I am writing an app and need to do something functionally similar to what url shortening websites do. I will be generating 6 character (case insensitive alphanumeric) random strings which would identify their longer versions of the link. This leads to 2176782336 possibilities ((10+26)^6). While assigning these strings, there are two approaches I can think about.
Approach 1: the system generates a random string at the runtime and checks for it uniqueness in the system, if it is not unique it tries again. and finally reaches a unique string somehow. But it might create issues if the user is "unlucky" maybe.
Approach 2: I generate a pool of some possible values and assign them as soon as they are needed, this however would make sure the user is always allocated a unique string almost instantly, while this could at the same time also mean, I would have to do plenty of computation in crons beforehand and will increase over the period of time.
While I already have the code to generate such values, a help on approach might be insightful as I am looking forward to a highly accelerated app experience. I could not find any comparative study on this.
Cheers!
What I do in similar situations is to keep N values queued up so that I can instantly assign them, and then when the queue's size falls below a certain threshold (say, .2 * N) I have a background task add another N items to the queue. It probably makes sense to start this background task as soon as your program starts (as opposed to generating the first N values offline and then loading them at startup), operating on the assumption that there will be some delay between startup and requests for values from the queue.
Related
I need to simulate "real traffic" on Web farm, by other words I need to generate high peaks but as well periods which less or even no HTTP requests (hits) at all. Reason for that is to test some atomized mechanisms for adding and reducing CPU and memory for Web servers itself (that is another story). That is why I need "totally random" sceneries when I have loads but as well period with zero or less traffic (so I can add or reduce compute power).
This is situation that I get now, as you can see I always have some avg load its always around some number of hits, even if I change 10 to 100 threads. Values (results) will always have some average value. There are no periods with less or more traffic which would be separated be +10 mints or so, only by few seconds.
Current situation
I would like to get "higher" variations by HITS/REQUESTS with some time breaks between it.
Situation that I want: i.stack.imgur.com/I4LhU.png
I tried several timers but no success and I do not want to use "Ultimate Thread Group" and similar components because I want test to be totaly randome and not predefined with time breaks and pause periods (thread delays). I would like test which will be totally randomized by it self - which could for example generate from 1 to 100 users per XY time.
This is my current Jmeter setup: i.stack.imgur.com/I4LhU.png
I do not know if I am missing some parameter in current setup or there is totally another way to do this.
Thanks a lot!
If this is something you really want (I strongly believe that the test needs to be repeatable, not random), I would suggest using Constant Throughput Timer for this. Despite the word "Constant" in its name you can use a Function or a Variable there, for instance __Random() and you will get different controllable "spikes" each iteration.
Moreover, you put a __P() function and amend its value via Beanshell Server while the test is running
I'm designing a large-scale project, and I think I see a way I could drastically improve performance by taking advantage of multiple cores. However, I have zero experience with multiprocessing, and I'm a little concerned that my ideas might not be good ones.
Idea
The program is a video game that procedurally generates massive amounts of content. Since there's far too much to generate all at once, the program instead tries to generate what it needs as or slightly before it needs it, and expends a large amount of effort trying to predict what it will need in the near future and how near that future is. The entire program, therefore, is built around a task scheduler, which gets passed function objects with bits of metadata attached to help determine what order they should be processed in and calls them in that order.
Motivation
It seems to be like it ought to be easy to make these functions execute concurrently in their own processes. But looking at the documentation for the multiprocessing modules makes me reconsider- there doesn't seem to be any simple way to share large data structures between threads. I can't help but imagine this is intentional.
Questions
So I suppose the fundamental questions I need to know the answers to are thus:
Is there any practical way to allow multiple threads to access the same list/dict/etc... for both reading and writing at the same time? Can I just launch multiple instances of my star generator, give it access to the dict that holds all the stars, and have new objects appear to just pop into existence in the dict from the perspective of other threads (that is, I wouldn't have to explicitly grab the star from the process that made it; I'd just pull it out of the dict as if the main thread had put it there itself).
If not, is there any practical way to allow multiple threads to read the same data structure at the same time, but feed their resultant data back to a main thread to be rolled into that same data structure safely?
Would this design work even if I ensured that no two concurrent functions tried to access the same data structure at the same time, either for reading or for writing?
Can data structures be inherently shared between processes at all, or do I always explicitly have to send data from one process to another as I would with processes communicating over a TCP stream? I know there are objects that abstract away that sort of thing, but I'm asking if it can be done away with entirely; have the object each thread is looking at actually be the same block of memory.
How flexible are the objects that the modules provide to abstract away the communication between processes? Can I use them as a drop-in replacement for data structures used in existing code and not notice any differences? If I do such a thing, would it cause an unmanageable amount of overhead?
Sorry for my naivete, but I don't have a formal computer science education (at least, not yet) and I've never worked with concurrent systems before. Is the idea I'm trying to implement here even remotely practical, or would any solution that allows me to transparently execute arbitrary functions concurrently cause so much overhead that I'd be better off doing everything in one thread?
