SdSet

Set theory applied on sorted and deduplicated slices. Much performance! Such Wow!

API Documentation can be found on docs.rs.

sdset stands for sorted-deduplicated-slices-set which is a little bit too long.

Performances

Note about the tests, which are done on ranges of integer, if it ends with:

• two_slices_big, the first slice contains 0..100 and the second has 1..101
• two_slices_big2, the first contains 0..100 and the second has 51..151
• two_slices_big3, the first contains 0..100 and the second has 100..200
• three_slices_big, the first contains 0..100, the second has 1..101 and the third has 2..102
• three_slices_big2, the first contains 0..100, the second has 34..134 and the third has 67..167
• three_slices_big3, the first contains 0..100, the second has 100..200 and the third has 200..300

These slices of runs of integer are useful when they overlap, we can see how performances changes when different parts of the slices overlaps.

To run the benchmarks you must enable the unstable feature.

$ cargo bench --features unstable

Note that the sdset set operations does not need many allocations so it starts with a serious advantage. For more information you can see the benchmarks variance.

btree are benchmarks that uses two or three BTreeSets which contains runs of integers (see above), the BTreeSets creations are not taken into account. The set operations are done on these sets and the result is accumulated in a final Vec.

The vec benchmarks are available for the union set operation only, it consist of a Vec which is populated with the elements of two or three slices (see above), sorted and deduplicated.

The duo and multi measurements are the implementations that are part of this crate, the first one can only do set operations on two sets and the second one can be used for any given number of sets.

Histograms

Histograms can be generated using the benchmarks by executing the following command:

$ export CARGO_BENCH_CMD='cargo bench --features unstable'
$ ./gen_graphs.sh

This is much more easier to read statistics and to see how sdset is more performant on already sorted and deduplicated slices than any other kind of collection.