I've got a rather large PHP web app which gets its products from numerous others suppliers through their API's, usually responding with a large XML to parse. Currently there are 20 suppliers but this is due to rise even further.
Our current set up uses multi curl to make the requests and this takes about 30-40 seconds to complete and is too long. The script runs in the background whilst the front end polls the database looking for results and then displays them as they come in.
To improve this process we were thinking of using a job server to run in the background, each supplier request being a separate job. We've seen beanstalkd and Gearman being mentioned.
So are we looking in the right direction, as in, is a job server the right way to go? We're looking at doing some promotion soon so we may get 200+ users searching 30 suppliers at the same time so the right choice needs to scale well if we have to load balance.
Any advice is great fully received.
You can use Beanstalkd, as you can customize the priority of jobs and the TTR time-to-resolve, default is 60 seconds, but for your scenario you must increase it. There is a nice admin console panel for Beanstalkd.
You should also leverage the multi Curl calls, so you should use parallel requests. In order to make use of Keep-alive you also need to maintain a pool of CURL handles and keep them warm. See high performance curl tips. You also need to tune Linux network stack.
If you run this in cloud, make sure you use multiple micro machines rather than one heavy machine as the throughput is better when you have multiple resources available.
Related
I have 3 codeigniter based application instances on two separate servers.
Server 1.
First instance is application, second instance is rest API, both use same database. ( I know there is no benefit to have two instances on same machine, other than cleanliness, and that is why I have it this way ).
Server 2.
This server holds only rest API with whole bunch of php data processing functions. I call this server worker because that is what it only does.
This server works as an endpoint for many API services I am connecting with.
So all this server does as first function is receive requests from application, sometimes it processes those requests before anything else.
Then sends requests to API service. Process is complete this session is over.
In short time API service responds with results where this server takes and processes the data then it sends the result to the application.
Application is at times heavy on amount of very simple sql queries, for the most part insert/update on single table. Amount of sent requests is kept to minimal as well, just because for the most part I send data as many requests in one. I call this bulk request.
What is very heavy is amount of responses I get, I can get up to a 1000 responses to one request within few seconds.( I can't minimize that, because I need every single one ), and then each response I get also is being followed by another two identical responses just to make sure I got it, which I threat as duplicate as soon as I can, and stopping that one process.
Then I process every response with php ( not too heavy just matching result arrays ) and post it to my rest API on the application server to update application tables.
Now when I run say 1 request that returns 1000 responses, application is processing data fine with correct results, but the server is pretty much not accessible in this time for other users.
Everything running on an (LAMP) Ubuntu 16.04 with mysql and apache.
Framework is latest codeigniter.
Currently my setup is...
...for the application server
2 vCPUs
4GB RAM
...for worker API server
1 vCPUs
1GB RAM
I know the server setup is very weak, and it bottlenecks for sure. But this was just for development stage.
Now I am moving into production and would like to hear opinions if you have any on how to best approach this.
I am a programmer first, then server administrator.
So I was debating switching to NGINX, I think I will definitely go with php-fpm, maybe MariaDB but I read of thread management is important. This app will not run heavy all the time probably 50/50 so I think just because of that I may not be able to set it to optimal for all times anyway, and may end up with not any better performance at the end.
Then probably will have to multiply servers and setup load balancing, also high availability.
Not sure about all this.
I don't think that just upgrading the servers to maximum will help tho. I can go all the way up too 64 GB RAM and 32 vCPUs per server.
Can I hear your opinions please?
Maybe share some experience?
Links to resources if you have some good ones?
Thank you very much. I hope you can help me.
Thank you.
None of your questions matter. Well, that is an exaggeration. Machines today are not enough different to worry about starting with the "best" on day one. Instead, implement something, run with it for a while, then see where your bottlenecks in order to decide what to do next.
Probably you won't have any bottlenecks for a long time.
I have a game running in N ec2 servers, each with its own players inside (lets assume it a self-contained game inside each server).
What is the best way to develop a frontend for this game allowing me to have near real-time information on all the players on all servers.
