I am searching for efficient ways of communication across two Perl
scripts. I have two scripts; Script 1 generates some data. I want my
Script 2 to be able to access that information.
The easiest/dumbest
way is to write the data generated by Script 1 as a file and read it
later using Script 2. Is there any other way than this? Can I store
the data in memory and make it available to Script 2 (of course with
support from my Linux )? Meaning malloc some data by Script 1 and make
Script 2 able to access it.
There is no guarantee that Script 2 will be run after Script 1. So
there should be some way to free that memory using a watchdog timer.
Let me reveal some more context. I am running these scripts on a web-server using CGI-Perl. So at the click of a button Script 1 is run and it generates a html web-page. Now the user can add some inputs to to this generated web-page and click a button on this new page.Now Script 2 should be able to read the data on new web-page.I can post the data back to web-server again but a more efficient way is to keep a copy of generated page in server also and make it available to script 2. Now, I would like to avoid writing down the generated page as a file. I was thinking of storing it in memory
This depends somewhat on your usage... one large set of data? Many small messages? Di you canre at all about data persistance? Is it TOTALLY asynchronous?
Some of the options are:
For any but the most high performace web sites, the best approach is to write our the HTML pages to files!. Unless the intrer-process communication is benchmarked to be the botttleneck in performance, don't both with any of the non-file solutions (shared memory, cache, intermediate server).
Specifically for two CGI scripts on the same server, if you run them under mod_perl or some other arrangement which shares Perl interpreter between 2 CGI processes, you can develop a package to serve as cache, which -with its package level variable - would be preserved in memory by mod_perl as long as mod_perl is running and can thus be used by a writer CGI process and a reader CGI process to communicate. Of course the usual synchronization/deadlock and persistance issues associated with reader/writer need to be considered.
As an alternative, use Apache::Session sessions to store inter-session data.
As you noted, shared memory. For example use IPC::ShareLite, IPC::Cache, or this solution from perlmonks.
Also, please check Chapter 16 Recipe 12 "Sharing Variables in Different Processes" from O'Reilly's "Perl Cookbook" (no link since non-pirated versions aren't online anywhere I know of)
Use a permanent medium. A file is one option. A database is another.
For async, use an intermediate messaging system (MQ, Tibco, something more lightweight). Probably a bit of an overkill in this scenario but a valid option to be aware of. This one is likely to be pretty stablem solid and optmized, but possibly not free and less flexible/tailored.
Or roll your own simple messaging system server - it's not THAT complicated for very simple one you seem to need.
Listen on one port for requests from first process to store data, listen on another port for requests from consumer process to send you that data, store the data in a storage area in memory and purge it when it expires using alarms or separate watcher child process).
You've tagged your question as "cgi". Are they both CGI programs? In that case, they can just talk to each other by making HTTP requests.
However, you'll have to tell a lot more about why you are trying to do this and what you need to accomplish for us to help you. It's certainly easy for Perl programs to communicate with each other in some fashion, but that doesn't mean it's the right answer for you.
When you have complex requirements for interaction among CGI programs, you probably want to move to a web framework that handles a lot of those details for you. Catalyst might be where'd you want to start. There's even a book for it.
Related
We have a perl web interface that I am currently working on to slowly convert to using Dancer 2 and PSGI instead of our slow old plain vanilla CGI model.
In our old model, we stored everything in sessions -- the history of what the users did, the call stacks, the data inputs, ........ you get the idea.
We do not want to do it that way anymore so that we can keep the sessions small and efficient. BUT, we'd still like to log just what the users have been doing (that way when an error gets reported we can see what they did to get to the error, what input(s) they put in, etc).
I looked at Logging on Dancer2 documentation, but this doesn't seem to quite get to what we need - this would only record Dancer2 messages + what other messages I put in.
This one that I found Dancer2::Logger doesn't seem to quite cut it either.
What other libraries could I use to do what I need? I seriously doubt that perl does NOT have somethign that does this so...
Just off the top of my head, I can think of Log::log4perl and Log::Dispatch, though there are myriad others.
You can use them to establish your own log files, separate from dancer's log.
As for the best way, most logging interfaces have the same api for logging, but differ in run-time instantiation, and configuration syntax. So read the docs on a few of them and maybe try a couple out on for size.
I'm a newbie in web server administration. I've read multiple times that flask built-in web server is not designed for "production", and must be used only for tests and debug...
But what if my app touchs only a thousand users who occasionnaly send data to the server ?
