Is it overkill to store 4 types of attributes into a 32-bit int within Core Data?
Or should I simply create a separate attribute for each of them? (will use logic operators to set/get).
I plan to add a new entity to an existing object which will contain anywhere from 200-400 items with about 14 attributes (including an 'index' attribute for ordering purposes). Only one set will be operated on or viewed at any time.
I will need to maintain undo support (referencing How do I improve performance of Core Data object insert on iPhone?)
I may be able to ween this down to about 8 attributes if I store several attributes into a single field. Barring the searchability issue, will I be saving appreciable space?
Also, is it unreasonable to store a set of 400 objects in a growing list of items which will grow at a rate of about 1-3 per week?
I hear some people storing thousands of items in core data so perhaps I am being paranoid. I suppose in the long-run I will need to provide an export archive option, perhaps to iCloud.
So you're saying you have 400 objects with 14 attributes, which you could either store as separate integers, or combine into fewer 32-bit (4-byte) values?
400 x 14 x 4 bytes = 22,400 bytes
That's not very much space at all. If you cut that in half, you're saving 11K, which will probably be dwarfed by the size of the extra code you'll be generating to encode and decode these values.
But don't take my word for it: write a small test program that stuffs values into Core Data, then run it under the profiler to see what happens.
You can also read up on SQLite and how it stores values, since that's what Core Data is using under the hood.
My gut says you're being paranoid and your bit twiddling code won't help much. Worse, it will be a great way to introduce really subtle bugs when you forget that you are shifting with sign extension. (And I love writing bit-twiddling code!)
I need a suggest how to operate with large amount of data on iPhone. Let say I have xml file with ~120k text records. I need to perform search on this data. The solution i have tried is to use Core Data to store information in sorted order in caches. And then use binary search which works fast. But the problem is to build this caches. On first launch application takes about 15-25 seconds to build this caches. Maybe I need to use different approach to search the data?
Thanks in advance.
If you're using an XML file with the requirement that you can't cache, then you're not going to succeed unless you somehow carefully format your XML file to have useful data traversal properties -- but then you may as well use a binary file that's more useful unless you have some very esoteric requirements.
Really what you want is one of the typical indexing algorithms (on disk hash, B-tree, etc) from the get-go.
However...
If you have to read in and parse your XML text file, then you can skirt using a typical big and slow generic XML parser and write a fast hackish version since most of the data records you'll need to recognize are probably formatted the same way over and over. Nothing special, just find where the relevant data fields start, grab the data until it ends, move on to the next data field.
Honestly, 120k of text isn't very much-- sounds like whatever XML parser you're using is just slow. (I use this trick all the time for autogenerated XML data that just represents things like tables or simple data records -- my own parser is faster than any generic XML parser.)
This is probably the solution you actually want since you sound fairly attached to the XML file format. It won't be as error-proof as a generic XML parser if you're not careful, however it will eat that 120KB file up like nobody's business. And it's entry level CS work -- read in a file with certain specific formatting and grab the data values from it. Regexps are your friend if you have access to them.
Try storing and doing your searches in the cloud. (using a database stored on a server somewhere)
Unless you specifically need ALL of the information on the device..
I'm creating an iPhone app, which fetches information from a server every time it is started. However, i'm planning on using the fetched data of the last month/few months/year to calculate some averages.
I had been thinking about saving them to NSUserDefaults using dictionaries (associating a date with a value), but i just remembered there also exists something like core data. Seeing that i do not have any experience with core data, i don't know if it's better. If it wouldn't, i could save the
time i'd use learning it otherwise.
The data comes in in XML format, and i get several sets of the same response each time (for different locations on a map). The amount of sets can change, as the user can add more locations. I currently only save the raw data to the disk to load if the load fails next time it starts. However, i also want to save some specific values from that XML in a way that i can easily access it. What would be the best way to do this?
Edit: I actually also need to know how fast/efficient core data is. I'm currently passing around NSArrays with NSDictionaries for the sets of data during that session. For saving the data that last longer than the session core data is ideal, i found out that much (just need to find a nice way to associate an entity with a date), i just need some advice on the efficiency.