My initial approach was:
Have a common-purpose shared hosting php website polling data from each server (1 socket for each server). Because most shared solutions don't really offer permanent sockets, this would require me to create and process a connection each 5 seconds or so. Because there isn't cronjob with that granularity, I would end up using the requests of one unfortunate client to make this update. There's so many wrong's here, lets consider this the worst case scenario.
The best scenario (i guess) would be to create small ec2 instance with some python/ruby/php web based frontend, with a server application designed just for polling and saving the data from the servers on the website database. Although this should work fine, I was looking for some solution where I don't need to spend that much money (even a micro instance is expensive for such pet project).
What's the best and cheap solution for this?
Is there a reason you can't have one server poll the others, stash the results in a json file, then push that file to the web server in question? The clients could then use ajax to update the listings in near real time pretty easily.
If you don't control the game servers I'd pass the work on updating the json off to one of the random client requests. it's not as bad as you think though.
Consider the following:
Deliver (now expired) data to client, including timestamp
call flush(); (test to make sure the page is fully rendered, you may need to send whitespace or something to fill the buffer depending on how the webserver is configured. appending flush(); sleep(4); echo "hi"; to a php script should be an easy way to test.
call ignore user abort (http://php.net/manual/en/function.ignore-user-abort.php) so your client will continue execution regardless of what the user does
poll all the servers, update your file
Client waits a suitable amount of time before attempting to update the updated stats via AJAX.
Yes that client does end up with the request taking a long time, but it doesn't affect their page load, so they might not even notice.
You don't provide the information needed to make a decision on this. It depends on the number of players, number of servers, number of games, communication between players, amount of memory and cpu needed per game/player, delay and transfer rate of the communications channels, geographical distribution of your players, update rate needed, allowed movement of the players, mutual visibility. A database should not initially be part of the solution, as it only adds extra delay and complexity. Make it work real-time first.
Really cheap would be to use netnews for this.
I'm currently developing a php daemon for connecting and retreiving data from social networks like facebook and twitter. This script allready works but I have some concerns about it.
It's possible to create an infinite amount of accounts that the script has to process and (right now) it runs every 5 minutes to create a 'near' realtime experience. So my concern is that, when, let's say 5000 accounts, have been created and have to be monitored. The script slows down and maybe wil run longer than the 5 minute interval. Is there any way to work around this problem? And better, is there any good way (with php, possible with javascript) to create a better 'near' realtime experience?
Any advice will be great!
Thanks in advance
One option would be to spawn multiple daemons and share duties between them. Perhaps have single central job queue and have the daemons consume that. It's really a server-side issue and Javascript has very little to do with such tasks, as long it's not server-side JS.
If the number of monitored subjects is going into thousands, PHP is not really a viable choice since it's neither inherently multi-threaded nor does it have synchronization features. In mass monitoring scenarios, a dedicated server running a J2EE, .NET or a custom multithreaded application is pretty much a must.
for most sites you can retrieve a stream containing all that data(in real-time). For example:
1. twitter
site streams allows services,
such as web sites or mobile push
services, to receive real-time updates
for a large number of users without
any of the hassles of managing REST
API rate limits
2. Facebook
The Graph API supports real-time
updates to enable your application
using Facebook to subscribe to changes
in data from Facebook.
When using these streams you can process the streams in real-time and don't have to do no(nearly none) polling.
P.S: I would most definitely code this in node.js.
set the max execution time to zero and include it
enclose your script in a inite loop:
set_time_limit(0);
while(true){
/your code
}
You should however include some way to end the process gracefully.
Some popular ways to do this is by checking if a env var was set or if a specific file exists.
set_time_limit(0);
while(true){
/your code
if(file_exist(KILL_SWITCH_FILE))break;
}
Another approach would be setting a flag when(in a filem,in a sql database,...) that your script is running and removing it when your done.
That way you can check if another instance of your script is still running.
Greetings All!
I am having some troubles on how to execute thousands upon thousands of requests to a web service (eBay), I have a limit of 5 million calls per day, so there are no problems on that end.
