How to sync CoreData and a REST web service asynchronously and the same time properly propagate any REST errors into the UI - iphone

Hey, I'm working on the model layer for our app here.
Some of the requirements are like this:
It should work on iPhone OS 3.0+.
The source of our data is a RESTful Rails application.
We should cache the data locally using Core Data.
The client code (our UI controllers) should have as little knowledge about any network stuff as possible and should query/update the model with the Core Data API.
I've checked out the WWDC10 Session 117 on Building a Server-driven User Experience, spent some time checking out the Objective Resource, Core Resource, and RestfulCoreData frameworks.
The Objective Resource framework doesn't talk to Core Data on its own and is merely a REST client implementation. The Core Resource and RestfulCoreData all assume you talk to Core Data in your code and they solve all the nuts and bolts in the background on the model layer.
All looks okay so far and initially I though either Core Resource or RestfulCoreData will cover all of the above requirements, but... There's a couple of things none of them seemingly happen to solve correctly:
The main thread should not be blocked while saving local updates to the server.
If the saving operation fails the error should be propagated to the UI and no changes should be saved to the local Core Data storage.
Core Resource happens to issue all of its requests to the server when you call - (BOOL)save:(NSError **)error on your Managed Object Context and therefore is able to provide a correct NSError instance of the underlying requests to the server fail somehow. But it blocks the calling thread until the save operation finishes. FAIL.
RestfulCoreData keeps your -save: calls intact and doesn't introduce any additional waiting time for the client thread. It merely watches out for the NSManagedObjectContextDidSaveNotification and then issues the corresponding requests to the server in the notification handler. But this way the -save: call always completes successfully (well, given Core Data is okay with the saved changes) and the client code that actually called it has no way to know the save might have failed to propagate to the server because of some 404 or 421 or whatever server-side error occurred. And even more, the local storage becomes to have the data updated, but the server never knows about the changes. FAIL.
So, I'm looking for a possible solution / common practices in dealing with all these problems:
I don't want the calling thread to block on each -save: call while the network requests happen.
I want to somehow get notifications in the UI that some sync operation went wrong.
I want the actual Core Data save fail as well if the server requests fail.
Any ideas?

You should really take a look at RestKit (http://restkit.org) for this use case. It is designed to solve the problems of modeling and syncing remote JSON resources to a local Core Data backed cache. It supports an offline mode for working entirely from the cache when there is no network available. All syncing occurs on a background thread (network access, payload parsing, and managed object context merging) and there is a rich set of delegate methods so you can tell what is going on.

There are three basic components:
The UI Action and persisting the change to CoreData
Persisting that change up to the server
Refreshing the UI with the response of the server
An NSOperation + NSOperationQueue will help keep the network requests orderly. A delegate protocol will help your UI classes understand what state the network requests are in, something like:
#protocol NetworkOperationDelegate
- (void)operation:(NSOperation *)op willSendRequest:(NSURLRequest *)request forChangedEntityWithId:(NSManagedObjectID *)entity;
- (void)operation:(NSOperation *)op didSuccessfullySendRequest:(NSURLRequest *)request forChangedEntityWithId:(NSManagedObjectID *)entity;
- (void)operation:(NSOperation *)op encounteredAnError:(NSError *)error afterSendingRequest:(NSURLRequest *)request forChangedEntityWithId:(NSManagedObjectID *)entity;
#end
The protocol format will of course depend on your specific use case but essentially what you're creating is a mechanism by which changes can be "pushed" up to your server.
Next there's the UI loop to consider, to keep your code clean it would be nice to call save: and have the changes automatically pushed up to the server. You can use NSManagedObjectContextDidSave notifications for this.
- (void)managedObjectContextDidSave:(NSNotification *)saveNotification {
NSArray *inserted = [[saveNotification userInfo] valueForKey:NSInsertedObjects];
for (NSManagedObject *obj in inserted) {
//create a new NSOperation for this entity which will invoke the appropraite rest api
//add to operation queue
}
//do the same thing for deleted and updated objects
}
The computational overhead for inserting the network operations should be rather low, however if it creates a noticeable lag on the UI you could simply grab the entity ids out of the save notification and create the operations on a background thread.
If your REST API supports batching, you could even send the entire array across at once and then notify you UI that multiple entities were synchronized.
The only issue I foresee, and for which there is no "real" solution is that the user will not want to wait for their changes to be pushed to the server to be allowed to make more changes. The only good paradigm I have come across is that you allow the user to keep editing objects, and batch their edits together when appropriate, i.e. you do not push on every save notification.

