I've been looking into pagination (paginate by timestamp) with a PSQL dbms. My approach currently is to build a b+ index to greatly reduce the cost of finding the start of the next chunk. But everywhere I look in tutorials and on NPM modules like express-paginate (https://www.npmjs.com/package/express-paginate), people seem to get chunks using offset one way or the other or fetching all the data anyways but simply sending them in chunks which to me doesn't seem to be a complete optimization that pagination is for.
I can see that they're still making an optimization by lazy loading and streaming the chunks (thus saving bandwidth and any download/processing time on the client-side), but since offset on psql still requires scanning previous rows. In the worst case where a user wants to view all the data, doesn't this approach have a very high server cost since if you have per say n chunks, you're accessing the first chunk n times, the second chunk n-1 times, the third chunk n-2 times, etc. I understand that this is really in terms of IOs so it's not that expensive but it still bothers me?
Am I missing something very obvious here? I feel like I am because there seems to be a lot more established and experienced engineers who seem to be using this approach. I'm guessing there is some part of the equation or mechanism that I'm just missing from my understanding.
No, you understand this quite well.
The reason why so many people and tools still advocate pagination with OFFSET and LIMIT (or FETCH FIRST n ROWS ONLY, to use the standard's language) is that they don't know a lot about databases. It is easy to understand LIMIT and OFFSET even if you the word “index” to you has no other meaning than ”the last pages in a book”.
There is another reason: to implement key set pagination, you must have an ORDER BY clause in your query, that ORDER BY clause has to contain a unique column, and you have to create an index that supports that ordering.
Moreover, your database has to be able to handle conditions like
... WHERE (name, id) > ('last_found', 42)
and support a multi-column index scan for them.
Since many tools strive to support several database systems, they are likely to go for the simple but inefficient method that works with every query on most database systems.
I have a table that loads in data from a webservice that returns a bunch of JSON data. I load more data when the user scrolls down as the DB I am querying holds quite a bit of data.
The question I have is - will it be feasible to implement the right side alphabetical listing on such a table and how could this be done? It is definitely possible if I load in ALL the data and then sort them locally, populate the index and cache the data for every other time. But what if this is going to be 10K rows of data or more. Maybe load this data on application first launch is one option.
So in terms of performance and usability, does anyone have any recommendations of what is possible to do?
I don't think that you should download all data to make those indexes, it would decrease refreshing time and might cause memory problems.
But if you think that indexes could make a good difference than you can add some features to your server API. I would add either a different API call like get_indexes. Or even I would add POST parameter get_indexes which adds an array of indexes to any call which has this parameter set.
And you should be ready to handle cases when user taps on indexes without any downloaded data or when user just stresses out your app making fast index scrolling up and down.
First see how big the data download is. If the server can gzip the data, it may be surprisingly small - JSON zips very well because of the duplicated keys.
If it's too big, I would recommend modifying the server if possible to let you specify a starting letter. That way, if the user hits the "W" in the index you should be able to request all items that begin with "W".
It would also be helpful to get a total record count from the server so you can know how many rows are in the table ahead of time. I would also return a "loading..." string for each unknown row until the actual data comes down.
I am assigned with the task to implement a functionality to shorten text typed text
For example , I type text like "you" when I highlight it and it has to change like "u"
I will have table which has list of words which has longer version of text and with text to be replaced.so whenever a user types word and highlights it i want to query the db for match , if a match is found I want to replace the word with the shortened word.
This is not my idea and am being assigned to this implementation.
I think this functionality will down the speed of the app responsiveness. And it has some disadvantages over the user friendliness of the application.
So I'd like to hear your opinions on what are the disadvantages it has and how can I implement this in a better manner. Or is that ok to have this kind of functionlity? Won't it affect the app speed?
It's hard to imagine that you'll see a noticeable decrease in performance. Even the iPhone 3G's processor runs at around 400MHz, and someone typing really fast on an iPhone might get four or five characters entered in a second. A simple implementation of the sort of thing you're talking about would involve a lookup in a data structure such as a dictionary, tree, or database, and you ought to be able to do that pretty quickly.
Why not try it? Implement the simplest thing you can think of and measure its performance. For the purpose of measuring, you might want to use a loop to repeatedly look up words from an array. Count the number of lookups you can do in, say, 20 seconds, and divide by 20 to get the average number per second.
i dont think it will take a lot of performance, anyway you can use the profiler to check how long every method is taking, as for the functionality, i believe you should give the user the opportunity to "undo" and keep his own word (same as apple's auto correction)
I have a quite slow data retrieval from a sqlite database on my iPhone and perhaps someone have an alternative idea to explain this. From what I tracked down so far sqlite3_step(statement) is sometimes unusually slow. While retrieving e.g. 50 rows from the database to execute this step takes normally some milliseconds but sometimes it takes several seconds.
My database is not small (80MB) and my theory is that the reason is paging. But can someone else think of an other reason for this?
Do you have a proper index on that table? Queries can be very slow if a full table scan is required to perform your query. See this page for example for some guidance on how to optimize your SQLite queries.
You may simply need to add an index to your table. Don't forget to reindex your table after you add your index (you'll need a tool, there's a free firefox add-on called "SQLite Manager" that does a pretty decent job for this)
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