thank you very much
The answer depends on what your script is doing :) It sounds like the increase in your case was quite small (from 64 to 80 MB, I'd recommend sticking to the powers of two though and upping it to 128MB btw.) so it shouldn't make much of a difference for modern machines. But to know if it was the right thing to do you need to find out why you needed more memory.
If your processing simply requires more memory (eg. you're processing uploaded files in memory, or decoding big json or xml structures or doing something else which is memory intensive) upping your limit is ok and common.
If however your application has memory leaks or is written in an inefficient way then upping the memory limit is just masking the problem and not solving it. You'll likely keep running into this issue and end up upping the memory all the time which is not feasible.
If you don't know what caused the sudden increase in memory consumption I'd recommend profiling your application using e.g. xhprof. You can also look at the last few changes to your app and see what might have caused it. If you can justify it then give your script more memory, otherwise try optimising your code first.
PHP is typically deployed in a way that a PHP process serves multiple request after another. During a single request a script can now allocate memory. At the end this memory will be free'd. So far so good. Now most operating systems are built in a way to keep memory, which was allocated bound to a process, even when freed. The assumption there is that a programmed which required memory once will need the amount again and it's cheaper to keep it available to the process than taking it back. Thus in a PHP deployment it might happen, that one request takes a lot of memory and then the memory is bound to the process and not available to the system anymore. Additionally it's a possible indication for a bug if some process takes a lot more memory than anticipated. So for those two things the memory_limit serves as safety net.
If your application needs more memory it's generally fine to increase the limit. The absolute maximum value is dependant on the system (available RAM / number of worker processes might be a rough formula, rough as it doesn't include other memory needed) Typically you should only increase by an amount needed.
Of course when changing this you have to remember when moving to other systems. Also typically less memory usage means faster execution thus you should try to see if you can optimise your code.
Side note: I purposely simplified the memory model above, ignoring virtual memory pages and how operating systems optimize there

Laravel4 memory consumption concerns

Case
Currently I am developing an application using Laravel 4. I installed profiler to see the stats about my app. This is the screenshot:
Questions
You can see that it consumes 12.25 MB memory for each request (very simple page) in my vagrant (Ubuntu 64 bit + Nginx + PHP 5.3.10+ MySQL). Do you think this is too much ? This means If I have 100 concurrent connections, the memory consumption will be about 1 GB. I think this is too much but what do you think ?
It loads 237 files for each request. Do you think this is too much ?
When I deploy this app to the my server (Centos 6.4 with Apache + PHP 5.5.3 with Zend OPcache + MySQL) the memory consumption decreases dramatically. This is the screenshot from the server:
What do you think about this difference between my mac and the server ?
No, you don't really need to worry about this.
12MB is not really a large amount for a PHP program. And 100 concurrent connections is a lot.
To put it into context, assume your PHP page takes half a second to run, that would mean you'd need to have 12000 page loads per minute to achieve a consistent 100 concurrent connections. That's a lot more traffic than any of my sites get, I can tell you that.
Of course, if your page takes longer than half a second to load, this number will come down quickly, and your 100 concurrent connections can become a possibility much more easily.
This is one reason why it's a really good idea to focus on performance‡ -- the quicker your program can finish running, the quicker it can free up its memory for the next visitor. In fact unless you have a really major memory usage problem (which you don't), performance is probably more important in this context than the amount of memory being used.
In any case, if you do have 100 concurrent connections, you're likely to get issues with your server software before you have them with PHP. Apache has a default limit to the max number of connections, and it is a lot lower than 100. (you can raise it, of course, but if you really are getting that kind of traffic, you'll likely be wanting more servers anyway)
As for the 12M memory usage, you're not really ever likely to get much less than that for a PHP program. PHP needs a chunk of memory just in order to run in the first place, and the framework will need a chunk too, so most of your 12M will be due to that. This means that although your small program may be using 12M, it does not follow that a larger program would use twice as much. So you probably don't need to worry too much about it.
If you do have high traffic, and performance issues as a result, there are various ways you can mitigate the problem. The main one is by using caching. PHP 5.5 comes with an OpCache module built-in, which will cache your programs for you so that it doesn't have to do all the bootstrap work such as loading all the files every time. For some systems, this can have a dramatic impact on performance.
There are also other layers of caching you can use, such as a server-level page cache like Varnish, which will cache your static pages so that PHP doesn't even need to be called if the page content hasn't changed.
(‡ of course there are other reasons for focussing on performance too, like keeping your visitors happy)

