Core Data max storage iPhone - iphone

Is there a limit to how much persistent storage a single iPhone app may consume?
What does save set the error argument to if the iPhone hits a per-app limit? What if it hits the hardware limit?
Is it possible to limit the number of objects stored for certain entities? If so, what's a good approach to doing this?
acani, an iPhone app I'm working on, downloads the nearest 20 users from the server and saves them to Core Data. After using the app for a while, the users SQLite table could become rather large. How could I limit it? What should I limit it to? Once this table has reached capacity, how could I make it so that newly downloaded users replace the oldest downloaded users?
Thanks!
Matt

I don't know the answer to the limits questions, but I would think you would want the maximum amount of data to be limited well ahead of that. There are some iPhone apps (games0 which take up a large amount of storage (I think Myst is something line 1.5G). But if you allowed your database to grow to those sorts of sizes you might start to impact on the storage the user has for their other applications.
I'd be inclined to suggest that your application needs to have some sort of database house keeping implemented. You will have to write this. Either automatically triggered or manually triggered by the user. For example you might want to setup a settings option where the user can specify how many "old" users it wants to preserve. If users are being added automatically based on location, what sort of algorythm would a user most likely want to cull the list with?

There is a 2GB limit for apps from the App Store but as far as user data goes, you should be able to basically fill the disk. When that happens, your saves will start to fail, I believe with 'NSFileWriteOutOfSpaceError' bubbled up from the PSC.
As far as limiting entity space, there's no Core Data support for this - you'd have to handle it programatically. You could extend the validation system to check for certain conditions (free space, number of entities) and fail an insert or update if these didn't match your criteria.
If you want to delete old users, just sort the results and delete the first/last one.

Related

Only commit changes to Firestore on app/widget close

As Firestore charges by the read/write, it would be super helpful to keep the changes in memory during the session and only commit them when the user exists either the entire app or a specific section. Is there a way to do that in a Flutter web application?
I think one problem with this approach is that the user might just close the tab including your app. In this case, you have no time to send your data to Firestore.
This aside, you could use packages like Hive to store your documents offline and later run a function to add the data to Firestore later.
You also have 50k reads and 20k writes for free with Firebase, which is sufficient for smaller apps. If you exceed this limit, your app is probably big enough to earn money with it anyway.

Avoiding data loss: suggested reading

I am about to work on an app which handles extremely valuable data. Any loss of this data for the user would be very costly, so I'm interested in finding out more about the best architecture design for our needs.
The user will be inputting this data in their iPhone each day. The alternative to using this app is carrying around a piece of paper with this sensitive information on it. So while I know we can be more secure than a piece of paper, I want to make sure we also cover the user stories like "I flushed my phone down the toilet" or "my son deleted the app, where's my data?"
A service like Dropbox comes to mind, but I wouldn't want to require our users to have a Dropbox account; the syncing architecture must be transparent to the user. iCloud is out because web and Android versions may follow.
Can anyone suggest either some good reading on this subject, or some good frameworks to look at? I expect to use a node.js backend, and while we are targeting iPhone first, Android will follow.
The data itself consists of 2 tables, each with a small number of fields, with a many to many relationship. A few new rows will be created by the user each day, but the data will be small and highly compressible.
Turns out this is an extremely difficult issue. In data assurance (this isnt yet a security type situation although could become one because of the assurance aspect) there is ALWAYS a time element. As a simple example what happens if your use has locally updated some piece of data. Just before you have the ability to fully push the data to some cloud service, etc... he / she dumps it in the toilet. Even if good signal was there for transmitting the data there is time in transferring and time necessary for the cloud server to respond saying the data got there properly.
Generally in data assurance, you really have to work to the best you can. You will NEVER be able to solve all issues as there is no data center, nor link to a data center, etc... that is perfect. There is always a chance of data loss. Truly the best you can do, is SYNC as fast as data changes, and if there is loss of connection, as soon as the connection becomes alive again.
Now, for security. Security by itself does not create assurance. If the data itself is something that the customer does not want to lose, and that is his only requirement, then security is un-necessary. If he / she is also worried about other getting their hands on his data, then you have to be worried about data-in-transit (both up and down during syncing), and on the device itself. For the best potential security, encrypt the data locally on the device prior to pushing over the cloud. There are many known attacks that even if using SSL or other services, can get at the data. If you wish, locally encrypt a file, then you could for SOME added security still use SSL (at this point you will have doubly encrypted the data). You also want to sign the data so that there is little chance of it being manipulated in transit, or by the cloud server itself (if a hacker hacked the cloud server). Generally the way to protect the data while on device, you may choose to have the user input a password, and put some fairly strict rules around how passwords are formed, and how many tries you allow before you disallow attempts for 30 minutes or so.
You may also wish to store the data locally in an encrypted form. This way if someone gets the device, they still will need to have the password before they can get the data (unless of course they can crack the algorithm you use to generate the symetric key from the password).
In terms of online data service, you could use iCloud, etc... I am actually NOT a fan of anything cloud. I think it is SO counter enterprise / proprietary data, it isnt even funny. I think it actually almost laughable that so many of these phone / device manufacturers are going SOOOOO cloud based. I think they are abandoning the big companies, as NO big company I know of wants to place their proprietary data on a cloud server that THEY DONT CONTROL. In any case, I would argue that so long as you have a good local encryption scheme prior to sending out the data, then you should be OK. I would from an assurance perspective however look at where the servers are in locale. the reason being that if assurance of data is of prime concern, most larger IT setups like to have replicated data centers on opposing sides of the country / world etc... The reason for this is if an earthquake takes down the data center on one side of the country, it most likely will NOT take down the one on the other side of the country simultaneously. If the data centers for iCloud or whatever you can find are essentially in one locale, then you may consider syncing with one data center on the west coast, and choose a completely differing data center (in this case company) to sync with that is centered on the east coast.
This is all very high level, how you would implement this on an iPhone specifically we could also talk about, byt I hope this at least begins to help pave a path.

