A few times while using my application I am processing some large data in the background. (To be ready when the user needs it. Something kind of indexing.) When this background process finished it needs to the save the data in a cache file, but since this is really large it take some seconds.
But at the same time the user may open some dialog which displays images and text loaded from the disk. If this happens at the same time while the background process data is saved, the user interface needs to wait until the saving process is completed. (This is not wanted, since the user then have to wait 3-4 seconds until the images and texts from the disk are loaded!)
So I am looking a way to throttling the writing to disk. I thought of splitting up the data in chunks and inserting a short delay between saving the different chunks. In this delay, the user interface will be able to load the needed texts and images, so the user will not recognize a delay.
At the moment I am using [[array componentsJoinedByString:'\n'] writeToFile:@"some name.dic" atomically:YES]. This is very high-level solution which doesn't allow any customization. How can I implement without large data into one file without saving all the data as one-shot?
Does writeToFile:atomically: blocks asynchronous reading?
No. It is like writing to a temporary file. Once completed successfully, then renaming the temporary file to the destination (replacing the pre-existing file at the destination, if it exists).
You should consider how you can break your data up, so it is not so slow. If it's all divided by strings/lines and it takes seconds, and easy approach to divide the database would be by first character. Of course, a better solution could likely be imagined, based on how you access, search, and update the index/database.
…inserting a short delay between saving the different chunks. In this delay, the user interface will be able to load the needed texts and images, so the user will not recognize a delay.
Don't. Just implement the move/replace of the atomic write yourself (writing to a temporary file during index and write). Then your app can serialize read and write commands explicitly for fast, consistent and correct accesses to these shared resources.