This becomes a sync problem and not one easy to solve. Here's what I'd do: In your iPhone UI use one context and then using another context (and another thread) download the data from your web service. Once it's all there go through the sync/importing processes recommended below and then refresh your UI after everything has imported properly. If things go bad while accessing the network, just roll back the changes in the non UI context. It's a bunch of work, but I think it's the best way to approach it.
Core Data: Efficiently Importing Data
Core Data: Change Management
Core Data: Multi-Threading with Core Data

You need a callback function that's going to run on the other thread (the one where actual server interaction happens) and then put the result code/error info a semi-global data which will be periodically checked by UI thread. Make sure that the wirting of the number that serves as the flag is atomic or you are going to have a race condition - say if your error response is 32 bytes you need an int (whihc should have atomic acces) and then you keep that int in the off/false/not-ready state till your larger data block has been written and only then write "true" to flip the switch so to speak.
For the correlated saving on the client side you have to either just keep that data and not save it till you get OK from the server of make sure that you have a kinnf of rollback option - say a way to delete is server failed.
Beware that it's never going to be 100% safe unless you do full 2-phase commit procedure (client save or delete can fail after the signal from the server server) but that's going to cost you 2 trips to the server at the very least (might cost you 4 if your sole rollback option is delete).
Ideally, you'd do the whole blocking version of the operation on a separate thread but you'd need 4.0 for that.

Related

Core Data - How to force NSPrivateQueueConcurrencyType context save in serial?

I was excited about the newly supported concurrent functions of CoreData since iOS 5.
A private queue is maintained and all save or fetch requests can be done via that queue.
However, can I set up the private queue for CoreData so that it executes request one by one?
My app is downloading news items from a number of feeds. Each time after downloading and parsing from one feed are finished, I just save the feed's items into CoreData via the private queue.
However, since I am downloading and parsing from multiple feeds simultaneously, I always have multiple groups of items, i.e., multiple save requests, for the CoreData.
Now the situation is that I guess CoreData just have a number of threads and each one is saving a group of items into the db. My UI got stuck in the mean time.
Do you think I can control the private queue so that no matter how many simultaneous save requests are, they will be done one by one?
Core Data is (probably) only using one serial queue or thread since its serial. I recently converted my app from using a serial queue I had created (app was 4.3) to use this new option in iOS 5. In all cases when you 'performBlock' the method is handled in a serial fashion. Also, you can now call '[moc performBlocK:...]' from any queue as that call is thread safe!
I believe what you want to do is have your background threads, which are most likely adding options, to use 'performBlock:' (without the wait). The block you provide is then queued and processed in a FIFO fashion. Later on, if your table wants to get objects, it can issue a 'performBlockAndWait:', or optionally your code can ask for the latest objects using performBlock, and at the end of the supplied block message back to your app the set of objects you need.
Also, I only ever save often in development builds, to verify validity. Once you are pretty sure things are working OK, you can then just perform a background save once all the data is downloaded.
EIDT: To reiterate - if you are downloading and also using images or other data while loading a viewController, and lots of things are going on, this is the WORST time to do a save. Use a timer or dispatch_after, and many seconds after everything seems stable THEN do the save.

Running continuos thread in app delegate is proper or not

In my app requirement is, when the app is launch for the first time it will send request to server to get data, parse it and save it in document folder which will be used across entire project.Again after particular time interval the app will send request to server to get updated data(if any) and update that data in document folder, which again will be updated across entire project.All this process is happening in background thread.This process will repeat until the app is running in foreground once the user close the app, the app will get terminate, it will not go in background.
This repeated request I am creating in app delegate as well as doing xml parsing once the data is received and saving after parsing. Now my question is, Is this proper means doing too much stuff in app delegate is safe or there is some limitation or is this bad programming?
What is the correct way of doing this?
I disagree with torrey.lyons to an extent. I think creating singletons is bad practice generally speaking and should be avoided where possible. One thing you should never do is code a class so that it has to be a singleton. Purpose built singletons tend to increase coupling and can be really problematic when it comes to unit testing where you might want to replace your singleton with a stub class or you might need it to be reinitialised for each unit test.
If this task of getting data is an application level task, there is absolutely no reason why it can't logically be located in the application delegate. I would however create a "connection manager" as torrey.lyons suggests and have one as a property of the app delegate.
I would also not use an explicit background thread to do the data update but I would use a subclass of NSOperation. This is a whole lot easier than managing your own thread.
It is bad practice. Your app delegate should ideally be concerned purely with its own responsibilities, i.e.. responding to the messages the application sends its delegate. It is much better to split off other discrete responsibilities into other objects. For example, you could have a "connection manager" object that is responsible for periodically communicating with the server. If you are sure the app will only connect to one server at a time you probably want to use the singleton pattern so that there only one instance of the object in your application and it can be easily reached by any other class. A good discussion of the proper role of the app delegate and singletons can be found on at Singletons, AppDelegates and top-level data. A good general overview on writing singletons can be found under the Care and Feeding of Singletons.