Is there any value in using core data for iPhone apps?

Can people give me examples of why they would use coreData in an application?
I ask this because most apps are just clients to a central server where an API of some sort gives you the information you need.
In my case I'm writing a timesheet application for a web app which has an API and I'm debating if there is any value in replicating the data structure on my server in core data(Sqlite)
e.g
Project has many timesheets
employee has many timesheets
It seems to me that I can just connect to the API on every call for lists of projects or existing timesheets for example.
I realize for some kind of offline mode you could store locally in core data but this creates way more problems because you now have a big problem with syncing that data back to the web server when you get connection again.. e.g. the project selected for a timesheet no longer exists.
Can any experienced developer shed some light on there experiences on when core data is best practice approach?
EDIT
I realise of course there is value in storing local persistance but the key value of user defaults seems to cover most applications I can think of.
You shouldn't think of CoreData simply as an SQLite database. It's not JUST an SQLite database. Sure, SQLite is an option, but there are other options as well, such as in-memory and, as of iOS5, a whole slew of custom data stores. The biggest benefit with CoreData is persistence, obviously. But even if you are using an in-memory data store, you get the benefits of a very well structured object graph, and all of the heavy lifting with regards to pulling information out of or putting information into the data store is handled by CoreData for you, without you necessarily needing to concern yourself with what is backing that data store. Sure, today you don't care too much about persistence, so you could use an in-memory data store. What happens if tomorrow, or in a month, or a year, you decide to add a feature that would really benefit from persistence? With CoreData, you simply change or add a persistent data store, and all of your methods to get information out or in remain unchanged. The overhead for that sort of addition is minimal in comparison to if you were trying to access SQLite or some other data store directly. IMHO, that's the biggest benefit: abstraction. And, in essence, abstraction is one of the most powerful things behind OOP. Granted, building the Data Model just for in-memory storage could be overkill for your app, depending on how involved the app is. But, just as a side note, you may want to consider what is faster: Requesting information from your web service every time you want to perform some action, or requesting the information once, storing it in memory, and acting on that stored value for the remainder of the session. An in-memory data store wouldn't persistent beyond that particular session.
Additionally, with CoreData you get a lot of other great features like saving, fetching, and undo-redo.
There are basically two kinds of apps. Those that provide you with local functionality (games, professional applications, navigation systems...) and those that grant access to a remote service.
Your app seems to be in the second category. If you access remote services, your users will want to access new or real-time data (you don't want to read 2 week old Facebook posts) but in some cases, local caching makes sense (e.g. reading your mails when you're on the train with unstable network).
I assume that the value of accessing cached entries when not connected to a network is pretty low for your customers (internal or external) compared to the importance of accessing real-time-data. So local storage might be not necessary at all.
If you don't have hundreds of entries in your timetable, "normal" serialization (NSCoding-protocol) might be enough. If you only access some "dashboard-data", you will be able to get along with simple request/response-caching (NSURLCache can do a lot of things...).
Core Data does make more sense if you have complex data structures which should be synchronized with a server. This adds a lot of synchronization logic to your project as well as complexity from Core Data integration (concurrency, thread-safety, in-app-conflicts...).
If you want to create a "client"-app with a server driven user experience, local storage is not necessary at all so my suggestion is: Keep it as simple as possible unless there is a real need for offline storage.
It's ideal for if you want to store data locally on the phone.
Seriously though, if you can't see a need for it for your timesheet app, then don't worry about it and don't use it.
Solving the sync problems that you would have with an "offline" mode would be detailed in your design of your app. For example - don't allow projects to be deleted. Why would you? Wouldn't you want to go back in time and look at previous data for particular projects? Instead just have a marker on the project to show it as inactive and a date/time that it was made inactive. If the data that is being synced from the device is for that project and is before the date/time that it was marked as inactive, then it's fine to sync. Otherwise display a message and the user will have to sort it.
It depends purely on your application's design whether you need to store some data locally or not, if it is a real problem or a thin GUI client around your web service. Apart from "offline" mode the other reason to cache server data on client side might be to take traffic load from your server. Just think what does it mean for your server to send every time the whole timesheet data to the client, or just the changes. Yes, it means more implementation on both side, but in some cases it has serious advantages.
EDIT: example added
You have 1000 records per user in your timesheet application and one record is cca 1 kbyte. In this case every time a user starts your application, it has to fetch ~1Mbyte data from your server. If you cache the data locally, the server can tell you that let's say two records were updated since your last update, so you'll have to download only 2 kbyte. Now you should scale up this for several tens of thousands of user and you will immediately notice the difference of the server bandwidth and CPU usage.

