I've looked through both Metadata Docs and Metadata Keys Docs, as well as reached out to technical support, but I am still not able to determine if I can extract the below sleep features, REM, light, and deep sleep, (reliably) from multiple data sources without first having or knowing about the data from the provider.
In this Personal Healthkit Sleep Metadata Example, there is one data source that pushes REM, light, and deep sleep. I know about the keys and can pull the data easily, but what about when I want to analyze multiple sources of data? Is there any documentation that shows what each device's metadata might look like beforehand so I can plan for it? I find it hard to believe that Apple is pushing data without any documentation, which would defeat the purpose of being able to collect user data from any number of data sources.
As you saw by reading the metadata documentation, Apple has not published any official metadata keys related to the sleep features you're interested in. In your example, the metadata values are associated with sleep samples using custom keys determined by the app that saved the samples. HealthKit allows apps to use arbitrary metadata keys to store additional information on samples that is not necessarily structured in a standardized way.
Related
Is there a way to get all activities from the Google fitness store via the REST API?
My current assumption is that other apps store their activities in sessions and I can retrieve them using Users.sessions.list. However, the information there, does not really include all the information that was stored or I would like to see: when I manually add a short run via the Fit Android app, I expect this information to be somehow accessible via the sessions API. This should at least include the information I have provided, such as distance or time.
Looking at the same information via the app or the web interface, I can see all the details I have previously entered plus the approximate number of steps and calories.
How do I get this information via the API?
I am currently mainly interested in activities of type running or jogging (8, 56-58) and would like to read the distance in addition to the time information already provided in the session.
Not sure, if this is the right way, but I get all the information I need, if I follow these steps
Find the correct session via Users.sessions.list
Query all data via Users.datasets.aggregate:
Set startTimeMillis and endTimeMillis to the values from the session in question
Set bucketBySession to group results by sessions.
I explicitly query all data sources: For every data source id I add a { "dataSourceId": <id>}to theaggregateBy` array. Not sure, if this is necessary
The resulting bucket has all information related to the session. For my use case I need to clean up overloaded data: some data sources return the distance as steps (derived) while I need the physical length in meters.
This seems to work for my Fit data with the additional cleaning, but I will need to check, if this works for other user's data too.
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.
I want to know what is the best way to store data on the iPhone from a web service.
I want the information to be stored on the device so the person doesn't need to access the web service every time he/she needs it. The currently information isn't much and contains less that 150 records. The records might update from time to time and a few new ones will be added. What is the best way to go about storing the data?
Thanks
If you use ASIHTTPRequest for your network stuff (and if you don't already, I can't sing its praises highly enough), you will find it has a cache layer built in which is perfect for situations like this.
You can activate it with a simple one line;
[ASIHTTPRequest setDefaultCache:[ASIDownloadCache sharedCache]];
And you have full control over the cache policy etc - just read the documentation.
The other simple approach of course is - on the assumption that your web service is returning JSON or XML - simply to store the response in a local file against a hash of the request parameters, then when you request the data again, you can first look to see if the file exists and if it does, return that data rather than going back to the website. You can roll your own cache policies etc too.
Since I discovered ASIHTTPRequest had a cache though, I've not needed to roll my own again.
I find that using coreData or sqllite3 is just overkill for 99% my requirements and a simple cache works very well.
If the data is relational, a Sqlite3 database would be the best storage option you have.
Also, this helps by allowing you to retrieve from the server and to update only the records that have changed, thus saving time and bandwidth.
This is the best option from a scalability point of view as well, as you stated that "current information isn't much", thus giving the impression that this is only a current situation, that may be subjected to further change, probably towards more records being added in time.
Sqite3 also gives you more control and better performance than using, for instance, Core Data. Here's an article explaining some of the details. Moreover, if you work through an Objective-C wrapper, such as FMDB, you get all the advantages without managing the complexity yourself.
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
Does anyone know how sites that have a real-time feed of a lot of data work? I am referring to something like a stock site, where they can tell you in real time (well, 20 minute delay mostly, but still real-time - 20 minutes as I understand it).
They have thousands of data pieces delivered to them every second, I would imagine: MSFT 25.00 +.23 VOL 12000 ???? for each stock that had a change during some interval.
So, is there just a constant feed of small pushes going on? Or do you think a site will pull from the place that has the real data and say "give me all changes since 12:23:45 CST to now" type query?
I ask this because at work we might have a situation where we need to have at our application's fingertips real time information like this, and it won't make sense to hit our third party provider over and over and over again every second...
Generally there is a server/client protocol defined between the 2 parties. In the company I work for the connection is maintained at all times.
Here is info on real time data feeds to go with your stock example
NYSE,NASDAQ
It is common for data providers to also have FTP sites with (delayed) batched data. One that comes to mind is the NWS EMWIN
Sites like Twitter feed data to certain approved sites in real-time via XMPP (Wiki link).
In the broadest terms, a push model is going to be the best way of achieving "real time" transfer, particularly if you're talking about a large amount of data.
However you do always have a problem when using a purely push model of how to recover from missed data.
Depending on the nature of your data that may not be a problem (thinking of video delivery as an analogue, where the amount of data is huge but there is sufficient redundancy for it to recover from missing data). And if you have any control over the data you may be able to build some redundancy in. For example, on every change event you can provide absolute values rather than changes, or previous value and new value.
I've done this making an attempt to retrieve the stock quote from the source, and falling back to a timestamped on-disk cache of the quote when the main source fails or times out.