What triggers UI refresh in CQRS client app?

I am attempting to learn and apply the CQRS design approach (pattern and architecture) to a new project but seem to be missing a key piece.
My client application executes a query and retrieves a list of light-weight, read-only DTOs from the read model. The user selects an item and clicks a button to initiate some action. The action is performed by creating and sending the corresponding command object to the write model (where the command handler carries out the action, updates the data store, etc.) At some point, however, I need to update the UI to reflect changes to the state of the application resulting from the action.
How does the UI know when it is time to refresh the original list?
Additional Info
I have noticed that most articles/blogs discussing CQRS use MVC client apps in their examples. I am working on a Silverlight client right now and am beginning to wonder if the pattern simply doesn't work in that case.
Follow-Up Question
After thinking more about Bartlomiej's response and subsequent discussion, I am wondering about error handling in CQRS. Given that commands are basically fire-and-forget asynchronous operations, how do we report an error condition to the UI?
I see 'refreshing the UI' to take one of two forms:
The operation succeeds, data has changed and the UI should be updated to reflect these changes
The operation fails, data has not changed but the user should be notified of the failure and potential corrective actions.
Even with a Post-Redirect-Get pattern in an MVC, you can't really Redirect until you know the outcome of the operation. None of the examples I've seen thus far address these real-world concerns.
I've been struggling with similar issues for a WPF client. The re-query trigger for any data is dependent on the data your updating, commands tend to fall into categories:
The command is a true fire and forget method, it informs the back-end of a state change but this change does not need to be reflected in the UI, or the change simply isn't important to the UI.
The command will alter the result of a single query
The command will alter the result of multiple queries, usually (in my domain at least) in a cascading fashion, that is, changing the state of a single "high level" piece of data will likely affect many "low level" caches.
My first trigger is the page load, very few items are exempt from this as most pages must assume data has been updated since it was last visited. Though some systems may be able to escape with only updating financial and other critical data in this way.
For short commands I also update data when 'success' is returned from a command. Though this is mostly laziness as IMHO all CQRS commands should be fired asynchronously. It's still an option I couldn't live without but one you may have to if your implementation expects high latency between command and query.
One pattern I'm starting to make use of is the mediator (most MVVM frameworks come with one). When I fire a command, I also fire a message to the mediator specifying which command was launched. Each Cache (A view model property Retriever<T>) listens for commands which affect it and then updates appropriately. I try to minimise the number of messages while still minimising the number of caches that update unnecessary from a single message so I'll (hopefully) eventually end up with a shortlist of update reasons, with each 'reason' updating a list of caches.
Another approach is simple honesty, I find that by exposing graphically how the system updates itself makes users more willing to be patient with it. On firing a command show some UI indicating you're waiting for the successful response, on error you could offer to retry / show the error, on success you start the update of the relevant fields. Baring in mind that this command could have been fired from another terminal (of which you have no knowledge) so data will need to timeout eventually to avoid missing state changes invoked by other machines also.
Noting the irony that the only efficient method of updating cache's and values on a client is to un-separate the commands and queries again, be it through hardcoding or something like a hashmap.
My two cents.
I think MVVM actually fits into CQRS quite well. The ViewModel simply becomes an observable ReadModel.
1 - You initialize your ViewModel state via a query on the ReadModel.
2 - Changes on your ViewModel are automatically reflected on any Views that are bound to it.
3 - Certain changes on your ViewModel trigger a command to propegate to a message queue, an object responsible for sending those commands to the server takes those messages off the queue and sends them to the WriteModel.
4 - Clients should be well formed, meaning the ViewModel should have performed appropriate validation before it ever triggered the command. Once the command has been triggered, any event notifications can be published onto an event bus for the client to communicate changes to other ViewModels or components in the system interested in those changes. These events should carry the relevant information necessary. Typically, this means that other view models usually don't have to re-query the read model as a result of the change unless they are dependent on other data that needs to be retrieved.
5 - There is an object that connects to the message bus on the server for real-time push notifications when other clients make changes that this client is interested in knowing about, falling back to long-polling if necessary. It propagates those to the internal message bus that ties the components on the client together.
6 - The last part to handle is the fact that clients can be occasionally connected, which should be the only reason a command fails (they don't have internet access at the moment), which is when the client should be notified of problems.
In my ASP.NET MVC 3 I use 2 techniques depending on use case:
already well-known Post-Redirect-Get pattern which fits nicely with CQRS. Your MVC action that triggers the command returns a redirection to action that performs a query.
in some cases, like real-time updates of other clients, I rely on domain events/messages. I create an event handler that uses singlarR to push changes to all connected and interested clients.
There are two major ways you can take as far as I know :
1) design your UI , so that the user does not see its changes right away. Like for instance a message to tell him his action is a success, and offering him different choices to continue his work. this should buy you enough time to have updated your readmodel.
2) more complex, but you might keep the information you have send to the server and shows them in the interface.
The most important I guess, educate your user if you can so that they know why the data is not here... yet!
I am thinking about it only now, but these are for sync command handling, not async, in async things go really harder on the brain...the client interface becomes an event eater too..