If it works, when will I have to bother with the configuration of a more sophisticated web server ? (I am looking for approximative metrics).
In a nutshell, I would love to find what the builtin web server can do (with approx thresholds) and what it cannot.
Thanks a lot !
There isn't one right answer to this question, but here are some things to keep in mind:
With the right amount of horizontal scaling, it is quite possible you could keep scaling out use of the debug server forever. When exactly you would need to start scaling (or switch to using a "real" web server) would also depend on the environment you are hosting in, the expectations of the users, etc.
The main issue you would probably run into is that the server is single-threaded. This means that it will handle each request one at a time, serially. This means that if you are trying to serve more than one request (including favicons, static items like images, CSS and Javascript files, etc.) the requests will take longer. If any given requests happens to take a long time (say, 20 seconds) then your entire application is unresponsive for that time (20 seconds). This is only the default, of course: you could bump the thread counts (or have requests be handled in other processes), which might alleviate some issues. But once again, it can still be slow under a "high" load. What is considered a "high" load will be dependent on your application and the expectations of a maximum acceptable response time.
Another issue is security: if you are concerned at ALL about security (and not just the security of the data in the application itself, but the security of the box that will be running it as well) then you should not use the development server. It is not ready to withstand any sort of attack.
Finally, the development server could just fail outright. It is not designed to be used as a long-running process (days, weeks, months), and so it has not been well tested to work in this capacity.
So, yes, it has limitations. Yes, you could still conceivably use it in production. And yes, I would still recommend using a "real" web server. If you don't like the idea of needing to install something like Apache or Nginx, you can still go with a solution that is still as easy as "run a python script" by using some of the WSGI Standalone servers, which can run a server that is designed to be in production with something just as simple as running python run_app.py in the command line. You typically just need to create a 4-5 line python script to import and create the server object, point it to your Flask app, and run it.
gunicorn could be run with only the following on the command line, no extra script needed:
gunicorn myproject:app
...where "myproject" is the Python package that contains the app Flask object. Keep in mind that one of developers of gunicorn would probably recommend against this approach. See https://serverfault.com/questions/331256/why-do-i-need-nginx-and-something-like-gunicorn.
The OP has long-since moved on, but for those who encounter this question in the future I would just add that setting up an Apache server, even on a laptop, is free and pretty easy. It can be readily configured for as few or as many features as you want just by uncomment in or commenting out lines in the config file. There might be an even easier GUI method for doing that nowdays, but just editing the configs is simple.
Current implementation-
Divide the original file into files equal to the number of servers.
Ensure each server picks one file for processing.
Each server splits the file into 90 buckets.
Use ForkManager to fork 90 processes, each operating on a bucket.
The child processes will make the API calls.
Merge the output of child processes.
Merge the output of each server.
Stats-
The size of the content downloaded using the API call is 40KB.
On 2 servers, the above process for a 225k user file runs in 15 minutes. My aim is to finish a 10 million file in 30 minutes. (Hope this doesn't sound absurd!)
I contemplated using BerkeleyDB but, couldn't find how do I convert the BerkeleyDB file into normal ASCII file.
This sounds like a one-time operation to me. Although I don't understand the 30 minute limit, I have a few suggestions I know from experience.
First of all, as I said in my comment, your bottleneck will not be reading the data from your files. It will also not be writing the results back to a harddrive. The bottleneck will be in the transfer between your machines and the remote machines. Your setup sounds sophisticated, but that might not help you in this situation.
If you are hitting a webservice, someone is running that service. There are servers that can only handle a certain ammount of load. I have brought down the dev environment servers of a big logistics company with a very small load test I ran at night. Often, these things are equipped for long-term load, but not short, heavy load.
Since IT is all about talking to each other through various protocols, like web services or other APIs, you should also consider just talking to the people who run this service. If you have a business-relationship, that is easy. If not, try to find a way to reach them and to ask if their service is able to handle so many requests at all. You could end up with them excluding you permanently because to their admins it looks like you tried to DDOS them.
I'd ask them if you could send them the files (or an excerpt of the data, cut down to what is relevant for processing) so they can do the operations in batch on their side. That way, you remove the load for processing everything as web requests, and the time it takes to do these requests.
I'm thinking of moving some workflow logic from C# code to stored JS in MongoDB (for example, wen a user sends a message, a bunch or records is to be created in different collections, which right now I do in C#), but I'm concerned whether I would be able to debug that JS code if things don't work correctly.
