we are facing a problem.
we have background requests that are downloading files constantly (up to 5MB each file). meanwhile, we have a UI that most navigations require REST calls.
we limited the number of background downloads so it won't suffocate the operationQueue that RESTkit uses.
when several files are downloaded in background, we see the network usage with 1->2 MB (which is understandable).
The problem is: the user navigates through the app, and each navigation calls a quick REST call that should return very little data. but because of the background downloads, the UI call is taking forever (~10 seconds).
Priority did not help, i saw that the UI call i make instantly is handled by the operation queue (because we limited the downloads limit and the NSOperationQueue had more space to fulfill other requests.
when we limited the concurrent REST download calls to 5 - the REST calls from the UI took 10 seconds.
when we limited the concurrent REST download calls to 2 - everything worked fine.
the issue here is that because we let only 2 downloads occur in the background - the whole background operation of downloading files will take forever.
the best scenario would be that every UI call would be considered as most important network-wise and even pause the background operations and let only the UI call to be handled - then resume the background operation - but i'm not sure it's possible.
any other idea to address this issue?
You could use 2 RKObjectManagers so that you have 2 separate queues, then use one for 'UI' and the other for 'background'. On top of that you can set the concurrent limits for each queue differently and you could suspend the background queue. Note that suspending the queue doesn't mean already running operations are paused, it just stops new operations from being started.
By doing this you can gain some control, but better options really are to limit the data flow, particularly when running on a mobile data network, and to inform the user what is happening so they can accept the situation or pause it till later.
Related
I'm using GPUImageFilter in a chain, and most of the time it works OK. I've recently come across a few random crashes that match the symptoms in this github issue (albeit I'm using GPUImageFilter not live capture or video). I'm trying to find a suitable method that can ensure I've cleared the frame buffer and any other GPUImage-related activities in willResignActive.
Currently I have:
[[GPUImageContext sharedFramebufferCache] purgeAllUnassignedFramebuffers];
Is this sufficient? Should I use something else instead/in addition to?
As indicated there, seeing gpus_ReturnNotPermittedKillClient in a stack trace almost always is due to OpenGL ES operations being performed while your application is in the background or is just about to go to the background.
To deal with this, you need to guarantee that all GPUImage-related work is finished before your application heads to the background. You'll want to listen for delegate notifications that your application is heading to the background, and make sure all processing is complete before that delegate callback exits. The suggestion there by henryl is one way to ensure this. Add the following near the end of your delegate callback:
runSynchronouslyOnVideoProcessingQueue(^{
// Do some operation
});
What that will do is inject a synchronous block into the video processing pipeline (which runs on a background queue). Your delegate callback will block the main thread at that point until this block has a chance to execute, guaranteeing that all processing blocks before it have finished. That will make sure all pending operations are done (assuming you don't add new ones) before your application heads to the background.
There is a slight chance of this introducing a deadlock in your application, but I don't think any of my code in the processing pipeline calls back into the main queue. You might want to watch out for that, because if I do still have something in there that does that, this will lock your application. That internal code would need to be fixed if so.
I am a bit confused about the different options to handle file downloads on iOS.
I want to be able to handle > 2.000 downloads a time, so some kind of parallelism would be nice
I want a download to be started immediately when fired
I want a download not to be paused or stopped when sending the app to the background
The concrete scenario is a bunch of downloads which are made initially after the user logs into the application. Here I have to download that many files which are mainly small images.
Currently I am using NSURLSessionConfiguration's defaultSessionConfiguration, but going this way the downloads get paused when the user suspends the app (which is likely as the full process needs some minutes).
NSURLSessionConfiguration backgroundSessionConfiguration seems to be the better way to go, but I am seeing delays of up to 20-30 seconds before anything happens after initializing. That's propably okay for some scenarios, but not for mine.
So is there a way to get a workaround to that delay issue? Otherwise I will propably go the "old way" and just download the files in background threads on my own with the 10 minutes limitation.
The Heroku Dev Center on the page about using worker dynos and background jobs states that you need to use worker's + queues to handle API calls, such as fetching an RSS feed, as the operation may take some time if the server is slow and doing this on a web dyno would result in it being blocked from receiving additional requests.