Php resource freeing

My client has their web hosting account on a shared server and their account has been suspended because is was "causing critical server overload". I have looked at the code and it is functionally programmed php that uses a lot of database queries. I have looked through and most of them are "SELECT *". This database has tables with a 10 or more rows and more than 1000 records.
I was wondering if the cause could be all the sql queries not being freed up, but I'm not sure when "script execution" finishes. Is it after the function has finished execution, or the whole page has been rendered? Could it be the size of the tables (structure or records)? Does anyone have any other ideas?
It really depends on the kind of package your client was on, what type of script custom coded or a standard script like wordpress.
Causing critical server overload - Could be a multitude of things:
High Memory usage: The script is not using a singleton model or its assigning huge amounts of data to arrays, variables or including lots of files. basically bad design & code smell.
High CPU: Insanely long scripts, Long iterated loops with complex calculations in between or infinite loops (sockets) ect on each page view.
High Network Traffic: Screen Scappers like a crawler thats requesting high amounts of traffic from other site or basically scripts that grab external content ALOT, or something like a torrent tracker.
High Disk usage: Constantly bombarding the servers IO stack (Writing and reading to the disk constantly)
A script with lots of database query's could fall into: High Disk usage (reading)+High Memory usage (iterating the result)+High CPU (doing stuff with the result))
You should use a tool to performance profile the script locally: xDebug or PQP, and find out whats really happening.
If your client is serious about there site then they should invest in a VPS.
Make sure you are closing your SQL connections properly. If you are doing alot of queries at once it might be more efficient to leave the connection open for longer periods. Or if you are not closing them after each query maybe try doing this. I must say 10 tables is not a lot and would it would suprise me that this is overloading the shared server.

What is the bottleneck when it's not Memory, CPU or IO?

