Cocoa Touch Tutorial: Using Grand Central Dispatch for Asynchronous Table View Cells

One of the problems that an iOS developer will often face is the performance of table view cells. Table view cells are loaded on-demand by the UITableView that they’re a part of; the system calls ‑cellForRowAtIndexPath: on the table view’s dataSource property to fetch a new cell in order to display it. Since this method is called (several times) while scrolling a table view, it needs to be very performant. You don’t have very much time to provide the system with a table view cell; take too long, and the application will appear to stutter to your users. This kills the immersion of your application and is an instant sign to users that the application is poorly-written. I guess what I’m saying is that this code needs to be fast. But what if something you need to do to display the table view cell takes a long time—say, loading an image?

In my MobiDevDay presentation a couple of weeks ago, I illustrated a solution to this problem: Grand Central Dispatch. GCD, Apple’s new multiprocessing API in Mac OS X Snow Leopard and iOS 4, is the perfect solution for this problem. Let’s take a look at how it works.

Grand Central Dispatch operates using queues. Queues are a C typedef: dispatch_queue_t. To get a new global queue, we call dispatch_get_global_queue(), which takes two arguments: a long for priority and an unsigned long for options, which is unused, so we’ll pass 0ul. Here’s how we get a high-priority queue:

dispatch_queue_t queue = dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0ul);

It’s pretty straightforward. To use this queue, we add blocks of code onto it. Typically this is done with blocks (Apple’s new code encapsulation extension to the C language), though it can be done with C functions. To submit a block onto a queue for execution, use the functions dispatch_sync and dispatch_async. They both take a queue and a block as parameters. dispatch_async returns immediately, running the block asynchronously, while dispatch_sync blocks execution until the provided block returns (though you cannot use its return value). Here’s how we schedule some code onto a queue (we’ll assume this code runs after our previous example, so queue is already defined):

dispatch_async(queue, ^{
    NSLog(@"Hello, World!");
});

It’s very easy to forget the ); at the end of that line, so be careful.

How does this apply to table view cells? Let’s take a look at a typical scenario for loading images from disk:

- (UITableViewCell *)tableView:(UITableView *)tableView
         cellForRowAtIndexPath:(NSIndexPath *)indexPath
{
    static NSString *CellIdentifier = @"ExampleCell";
    
    UITableViewCell *cell = [tableView dequeueReusableCellWithIdentifier:CellIdentifier];
    if (cell == nil) {
        cell = [[[UITableViewCell alloc] initWithStyle:UITableViewCellStyleDefault
                                       reuseIdentifier:CellIdentifier] autorelease];
    }
    
    // Get the filename to load.
    NSString *imageFilename = [imageArray objectAtIndex:[indexPath row]];
    NSString *imagePath = [imageFolder stringByAppendingPathComponent:imageFilename];
    
    [[cell textLabel] setText:imageFilename];
    UIImage *image = [UIImage imageWithContentsOfFile:imagePath];
    [[cell imageView] setImage:image];

    return cell;
}

The problem with that code is that creating image blocks until ‑imageWithContentsOfFile: returns. If the images are especially large, this is catastrophic. Modifying this code to use Grand Central Dispatch is simple:

- (UITableViewCell *)tableView:(UITableView *)tableView
         cellForRowAtIndexPath:(NSIndexPath *)indexPath
{
    static NSString *CellIdentifier = @"Cell";
    
    UITableViewCell *cell = [tableView dequeueReusableCellWithIdentifier:CellIdentifier];
    if (cell == nil) {
        cell = [[[UITableViewCell alloc] initWithStyle:UITableViewCellStyleDefault
                                       reuseIdentifier:CellIdentifier] autorelease];
    }
    
    // Get the filename to load.
    NSString *imageFilename = [imageArray objectAtIndex:[indexPath row]];
    NSString *imagePath = [imageFolder stringByAppendingPathComponent:imageFilename];
    
    [[cell textLabel] setText:imageFilename];
    
    dispatch_queue_t queue = dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0ul);

    dispatch_async(queue, ^{
        UIImage *image = [UIImage imageWithContentsOfFile:imagePath];
    
        dispatch_sync(dispatch_get_main_queue(), ^{
            [[cell imageView] setImage:image];
            [cell setNeedsLayout];
        });
    });
    
    return cell;
}

First, we create our image asynchronously by using dispatch_async(). Once we have it, however, we have to come back to the main thread in order to update our table view cell’s UI (all UI updates should be on the main thread, unless you like reading crash reports). GCD has a function to get the main queue—analogous to the main thread—called dispatch_get_main_queue(). We can dispatch a block to that thread to update the UI.

By making this simple modification, we can very easily improve the performance of our table view. There are a few steps remaining, however, and this method has one serious shortcoming: if the cell is re-used by the time the image loads, it can load the wrong image into the cell. To get around this, it would be better to cache the images in an array or a dictionary (just be sure to release it in your view controller’s ‑didReceiveMemoryWarning: method). That said, this is an example of something you can do quite easily to improve the performance of your application. The better it performs, the more your users will like it, and that’s the ultimate goal.

The code used in this post is available as a GitHub repository.

MobiDevDay Presentation Slides

I gave a presentation on blocks and Grand Central Dispatch today at MobiDevDay. You can download the slides at SlideShare.

Looking for more reading about blocks? Here are some more resources:

Also, as we saw in the presentation, check out cdecl.org to cheat!

UPDATE: Looking for example code? I’ve put some of the code that went into the slides up on GitHub. It’s light, but it also includes a .PDF version of the presentation.