However, I'm trying to figure out how to process 1,000 - 10,000 requests every minute to every 5 minutes.
Basically the flow is:
1) Get list of items from database (1,000 to 10,000 items)
2) Make a API POST request for each item
3) Accept return data, process data, update database
Obviously a single PHP instance running this in a loop would be impossible.
I am aware that PHP is not a multithreaded language.
I tried the CURL solution, basically:
1) Get list of items from database
2) Initialize multi curl session
3) For each item add a curl session for the request
4) execute the multi curl session
So you can imagine 1,000-10,000 GET requests occurring...
This was ok, around 100-200 requests where occurring in about a minute or two, however, only 100-200 of the 1,000 items actually processed, I am thinking that i'm hitting some sort of Apache or MySQL limit?
But this does add latency, its almost like performing a DoS attack on myself.
I'm wondering how you would handle this problem? What if you had to make 10,000 web service requests and 10,000 MySQL updates from the return data from the web service... And this needs to be done in at least 5 minutes.
I am using PHP and MySQL with the Zend Framework.
Thanks!
I've had to do something similar, but with Facebook, updating 300,000+ profiles every hour. As suggested by grossvogel, you need to use many processes to speed things up because the script is spending most of it's time waiting for a response.
You can do this with forking, if your PHP install has support for forking, or you can just execute another PHP script via the command line.
exec('nohup /path/to/script.php >> /tmp/logfile 2>&1 & echo $!'), $processId);
You can pass parameters (getopt) to the php script on the command line to tell it which "batch" to process. You can have the master script do a sleep/check cycle to see if the scripts are still running by checking for the process id's. I've tested up to 100 scripts running at once in this manner, at which point the CPU load can get quite high.
Combine multiple processes with multi-curl, and you should easily be able to do what you need.
My two suggestions are (a) do some benchmarking to find out where your real bottlenecks are and (b) use batching and cacheing wherever possible.
Mysqli allows multiple-statement queries, so you could definitely batch those database updates.
The http requests to the web service are more likely the culprit, though. Check the API you're using to see if you can get more info from a single call, maybe? To break up the work, maybe you want a single master script to shell out to a bunch of individual processes, each of which makes an api call and stores the results in a file or memcached. The master can periodically read the results and update the db. (Careful to rotate the data store for safe reading and writing by multiple processes.)
To understand your requirements better, you must implement your solution only in PHP? Or you can interface a PHP part with another part written in another language?
If you could not go for another language, try to perform this update maybe as php script that runs in the background and not through the apache.
You can follow Brent Baisley advice for a simple use case.
If you want to build a robuts solution, then you need to :
set up a representation of the actions in a table in database that will be your process queue;
set up a script that pop this queue and process your action;
set up a cron daemon that run this script every x.
This way you can have 1000 PHP scripts running, using your OS parallelism capabilities and not hanging when ebay is taking to to respond.
The real advantage of this system is that you can fully control the firepower you throw at your task by adjusting :
the number of request one PHP script does;
the order / number / type / priority of the action in the queue;
the number or scripts the cron daemon runs.
Thanks everyone for the awesome and quick answers!
The advice from Brent Baisley and e-satis works nicely, rather than executing the sub-processes using CURL like i did before, the forking takes a massive load off, it also nicely gets around the issues with max out my apache connection limit.
Thanks again!
It is true that PHP is not multithreaded, but it can certainly be setup with multiple processes.
I have created a system that resemebles the one that you are describing. It's running in a loop and is basically a background process. It uses up to 8 processes for batch processing and a single control process.
It is somewhat simplified because i do not have to have any communication between the processes. Everything resides in a database so each process is spawned with the full context taken from the database.
Here is a basic description of the system.
1. Start control process
2. Check database for new jobs
3. Spawn child process with the job data as a parameter
4. Keep a table of the child processes to be able to control the number of simultaneous processes.
Unfortunately it does not appear to be a widespread idea to use PHP for this type of application, and i really had to write wrappers for the low level functions.