However, from what I've read, it seems to me that one of the major points of Node.js is that it doesn't suffer from blocking under these conditions due to its asynchronous event-based runtime model.
I'm confused because wouldn't this imply that it would be ok to do API calls (asynchronously) in the web dynos? Perhaps the docs were written more for the Ruby/Python/etc use cases where a synchronous model was more prevalent?
NodeJS is an implementation of the reactor pattern. The default build of of NodeJS uses 5 reactors. Once these 5 reactors are being used for IO bound tasks, the main event loop will block.
A common misconception about NodeJS is that it is a system that allows you to do many things at once. This is not necessarily the case, it allows you to do other things while waiting on IO bound tasks, up to 5 at a time.
Any CPU bound tasks are always executed in the main event loop, meaning they will block.
This means if your "job" is IO bound, like putting things in databases then you can probably get away with not using dynos. This of course is dependent on how many things you plan on having go on at once. Remember, any task you put in your main app will take away resources from other incoming requests.
Generally it is not recommended for things like this, if you have a job that does some processing, it belongs in a queue that is executed in its own process or thread.
I have created a web-service app and i want to populate my view controllers according to the response i fetch(via GET) in main thread. But i want to create a scheduled timer which will go and control my server, if there becomes any difference(let's say if the count of an array has changed) i will create a local notification. As far as i read from here and some google results, i cant run my app in background more then ten minutes expect from some special situations(Audio, Vo-IP, GPS).. But i need to control the server at least one per minute.. Can anyone offer some idea-or link please?
EDIT
I will not sell the app in store, just for a local area network. Let's say, from the server i will send some text messages to the users and if a new message comes, the count of messages array will increment, in this situation i will create a notification. I need to keep this 'controlling' routing alive forever, whether in foreground or background. Does GCD give such a solution do anyone have any idea?
Just simply play a mute audio file in loop in the background, OR, ping the user's location in the background. Yes, that will drain the battery a bit, but it's a simple hack for in-home applications. Just remember to enable the background types in your Info.plist!
Note: "[...] I fetch (via GET) in main thread." This is not a good approach. You should never fetch any network resources on the main thread. Why? Because your GUI, which is maintained by the main thread, will become unresponsive whenever a fetch isn't instantaneous. Any lag spike on the network results in a less than desirable user experience.
Answer: Aside from the listed special situations, you can't run background apps. The way I see it:
Don't put the app in the background. (crappy solution)
Try putting another "entity" between the app and the "server". I don't know why you "need to control the server at least one per minute" but perhaps you can delegate this "control" to another process outside the device?
.
iOS app -> some form of proxy server -> server which requires
"babysitting" every minute.
I am using Heroku to host a small app. It's running a screenscraper using Mechanize and Nokogiri for every search request, and this takes about 3 seconds to complete.
Does the screenscraper block anyone else who wants to access the app at that moment? In other words, is it in holding mode for only the current user or for everyone?
If you have only one heroku dyno, then yes it is the case that other users would have to wait in line.
Background jobs are for cases like yours where there is some heavy processing to be done. The process running rails doesn't do the hard work up-front, instead it triggers a background job to do it and responds quickly, freeing itself up to respond to other requests.
The data processed by the background job is viewed later - perhaps in a few requests time, or whenever the job is done, loaded in by javascript.
Definitely, because a dyno is single threaded if it's busy scrapping then other requests will be queued until the dyno is free or ultimately timed out if they hang for more than 30 seconds.
Anything that relies on an external service would be best run through a worker via DJ - even sending an email, so your controller puts the message into the queue and returns the user to a screen and then the mail is picked up by DJ and delivered so the user doesn't have to wait for the mailing process to complete.
Install the NewRelic gem to see what your queue length is doing
John.
If you're interested in a full service worker system we're looking for beta testers of our Heroku appstore app SimpleWorker.com. It's integrated tightly into Heroku and offers a number of advantages over DJ.
It's as simple as a few line of code to send your work off to our elastic worker cloud and you can take advantage of massive parallel processing because we do not limit the number of workers.
Shoot me a message if you're interested.
Chad