Core Data client+server/background saving/general import question

I'm working on a Core Data-based application that has a Mac application acting as a 'server' and an iPhone as a client. Everything is going swimmingly, except I'm running into performance issues.
When the user taps an object, the server must return some objects related to that object (nothing too heavy, usually 3-4 objects) and show a UI to choose some options. This needs to be as fast as possible. The round-trip time to the server, the server pulling the data, formatting it, returning it to the client, and the client creating NSManagedObjects from the data (which cannot be optimized further) is about 200 ms. The code relating to presenting the UI (which cannot be optimized further, again) requires around 150 ms. On an iPod touch 2G running iOS 4.0, the single line of code saving the managed object context after the objects are imported is taking anywhere from 150-200 ms.
To me, this screams that I should be backgrounding the managed object context saving. However, as far as I understand it, that won't really meet my needs. If I want to save the managed object context on a background thread, then all the objects in it must have been created on a background thread in a separate managed object context, so I won't see any speed gain because it will still take 100-200 ms for the save to occur, and I'll be seeing even more overhead because I'll still need to tell my main thread to update it's managed objects from the backgrounded managed object context's save before my view controller sees that it needs to refresh itself.
Am I missing an obvious solution? Is there something about Core Data I could use in this situation that would help? I hate to throw such a general question like this out there, but I'm at a complete loss where to go from here.
Sounds like you need to move the entire server communication to a background thread. If you did that then the entire UI would be responsive no matter how long the communication with the server took.
To do this, you stand up a second NSManagedObjectContext on the background thread connected to the same NSPersistentStoreCoordinator. Then you perform your server communication on that background thread (it might even make sense to use an NSOperation) and save the changes.
Your main thread and therefore main NSManagedObjectContext listens for save notifications and when it receives one it updates the main thread and UI. This will eliminate any freezing you are seeing and the processing time becomes mostly irrelevant.

Core data, file downloads, and thread-safety

What's the preferred approach for constantly sharing data across threads when using Core Data? I am downloading a large file and want to show progress of the download in a UIProgressBar. The actual download is happening in a background thread created by NSOperation.
The download information (local path, total bytes, bytes received) is modeled as a Core Data managed object, and the actual file is stored in the Documents/ directory. One solution that came to my mind was to create a separate managed object context in the background thread and pass it the objectID and pull it up using the objectWithID: method. Whenever the background thread does a save, the main thread gets a notification and the main context merges those changes and the table view is subsequently updated.
This approach works, but the save can't be done too frequently or the UI freezes up. So the UI is updated after every X KB's of data is received where X has to be at least 500 KB for the UI to be somewhat responsive. Is there a better approach to pass the download progress data to the main thread as it is received?
EDIT: Would using KVO be of any help? If yes, do you know of any good tutorials on the topic?
I know you already built your own system, but I use ASIHTTPRequest for all my network operations. It is very robust and has tons of goodies like file resuming, saving directly to disk, upload progress monitoring, download progress monitoring, and the kitchen sink. If you dont use it, you can look at the source to see how they do it because the UI never freezes when I use the progress reporting in this framework.
Although I am going to use ASIHTTPRequest for my project, it's still good to mention my solution to the problem for completeness. It is kind of obvious, but saving the core data context as frequently as every couple of seconds is a terrible mistake.
Instead, I added a progress delegate to the download operation, which gets update notification on the main thread.
NSNumber bytesDownloaded = [NSNumber numberWithLongLong:[data length]];
[downloadDelegate performSelectorOnMainThread:#selector(updateProgress:) withObject:bytesDownloaded waitUntilDone:NO];
The important thing was to pass the download progress information to the delegate on the main thread. The delegate updates the progress, keeps accumulating changes and either saves when the download completes or at much bigger intervals.