The manual has a whole section on these functions, and it appears that there are methods for allowing IPC as well.
PCNTL has the functions to control forking/child processes, and Semaphore covers IPC.
The interesting part of this is that i'm able to fork off actual PHP code, not execute other programs.
I've a problem which is giving me some hard time trying to figure it out the ideal solution and, to better explain it, I'm going to expose my scenario here.
I've a server that will receive orders
from several clients. Each client will
submit a set of recurring tasks that
should be executed at some specified
intervals, eg.: client A submits task
AA that should be executed every
minute between 2009-12-31 and
2010-12-31; so if my math is right
that's about 525 600 operations in a
year, given more clients and tasks
it would be infeasible to let the server process all these tasks so I
came up with the idea of worker
machines. The server will be developed
on PHP.
Worker machines are just regular cheap
Windows-based computers that I'll
host on my home or at my workplace,
each worker will have a dedicated
Internet connection (with dynamic IPs)
and a UPS to avoid power outages. Each
worker will also query the server every
30 seconds or so via web service calls,
fetch the next pending job and process it.
Once the job is completed the worker will
submit the output to the server and request
a new job and so on ad infinitum. If
there is a need to scale the system I
should just set up a new worker and the
whole thing should run seamlessly.
The worker client will be developed
in PHP or Python.
At any given time my clients should be
able to log on to the server and check
the status of the tasks they ordered.
Now here is where the tricky part kicks in:
I must be able to reconstruct the
already processed tasks if for some
reason the server goes down.
The workers are not client-specific,
one worker should process jobs for
any given number of clients.
I've some doubts regarding the general database design and which technologies to use.
Originally I thought of using several SQLite databases and joining them all on the server but I can't figure out how I would group by clients to generate the job reports.
I've never actually worked with any of the following technologies: memcached, CouchDB, Hadoop and all the like, but I would like to know if any of these is suitable for my problem, and if yes which do you recommend for a newbie is "distributed computing" (or is this parallel?) like me. Please keep in mind that the workers have dynamic IPs.
Like I said before I'm also having trouble with the general database design, partly because I still haven't chosen any particular R(D)DBMS but one issue that I've and I think it's agnostic to the DBMS I choose is related to the queuing system... Should I precalculate all the absolute timestamps to a specific job and have a large set of timestamps, execute and flag them as complete in ascending order or should I have a more clever system like "when timestamp modulus 60 == 0 -> execute". The problem with this "clever" system is that some jobs will not be executed in order they should be because some workers could be waiting doing nothing while others are overloaded. What do you suggest?
PS: I'm not sure if the title and tags of this question properly reflect my problem and what I'm trying to do; if not please edit accordingly.
Thanks for your input!
#timdev:
The input will be a very small JSON encoded string, the output will also be a JSON enconded string but a bit larger (in the order of 1-5 KB).
The output will be computed using several available resources from the Web so the main bottleneck will probably be the bandwidth. Database writes may also be one - depending on the R(D)DBMS.
It looks like you're on the verge of recreating Gearman. Here's the introduction for Gearman:
Gearman provides a generic application
framework to farm out work to other
machines or processes that are better
suited to do the work. It allows you
to do work in parallel, to load
balance processing, and to call
functions between languages. It can be
used in a variety of applications,
from high-availability web sites to
the transport of database replication
events. In other words, it is the
nervous system for how distributed
processing communicates.
You can write both your client and the back-end worker code in PHP.
Re your question about a Gearman Server compiled for Windows: I don't think it's available in a neat package pre-built for Windows. Gearman is still a fairly young project and they may not have matured to the point of producing ready-to-run distributions for Windows.
Sun/MySQL employees Eric Day and Brian Aker gave a tutorial for Gearman at OSCON in July 2009, but their slides mention only Linux packages.
Here's a link to the Perl CPAN Testers project, that indicates that Gearman-Server can be built on Win32 using the Microsoft C compiler (cl.exe), and it passes tests: http://www.nntp.perl.org/group/perl.cpan.testers/2009/10/msg5521569.html But I'd guess you have to download source code and build it yourself.