There isn't a particular facility for that. One thing you could do is run some of that code in the mongo shell, which can execute exactly the same javascript as the server. The shell doesn't have a debugger but with its interactive prompt it would be much easier to try things, inspect variables, etc.
Personally I would not necessarily recommend moving code into the server. Note it is possible to send several write operations (such as inserts) in a row and then after sending several ask for a single acknowledgement. Thus that scenario is not necessarily slow even if there is some nontrivial network latency.
Alternatively you could run C# code on the same server as the mongod process and thereby get extremely low latency on turnarounds of requests. One way to do that would be to make a web server that is written in C# and encapsulates the logic suggested above.
I guess you can write some debug information into separate collection and see how things are going, but it seems to me that actual debugging is not possible.
Our shop has developed a few WEB/SMS/DB solution for a dozen client installations. The applications have some real-time performance requirements, and are just good enough to function properly. The problem is that the clients (owners of the production servers) are using the same server/database for customizations that are causing problems with the performance of the applications that we created and deployed.
A few examples of clients' customizations:
Adding large tables with many text datatypes for the columns that get cast to other data types in the queries
No primary keys, indexes, or FK constraints
Use of external scripts that use count(*) from table where id = x, in a loop from the script, to determine how to construct more queries later in the same script. (no bulk actions that the planner can optimize or just do everything in a single pass)
All new code files on the server are created/owned by root, with 0777 permissions
The clients don't take suggestions/criticism well. If we just go ahead and try to port/change the scripts ourselves, the old code can come back, clobbering any changes that we make! Or with out limited knowledge of their use cases, we break functionality while trying to optimize their changes.
My question is this: how can we limit the resources to queries/applications other that what we create and deploy? Are there any pragmatic options in scenarios like this? We prided ourselves in having an OSS solution, but it seems that it's become a liability.
We use PG 8.3 running on a range on Linux Distos. The clients prefer php, but shell scripts, perl, python, and plpgsql are all used on the system in one form or another.
This problem started about two minutes after the first client was given full access to the first computer, and it hasn't gone away since. Anytime someone whose priorities are getting business oriented work done quickly they will be sloppy about it and screw up things for everyone. That's just how things work, because proper design and implementation are harder than cheap hacks. You're not going to solve this problem, all you can do is figure out how to make it easier for the client to work with you than against you. If you do it right, it will look like excellent service rather than nagging.
First off, the database side. There's now way to control query resources in PostgreSQL. The main difficulty is that tools like "nice" control CPU usage, but if the database doesn't fit in RAM it may very well be I/O usage that is killing you. See this developer message summarizing the issues here.
Now, if in fact it's CPU the clients are burning through, you can use two techniques to improve that situation:
Install a C function that changes the process priority (example 1, example 2) and make sure whenever they run something it gets called first (maybe put it into their psql config file, there are other ways).
Write a script that looks for postmaster processes spawned by their userid and renice them, make it run often in cron or as a daemon.
It sounds like your problem isn't the particular query processes they're running, but rather other modifications they're making to the larger structure. There's only one way to cope with that: you have to treat the client like they're an intruder and use the approaches of that portion of the computer security field to detect when they screw things up. Seriously! Install an intrusion detection system like Tripwire on the server (there are better tools, that's just the classic example), and have it alert you when they touch anything. New file that's 0777? Should jump right out of a proper IDS report.
On the database side, you can't directly detect the database being modified usefully. You should do a pg_dump of the schema every day into a file (pg_dumpall -g and pg_dump -s, then diff that against the last one you delivered and again alert you when it's changed. If you manage that this well, the contact with the client turns into "we noticed you changed on the server...what is it you're trying to accomplish with that?" which makes you look like you're really paying attention to them. That can turn into a sales opportunity, and they may stop fiddling with things as much just knowing you're going to catch it immediately.
The other thing you should start doing immediately is install as much version control software as you can on each client box. You should be able to login to each system, run the appropriate status/diff tool for the install, and see what's changed. Get that mailed to you regularly too. Again, this works best if combined with something that dumps the schema as a component to what it manages. Not enough people use serious version control approaches on the code that lives in the database.
That's the main set of technical approaches useful here. The rest of what you've got is a classic consulting client management problem that's far more of a people problem than a computer one. Cheer up, it could be worse--FSM help you if you give them ODBC access and they discover they can write their own queries in Access or something simple like that.