If you're going to be working with larger amounts of data, it's probably anyway better to give Core Data a try, it's after all not that complicated and there's a plenty of good tutorials where you can learn it. There are different settings for the storage type, you can either use a sqlite database or an xml file.
According to the guys from Apple, it should be fast and memory effective to use Core Data in contrast to self-made solutions, so it's a preferred way to go.
Core data would be easier to manipulate the data and query the data using predicates. Core Data supports dates so you can even find items in date ranges.
is there any easy way of store XML data into core data?
Currently, my app just pulls the values from the XML file directly, however, this isn't efficient for XML files which holds over 100 entries, thus storing the data in Core Data would be the best option. XML file is called/downloaded/parsed ever time the app opens.
With the Core Data, the XML data would be downloaded ever 3600 seconds or so, and refresh the current data in the core data, to reduce the loading time when opening the app.
Any ideas on how I can do this?
Having reviewed the developer documentation, it doesn't look very tasty.
I take that you mean you have to down load an xml file, parse it and then save the data encoded in the file? You have several options for saving such data.
If the data is relatively simple and static e.g. a repeating list of items, then you might just want to use a NSArray, NSSet or NSDictionary (or some nested combination) and then just write the resulting collection to disk as a plist using the collection classes writeToFile: methods. Then when the data is needed you just use one of the initWithFile: methods. The disadvantage of this system is that you have to read the entire file back into memory to use it. This system doesn't scale for very large data sets.
If the data is complex e.g. a bunch of separate but highly interrelated chunks of data, and moderately large, then Core Data would be better.
Of course, you always have the option of writing the downloaded file straight to disk as a string if you want.
In my dictionary IPhone app I need to save an array of strings which actually contains about 125.000 distinct words; this transforms in aprox. 3.2Mb of data.
The first time I run the app I get this data from an SQLite db. As it takes ages for this query to run, I need to save the data somehow, to read it faster each time the app launches.
Until now I've tried serializing the array and write it to a file, and afterword I've tested if writing directly to NSUserDefaults to see if there's any speed gain but there's none. In both ways it takes about 7 seconds on the device to load the data. It seems that not reading from the file (or NSUserDefaults) actually takes all that time, but the deserialization does:
objectsForCharacters = [[NSKeyedUnarchiver unarchiveObjectWithData:data] retain];
Do you have any ideeas about how I could write this data structure somehow that I could read/put in memory it faster?
The UITableView is not really designed to handle 10s of thousands of records. If would take a long time for a user to find what they want.
It would be better to load a portion of the table, perhaps a few hundred rows, as the user enters data so that it appears they have all the records available to them (Perhaps providing a label which shows the number of records that they have got left in there filtered view.)
The SQLite db should be perfect for this job. Add an index to the words table and then select a limited number of rows from it to show the user some progress. Adding an index makes a big difference to the performance of the even this simple table.
For example, I created two tables in a sqlite db and populated them with around 80,000 words
#Create and populate the indexed table
create table words(word);
.import dictionary.txt words
create unique index on words_index on word DESC;
#Create and populate the unindexed table
create table unindexed_words(word);
.import dictionary.txt unindexed_words
Then I ran the following query and got the CPU Time taken for each query
.timer ON
select * from words where word like 'sn%' limit 5000;
...
>CPU Time: user 0.031250 sys 0.015625;
select * from unindex_words where word like 'sn%' limit 5000;
...
>CPU Time: user 0.062500 sys 0.0312
The results vary but the indexed version was consistently faster that the unindexed one.
With fast access to parts of the dictionary through an indexed table, you can bind the UITableView to the database using NSFecthedResultsController. This class takes care of fecthing records as required, caches results to improve performance and allows predicates to be easily specified.
An example of how to use the NSFetchedResultsController is included in the iPhone Developers Cookbook. See main.m
Just keep the strings in a file on the disk, and do the binary search directly in the file.
So: you say the file is 3.2mb. Suppose the format of the file is like this:
key DELIMITER value PAIRDELIMITER
where key is a string, and value is the value you want to associate. The DELIMITER and PAIRDELIMITER must be chosen as such that they don't occur in the value and key.