When to Cache the data

Q1) I am designing a iPhone app and want to know on what basis I should take the decision of caching data.
Q2) I have a huge data set which can change frequently. On my app I am showing the data under different categories and is planning to fetch the data from server when a particular category is tapped. This will reduce the data transfer. Also, this data can change frequently but I can store it for let say 30 minutes. What strategy should I take here? Should I store in core data or no caching all together and for each repetitive taps should hit the server?
Please suggest.
What does "hit" mean in this context? Asking the server whether your data is fresh or simply refetching it?
I would suggest that you cache a few MB or so, that you assume that data stays fresh for at least thirty seconds or so (depends on your scenario). If you want the application to feel very fluent, download everything that can be reached with two taps (or so) or less if it isn't yet cached after each tap (as long as that isn't too much data).
You might also want to include a less-data-mode for users who have a traffic-based-costs internet access.
It totally depends upon the frequency of new data. You can cache the data that's to be displayed at the application launch in all your tabs and then let the updated data flow when user makes request for new data.

Best strategy for synching data in iPhone app

I am working on a regular iPhone app which pulls data from a server (XML, JSON, etc...), and I'm wondering what is the best way to implement synching data. Criteria are speed (less network data exchange), robustness (data recovery in case update fails), offline access and flexibility (adaptable when the structure of the database changes slightly, like a new column). I know it varies from app to app, but can you guys share some of your strategy/experience?
For me, I'm thinking of something like this:
1) Store Last Modified Date in iPhone
2) Upon launching, send a message like getNewData.php?lastModifiedDate=...
3) Server will process and send back only modified data from last time.
4) This data is formatted as so:
<+><data id="..."></data></+> // add this to SQLite/CoreData
<-><data id="..."></data></-> // remove this
<%><data id="..."><attribute>newValue</attribute></data></%> // new modified value
I don't want to make <+>, <->, <%>... for each attribute as well, because it would be too complicated, so probably when receive a <%> field, I would just remove the data with the specified id and then add it again (assuming id here is not some automatically auto-incremented field).
5) Once everything is downloaded and updated, I will update the Last Modified Date field.
The main problem with this strategy is: If the network goes down when I am updating something => the Last Modified Date is not yet updated => next time I relaunch the app, I will have to go through the same thing again. Not to mention potential inconsistent data. If I use a temporary table for update and make the whole thing atomic, it would work, but then again, if the update is too long (lots of data change), the user has to wait a long time until new data is available. Should I use Last-Modified-Date for each of the data field and update data gradually?
I would start by making the update routine atomic, since you'll have enough on your hands figuring out how to get the client-server communication working properly.
After that is a good time to consider tweaking it to be incremental, but only after you do some testing to figure out if it's really necessary. If you're tuning your update protocol to be as low bandwidth as possible, you might discover that even a "big" update is downloaded fast enough.
Another way to look at it is to ask yourself, how often is there going to be network trouble when an average user is doing a sync? You probably don't want to tune for unlikely scenarios.
If you are trying to optimize (minimize) the data transfer you may want to consider a different format than XML, since XML is fairly verbose. Or at least you may want to trade in XML readability for space by making each element name and attribute as small as possible, and eliminate all unnecessary whitespace.
Your basic scheme is good. The thing you need to do is to somehow make your updates idempotent so that you can restart a partially-completed transfer without risk. This is a better way to go than to try to implement some sort of true atomic commit (though you could do that too, using, eg, the SQLite database).
In our experience fairly large updates (10s of KB) can be downloaded quite rapidly, if the server is fast enough. No great need to break updates up into tiny bits. But certainly it won't hurt to try to minimize the amount of data transferred by keeping more granular info on "last update".
(And definitely you should use JSON rather than XML as your transmitted data representation.)
Wonder if you have considered using a Sync Framework to manage the synchronization. If that interests you can take a look at the open source project, OpenMobster's Sync service. You can do the following sync operations
two-way
one-way client
one-way device
bootup
Besides that, all modifications are automatically tracked and synced with the Cloud. You can have your app offline when network connection is down. It will track any changes and automatically in the background synchronize it with the cloud when the connection returns. It also provides synchronization like iCloud across multiple devices
Also, modifications in the Cloud are synched using Push notifications, so the data is always current even if it is stored locally.
In your case,
Criteria are speed (less network data exchange), robustness (data recovery in case update fails), offline access
Speed: Only the changes are sent across the network in both directions
Robustness: It stores data in a transactional store like sqlite and any failed updates are communicated in the SyncML payload. Only the successful operations are processed while the failed operations are re-tried during the next sync
Here is a link to the open source project: http://openmobster.googlecode.com
Here is a link to iPhone App Sync: http://code.google.com/p/openmobster/wiki/iPhoneSyncApp