I have a PHP class that selects data about a file from a MySQL database, processes that data in PHP and then outputs the final data to the command line. Then it moves onto the next file within a foreach loop. ( later I'll be inserting this data into another table ... but that's not important now )
I want to make the processing as fast as possible.
When I run the script and monitor my system using top or iostat:
my cpus are never less than 65% idle ( 4 core EC2 instance )
the PHP script sits at about 45%
mysqld sits at about 8%
my memory usage never passes ~1.5GB ( 8GB of ram total )
there is very little disk IO
What other bottlenecks could be preventing this process from running faster and using the available CPU and Memory?
EDIT 1:
This does not need to be a procedural process and I've designed it to parallelize the processing if necessary. If I can speed it up some, it'd be simpler to leave it as procedural processing.
I've monitored the disk I/O using iostat -x 1 and there is very little.
I need to speed this up in general because it will ultimately be used to process hundreds of millions of files and I'd like it to be as fast as possible as it's part of a larger processing step.
Well, it may be because a single PHP process can only run on one core at a time and you're not loading up your system to the point where it will have four concurrent jobs running continuously.
Example: if PHP were the only thing running on that box, it was inherently tied to a single core per "job" and only one request at a time were being made, I'd fully expect a CPU load of around 25% despite the fact it's already going as fast as it possibly can.
Of course, once that system started ramping up to the point where there are continuously four PHP scripts running, you may find higher CPU utilisation.
In my opinion, you should only really worry about a performance problem if it's an actual problem (such as not being able to keep up with incoming requests). Optimisation just because you want it using more CPU and/or memory resources seems to be looking at it the wrong way around. I would just get it running as fast as possible without worrying about the actual resources used.
If you want to process hundreds of millions of files as fast as possible (as per your update) and PHP is core-bound, you should think about horizontal scaling.
In other words, if the processing of a single file is independent, you can simply start two or three PHP processes and have them process one file each. That will be more likely to get them running on distinct cores.
You can even scale across physical machines if necessary though that's likely to introduce network latency on the DB access (unless the DB is replicated across all the machines as well).
Without a fair bit more detail, the options I can provide will be mostly generic ones.
The first problem you need to fix is the word "bottleneck", because it means everything and nothing.
It conjurs this image of some sort of constriction in the flow of whatever the machine seems to do which is so fast it must be like water running through pipes.
Computation isn't like that.
I find it helps to see how a very simple, slow, computer works, namely Harry Porter's Relay Computer.
You can watch it chug along, at a very slow clock rate, executing every little step within each instruction and finishing them before it starts the next.
(Now, obviously, machines these days are multi-core, pipelined, multi-level cache, blah blah. That's all fine, but that makes you think computation is like water flowing, and that prevents you from understanding software performance.)
Think of any computer and software as just like in that relay machine, except on a scale of nanoseconds, not seconds.
When a computer is calculating in a program, it is executing instructions one after the other. Call that "X".
When a program wants to read or write some bits to external hardware, it has to request that hardware to start, and then it has to find a way to kill time until the result is ready.
Call that "y".
It could be an idle loop, or letting another "thread" run, etc.
So the execution of a program looks like
XXXXXyyyyyyyXXXXXXXXyyyyyyy
If there are more "y"s in there than "X"s we tend to call it "I/O bound".
If not, we might call it "compute bound".
Either way, it's just a matter of proportion of time spent.
If you say it's "memory bound", that's just like I/O except it could be different external hardware.
It still occupies some fraction of the overall sequential timeline.
Now for any given task, there are infinitely many programs that could be written to do it. Some of them will get done in fewer steps than all the others.
When you want performance, you want to get as close as possible to writing one of those programs.
One way to do it is to find "X"s and "y"s that you can get rid of, and get rid of as many as possible.
Now, within a single thread, if you pick an "X" or "y" at random, how can you tell if you can get rid of it?
Find out what it's purpose is!
That "X" or "y" represents a moment in the execution sequence of the program, and if you look at the state of the program at that time, and look at the source code, you will be able to figure out why that moment is being spent.
Do that a few times.
As soon as you see two moments in time having a similar less-than-absolutely-necessary purpose,
there are probably a lot more like them, and you've found something you can get rid of.
If you do so, the program will no longer be spending that time.
That's the basic idea behind this method of performance tuning.
Here's an example where that method was used, over several iterations, to remove over 97% of the time spent in a program.
Not all programs are that far away from optimal.
(Some are much farther.)
Many programs just have to do a certain amount of "X"s or "y"s, and there's no way around it.
Nevertheless, it is often very surprising how much room you can find for speedup in otherwise perfectly good code - provided - you forget about "bottlenecks" and look for steps that it's doing, over time, that could be removed or done better.
It's easy.
I suspect you're spending most of your time communicating with MySQL and reading the files. How are you determining that there's very little IO? Communicating with MySQL is going to be over the network, which is very slow compared to direct memory access. Same with reading files.
Looks like CPU is your bottleneck. Or to be more precise a single core is your bottle neck.
100% utilisation of a single core will result in a "25% CPU utilisation" if the other three cores are idle.
Your numbers are consistent with a php script running at 100% on a single core, with 5 to 10% utilization on the other three cores.
Sorry to resurrect an old thread, but thought this might help someone out.
I had a similar problem and it had to do with a command line script that was throwing numerous 'Notice' warnings. That somehow led to it performing slowly and using less than 10% of the cpu. This behavior only showed up on migrating from MacOS X to Ubuntu, as the default in OSX seems to be to suppress the wornings. Once I fixed the offending code it performed much better, with processes using around 100% cpu consistently.
As the other guy said, sorry to resurrect an old thread, but this may help somebody.
I had the same issue: running a bunch of processes in parallel, all using MySQL. The machine was slow with no identifiable bottlenecks: cpu, memory nor disk.
It turns out that the most probable cause of my problems was that MySQL internal threads were hung on the same semaphore most of the time. Switching from vanilla MySQL 5.5 to MariaDB 10.0 fixed the problem.
Also, to ensure that my machine is always running at full capacity while not being flooded, I have created a Perl script raspawn.pl (on GitHub).
You can read the full sad story here.

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