Read the documentation.

tinyset

tinyset contains a few collections that are optimized to scale in size well for small numbers of elements, while still scaling well in time (and size) for numbers of elements. We have two set types:

1. Set is basically interchangeable with HashSet, although it does require that its elements implement the Copy trait, since otherwise I would have to learn to write correct unsafe code, which would be scary. It uses FNV hashing when there are large numbers of elements.

2. TinySet is places a stronger requirement on its elements, which must have trait HasInvalid. This is intended for elements that are Copy, are Hash, and have an "invalid" value. For the unsigned integer types, we take their maximum value to mean invalid. This constraint allows us to save a bit more space.

3. Set64 is a set for types that are 64 bits in size or less and are Copy, intended for essentially integer types. This is our most efficient type, since it can store values in less space than std::mem::size_of::<T>(), in the common case that they are small numbers. It is also essentially as fast as any of the other set types (faster than many), and can avoid heap allocations entirely for small sets.

All of these set types will do no heap allocation for small sets of small elements. TinySet will store up to 16 bytes of elements before doing any heap allocation, while Set stores sets up to size 8 without allocation. Set64 will store up to 22 bytes of elements, and if all your elements are small (e.g. 0..22 as u64 it will store them in as few bytes as possible.

All these sets are similar in speed to fnv::HashSet. Set64 is usually faster than fnv::HashSet, sometimes by as much as a factor of 2.

To run the benchmark suite, cd into bench and then run

cargo +nightly run --bin sets --release

This will give you loads of timings and storage requirements for a wide variety of set types. You will need nightly rust installed with rustup.

You can alternatively run

cargo +nightly run --bin maps --release

This will give you loads of timings and storage requirements for a wide variety of map types.