Example
For maximum clarity, here's an example of how I imagine the system would work:
The UI module has been instructed by the player to move the view over to a certain area of space. It informs the content management module of this, and asks it to make sure that all of the stars the player can currently click on are fully generated and ready to be clicked on.
The content management module checks and sees that a couple of the stars the UI is saying the player could potentially try to interact with have not, in fact, had the details that would show upon click generated yet. It produces a number of Task objects containing the methods of those stars that, when called, will generate the necessary data. It also adds some metadata to these task objects, assuming (possibly based on further information collected from the UI module) that it will be 0.1 seconds before the player tries to click anything, and that stars whose icons are closest to the cursor have the greatest chance of being clicked on and should therefore be requested for a time slightly sooner than the stars further from the cursor. It then adds these objects to the scheduler queue.
The scheduler quickly sorts its queue by how soon each task needs to be done, then pops the first task object off the queue, makes a new process from the function it contains, and then thinks no more about that process, instead just popping another task off the queue and stuffing it into a process too, then the next one, then the next one...
Meanwhile, the new process executes, stores the data it generates on the star object it is a method of, and terminates when it gets to the return statement.
The UI then registers that the player has indeed clicked on a star now, and looks up the data it needs to display on the star object whose representative sprite has been clicked. If the data is there, it displays it; if it isn't, the UI displays a message asking the player to wait and continues repeatedly trying to access the necessary attributes of the star object until it succeeds.
Even though your problem seems very complicated, there is a very easy solution. You can hide away all the complicated stuff of sharing you objects across processes using a proxy.
The basic idea is that you create some manager that manages all your objects that should be shared across processes. This manager then creates its own process where it waits that some other process instructs it to change the object. But enough said. It looks like this:
import multiprocessing as m
manager = m.Manager()
starsdict = manager.dict()
process = Process(target=yourfunction, args=(starsdict,))
process.run()
The object stored in starsdict is not the real dict. instead it sends all changes and requests, you do with it, to its manager. This is called a "proxy", it has almost exactly the same API as the object it mimics. These proxies are pickleable, so you can pass as arguments to functions in new processes (like shown above) or send them through queues.
You can read more about this in the documentation.
I don't know how proxies react if two processes are accessing them simultaneously. Since they're made for parallelism I guess they should be safe, even though I heard they're not. It would be best if you test this yourself or look for it in the documentation.
I am using shared variables on perl with use threads::shared.
That variables can we modified only from single thread, all other threads are only 'reading' that variables.
Is it required in the 'reading' threads to lock
{
lock $shared_var;
if ($shared_var > 0) .... ;
}
?
isn't it safe to simple verification without locking (in the 'reading' thread!), like
if ($shared_var > 0) ....
?
Locking is not required to maintain internal integrity when setting or fetching a scalar.
Whether it's needed or not in your particular case depends on the needs of the reader, the other readers and the writers. It rarely makes sense not to lock, but you haven't provided enough details for us to determine what your needs are.
For example, it might not be acceptable to use an old value after the writer has updated the shared variable. For starters, this can lead to a situation where one thread is still using the old value while the another thread is using the new value, a situation that can be undesirable if those two threads interact.
It depends on whether it's meaningful to test the condition just at some point in time or other. The problem however is that in a vast majority of cases, that Boolean test means other things, which might have already changed by the time you're done reading the condition that says it represents a previous state.
Think about it. If it's an insignificant test, then it means little--and you have to question why you are making it. If it's a significant test, then it is telltale of a coherent state that may or may not exist anymore--you won't know for sure, unless you lock it.
A lot of times, say in real-time reporting, you don't really care which snapshot the database hands you, you just want a relatively current one. But, as part of its transaction logic, it keeps a complete picture of how things are prior to a commit. I don't think you're likely to find this in code, where the current state is the current state--and even a state of being in a provisional state is a definite state.
I guess one of the times this can be different is a cyclical access of a queue. If one consumer doesn't get the head record this time around, then one of them will the next time around. You can probably save some processing time, asynchronously accessing the queue counter. But here's a case where it means little in context of just one iteration.
In the case above, you would just want to put some locked-level instructions afterward that expected that the queue might actually be empty even if your test suggested it had data. So, if it is just a preliminary test, you would have to have logic that treated the test as unreliable as it actually is.
Say, my application has n number of threads trying to read the same collection object, say a List. Will there be any race-codition or dead-lock or any similar problems ? In other words, Is it necessary to lock the List for read only operation ?
It totally depends on you whether you want to restrict the number of users or not. Normally if you see excel files in Windows, when it is shared across network, a maximum of 10 people can open it for reading at a time. This number can be increased to any number or for that matter there need not be any restriction at all. It is your wish as a programmer whether you want to restrict or not. The only thing you need to keep in mind is that if the file is on a server and if 1 million read requests are coming every second, if there is no restriction imposed, it is likely that your system will slow down and it will not be able to serve anyone. Instead if you impose locking say that only 100 users can read it at a time, you can be sure that your system will not be overloaded. This is a real time scenario I am explaining considering the worst case.