Gearman seems like the perfect candidate for this scenario, you might even want to virtualize you windows machines to multiple worker nodes per machine depending on how much computing power you need.
Also the persistent queue system in gearman prevents jobs getting lost when a worker or the gearman server crashes. After a service restart the queue just continues where it has left off before crash/reboot, you don't have to take care of all this in your application and that is a big advantage and saves alot of time/code
Working out a custom solution might work but the advantages of gearman especially the persistent queue seem to me that this might very well be the best solution for you at the moment. I don't know about a windows binary for gearman though but i think it should be possible.
A simpler solution would be to have a single database with multiple php-nodes connected. If you use a proper RDBMS (MSql + InnoDB will do), you can have one table act as a queue. Each worker will then pull tasks from that to work on and write it back into the database upon completion, using transactions and locking to synchronise. This depends a bit on the size of input/output data. If it's large, this may not be the best scheme.
I would avoid sqlite for this sort of task, although it is a very wonderful database for small apps, it does not handle concurrency very well, it has only one locking strategey which is to lock the entire database and keep it locked until a sinlge transaction is complete.
Consider Postgres which has industrial strength concurrency and lock management and can handle multiple simultanious transactions very nicely.
Also this sounds like a job for queuing! If you were in hte Java world I would recommend a JMS based archictecture for your solution. There is a 'dropr' project to do something similar in php but its all fairly new so it might not be suitable for your project.
Whichever technoligy you use you should go for a "free market" solution where the worker threads consume available "jobs" as fast as they can, rather than a "command economy" where a central process allocates tasks to choosen workers.
The setup of a master server and several workers looks right in your case.
On the master server I would install MySQL (Percona InnoDB version is stable and fast) in master-master replication so you won't have a single point of failure.
The master server will host an API which the workers will pull at every N seconds. The master will check if there is a job available, if so it has to flag that the job has been assigned to the worker X and return the appropriate input to the worker (all of this via HTTP).
Also, here you can store all the script files of the workers.
On the workers, I would strongly suggest you to install a Linux distro. On Linux it's easier to set up scheduled tasks and in general I think it's more appropriate for the job.
With Linux you can even create a live cd or iso image with a perfectly configured worker and install it fast and easy on all the machines you want.
Then set up a cron job that will RSync with the master server to update/modify the scripts. In this way you will change the files in just one place (the master server) and all the workers will get the updates.
In this configuration you don't care of the IPs or the number of workers because the workers are connecting to the master, not vice-versa.
The worker job is pretty easy: ask the API for a job, do it, send back the result via API. Rinse and repeat :-)
Rather than re-inventing the queuing wheel via SQL, you could use a messaging system like RabbitMQ or ActiveMQ as the core of your system. Each of these systems provides the AMQP protocol and has hard-disk backed queues. On the server you have one application that pushes new jobs into a "worker" queue according to your schedule and another that writes results from a "result" queue into the database (or acts on it some other way).
All the workers connect to RabbitMQ or ActiveMQ. They pop the work off the work queue, do the job and put the response into another queue. After they have done that, they ACK the original job request to say "its done". If a worker drops its connection, the job will be restored to the queue so another worker can do it.
Everything other than the queues (job descriptions, client details, completed work) can be stored in the database. But anything realtime should be put somewhere else. In my own work I'm streaming live power usage data and having many people hitting the database to poll it is a bad idea. I've written about live data in my system.
I think you're going in the right direction with a master job distributor and workers. I would have them communicate via HTTP.
I would choose C, C++, or Java to be clients, as they have capabilities to run scripts (execvp in C, System.Desktop.something in Java). Jobs could just be the name of a script and arguments to that script. You can have the clients return a status on the jobs. If the jobs failed, you could retry them. You can have the clients poll for jobs every minute (or every x seconds and make the server sort out the jobs)
PHP would work for the server.
MySQL would work fine for the database. I would just make two timestamps: start and end. On the server, I would look for WHEN SECONDS==0