Furthermore, the file must be sorted on the key
With this file you can just do the binary search in the file itself.
Suppose one types a letter, you go to the half of the file, and search(forwards or backwards) to the first PAIRDELIMITER. Then check the key and see if you have to search upwards or downwards. And repeat untill you find the key you need,
I'm betting this will be fast enough.
Store your dictionary in Core Data and use NSFetchedResultsController to manage the display of these dictionary entries in your table view. Loading all 125,000 words into memory at once is a terrible idea, both performance- and memory-wise. Using the -setFetchBatchSize: method on your fetch request for loading the words for your table, you can limit NSFetchedResultsController to only handling the small subset of words that are visible at any given moment, plus a little buffer. As the user scrolls up and down the list of words, new batches of words are fetched in transparently.
A case like yours is exactly why this class (and Core Data) was added to iPhone OS 3.0.
Do you need to store/load all data at once?
Maybe you can just load the chunk of strings you need to display and load all other strings in the background.
Perhaps you can load data into memory in one thread and search from it in another? You may not get search results instantly, but having some searches feel snappier may be better than none at all, by waiting until all data are loaded.
Are some words searched more frequently or repeatedly than others? Perhaps you can cache frequently searched terms in a separate database or other store. Load it in a separate thread as a searchable store, while you are loading the main store.
As for a data structure solution, you might look into a suffix trie to search for substrings in linear time. This will probably increase your storage requirements, though, which may affect your ability to implement this with an iPhone's limited memory and disk storage capabilities.
I really don't think you're on the right path trying to load everything at once.
You've already determined that your bottleneck is the deserialization.
Regardless what the UI does, the user only sees a handful (literally) of search results at a time.
SQLlite already has a robust indexing mechanism, there is likely no need to re-invent that wheel with your own indexing, etc.
IMHO, you need to rethink how you are using UITableView. It only needs a few screenfuls of data at a time, and you should reuse cell objects as they scroll out of view rather than creating a ton of them to begin with.
So, use SQLlite's indexing and grab "TOP x" rows, where x is the right balance between giving the user some immediately-available rows to scroll through without spending too much time loading them. Set the table's scroll bar scaling using a separate SELECT COUNT(*) query, which only needs to be updated when the user types something different.
You can always go back and cache aggressively after you deserialize enough to get something up on-screen. A slight lag after the first flick or typing a letter is more acceptable than a 7-second delay just starting the app.
I have currently a somewhat similar coding problem with a large amount of searchable strings.
My solution is to store the prepared data in one large memory array, containing both the texttual data and offsets as links. Meaning I do not allocate objects for each item. This makes the data use less memory and also allows me to load & save it to a file without further processing.
Not sure if this is an option for you, since this is quite an obvious solution once you've realized that the object tree is causing the slowdown.
I use a large NSData memory block, then search through it. Well, there's more to it, it took me about two days to get it well optimized.
In your case I suspect you have a dictionary with a lot of words that have similar beginnings. You could prepare them on another computer in a format the both compacts the data and also facilitates fast lookup. As a first step, the words should be sorted. With that, you can already perform a binary search on them for a fast lookup. If you store it all in one large memory area, you can do the search quite fast, compared to how sqlite would search, I think.
Another way would be to see the words as a kind of tree: You have many thousands that begin with the same letter. So you divide your data accordingly: You have a sql table for each beginning letter of your set of words. that way, if you look up a word, you'd select one of the now-smaller tables depening on the first letter. This makes the amount that has to be searched already much smaller. and you can do this for the 2nd and 3rd letter as well, and you already could have quite a fast access.
Did this give you some ideas?
Well actually I figured it out myself in the end, but of course I thank you all for your quick and pertinent answers. To be concise I will just say that, the fact that Objective-C, just like any other object-based programming language, due to introspection and other objective requirements is significantly slower than procedural programming languages.
The solution was in fact to load all my data in a continuous chunk of memory using malloc (a char **) and search on-demand in it and transform to objects. This concluded in a .5 sec loading time (from file to memory) and resonable (should be read "fast") operations during execution. Thank you all again and if you have any questions I'm here for you. Thanks