PSA: Collection casting is not free

Suyash Srijan
4 min readJun 25, 2019

Type casting is a really easy and convenient way to check the type of an instance or to convert its type to another type.

One of the operations we sometimes perform when dealing with collections is to convert it into a collection of something else. We accomplish this by using the map function.

For example:

Mapping [User] to [Person]

However, sometimes there is a relationship between the types and therefore we can skip the map and use a cast (as/as?/as!) instead.

For example:

Upcasting [IntBox] to [Boxable]

Many people think of casting as a compile-time operation or something that happens within the type system and therefore has zero cost. However, that is not true, at least when it comes to casting collections.

To understand why, let’s use the above example and go deeper.

Anatomy of an array buffer

The size of an array’s buffer is at least MemoryLayout<T>.stride * N where T is the type of the element stored in the array and N is the number of elements stored in the array.

(and if you’re wondering why stride is used, instead of size, here’s a hint: alignment)

In our earlier example, we initially had an array of IntBox with three elements in it. Thus, the size of the buffer was 24 bytes.

Size of [IntBox] buffer with 3 elements

But, when we upcasted it to an array of Boxable, something different happened. Yes, we went from an array of IntBox to an array of Boxable. But also, we went through a change in memory representation.

Size of [Boxable] buffer with 3 elements

The size of the existing buffer was 24 bytes, however we can’t fit three Boxable existential containers in it, because it needs a buffer that is 5 times larger.

This means we can’t just simply copy the buffer and convert each element from one type to another. So, how are we able to cast an [IntBox] to a [Boxable]?

Well, by creating a brand new array of course! Yes, what’s really going on is the runtime is effectively creating a brand new array and “mapping” each element from one type to the other. So, whenever you’re casting a collection, what you’re really doing (or rather, what the runtime is doing) is effectively a map. Yes, very subtle.

It’s even more subtle when the explicit casting is not required:


Here’s a very simple benchmark that demonstrates the cost of casting a collection (using the same code as the example):

Map vs cast benchmark (x = size of array, y = time to convert). Note: both axis are on a log scale

As you can see, a cast has pretty much the same performance impact as a map.

Now, you might be wondering, what if the size of the existing buffer is much larger? Well, it doesn’t matter. Whether you’re upcasting or downcasting (regardless of the size of the existing buffer), either of those operations would result in a runtime call to either forcefully or conditionally perform the cast and you will have to pay the price, because both operations [effectively] result in a map.

Okay, so why is this important to know? Well, most people don’t actually realise that casting a collection can change the performance characteristics of the code. There is an expectation that this kind of covariance would JustWork™ (without any gotchas), however that’s not really the case because it’s not a free conversion.

Unfortunately, there’s nothing we can do about it. However, when performing casting like this, it might be better to be explicit and use a map instead (or leave a comment about this implicit behaviour). This can be helpful when you’re working with performance sensitive code or collections with large number of elements (or both), so you can make the performance characteristics of your code more obvious to the person reading it.

In summary, casting a collection is just a simpler way of calling map. It’s not free, because it's a linear operation.

If you want to learn how to write efficient Swift code that works with collections, I highly recommend buying the “Optimizing Collections” book, written by Károly Lőrentey, who works on the Swift Standard Library team.



Suyash Srijan

iOS Engineer at @theappbusiness. Swift compiler collaborator.