But If you are asking it only for learning sake, I would say it is not required. If n number of users are opening the same file for reading, ideally speaking you can give access to all the n users to read the collection object. No synchronisation mechanism is needed. When there is no synchronisation there will be no dead lock or anything.
Hope this removes your confusion. Thanks.
not necessary unless the read operation causes internal status change of the collection object.
I'm looking for a design pattern that would fit my application design.
My application processes large amounts of data and produces some graphs.
Data processing (fetching from files, CPU intensive calculations) and graph operations (drawing, updating) are done in seperate threads.
Graph can be scrolled - in this case new data portions need to be processed.
Because there can be several series on a graph, multiple threads can be spawned (two threads per serie, one for dataset update and one for graph update).
I don't want to create multiple progress bars. Instead, I'd like to have single progress bar that inform about global progress. At the moment I can think of MVC and Observer/Observable, but it's a little bit blurry :) Maybe somebody could point me in a right direction, thanks.
I once spent the best part of a week trying to make a smooth, non-hiccupy progress bar over a very complex algorithm.
The algorithm had 6 different steps. Each step had timing characteristics that were seriously dependent on A) the underlying data being processed, not just the "amount" of data but also the "type" of data and B) 2 of the steps scaled extremely well with increasing number of cpus, 2 steps ran in 2 threads and 2 steps were effectively single-threaded.
The mix of data effectively had a much larger impact on execution time of each step than number of cores.
The solution that finally cracked it was really quite simple. I made 6 functions that analyzed the data set and tried to predict the actual run-time of each analysis step. The heuristic in each function analyzed both the data sets under analysis and the number of cpus. Based on run-time data from my own 4 core machine, each function basically returned the number of milliseconds it was expected to take, on my machine.
f1(..) + f2(..) + f3(..) + f4(..) + f5(..) + f6(..) = total runtime in milliseconds
Now given this information, you can effectively know what percentage of the total execution time each step is supposed to take. Now if you say step1 is supposed to take 40% of the execution time, you basically need to find out how to emit 40 1% events from that algorithm. Say the for-loop is processing 100,000 items, you could probably do:
for (int i = 0; i < numItems; i++){
if (i % (numItems / percentageOfTotalForThisStep) == 0) emitProgressEvent();
.. do the actual processing ..
}
This algorithm gave us a silky smooth progress bar that performed flawlessly. Your implementation technology can have different forms of scaling and features available in the progress bar, but the basic way of thinking about the problem is the same.
And yes, it did not really matter that the heuristic reference numbers were worked out on my machine - the only real problem is if you want to change the numbers when running on a different machine. But you still know the ratio (which is the only really important thing here), so you can see how your local hardware runs differently from the one I had.
Now the average SO reader may wonder why on earth someone would spend a week making a smooth progress bar. The feature was requested by the head salesman, and I believe he used it in sales meetings to get contracts. Money talks ;)
In situations with threads or asynchronous processes/tasks like this, I find it helpful to have an abstract type or object in the main thread that represents (and ideally encapsulates) each process. So, for each worker thread, there will presumably be an object (let's call it Operation) in the main thread to manage that worker, and obviously there will be some kind of list-like data structure to hold these Operations.
Where applicable, each Operation provides the start/stop methods for its worker, and in some cases - such as yours - numeric properties representing the progress and expected total time or work of that particular Operation's task. The units don't necessarily need to be time-based, if you know you'll be performing 6,230 calculations, you can just think of these properties as calculation counts. Furthermore, each task will need to have some way of updating its owning Operation of its current progress in whatever mechanism is appropriate (callbacks, closures, event dispatching, or whatever mechanism your programming language/threading framework provides).
So while your actual work is being performed off in separate threads, a corresponding Operation object in the "main" thread is continually being updated/notified of its worker's progress. The progress bar can update itself accordingly, mapping the total of the Operations' "expected" times to its total, and the total of the Operations' "progress" times to its current progress, in whatever way makes sense for your progress bar framework.
Obviously there's a ton of other considerations/work that needs be done in actually implementing this, but I hope this gives you the gist of it.
Multiple progress bars aren't such a bad idea, mind you. Or maybe a complex progress bar that shows several threads running (like download manager programs sometimes have). As long as the UI is intuitive, your users will appreciate the extra data.
When I try to answer such design questions I first try to look at similar or analogous problems in other application, and how they're solved. So I would suggest you do some research by considering other applications that display complex progress (like the download manager example) and try to adapt an existing solution to your application.
Sorry I can't offer more specific design, this is just general advice. :)
Stick with Observer/Observable for this kind of thing. Some object observes the various series processing threads and reports status by updating the summary bar.