Lazysort
Adds a method to iterators that returns a sorted iterator over the data. The sorting is achieved lazily using a quicksort algorithm.
Available via crates.io.
Requires a recent Rust nightly build. The current version has been pretty-much automatically translated through recent Rust changes, as such it might not be entirely idiomatic.
Usage
extern crate lazysort;
use lazysort::Sorted;
use lazysort::SortedBy;The Sorted trait adds a method sorted to all Iterator<T: Ord> which returns an iterator over the same data in default order.
The SortedBy trait adds a method sorted_by to all Iterator<T> which returns an iterator over the same data ordered according to the provided closure of type |T, T| -> Ordering
For example:
let data: Vec<uint> = vec![9, 1, 3, 4, 4, 2, 4];
for x in data.iter().sorted() {
println!("{}", x);
}Will print: 1, 2, 3, 4, 4, 4, 9
Implementation details and performance
The algorithm is essentially the same as described in my blog post using a lazy sort as an example of Clojure's lazy sequences. But made to fit in with Rust's iterators.
The full sequence from the parent iterator is read, then each call to next returns the next value in the sorted sequence. The sort is done element-by-element so the full order is only realised by iterating all the way through to the end.
Previous versions did not use an in-place sort, in keeping as they were with Clojure's immutable data-structures. The latest version however does sort in-place.
To summarise, the algorithm is the classic quicksort, but essentially depth-first; upon each call to next it does the work necessary to find the next item then pauses the state until the next call to next.
Because of the overhead to track state, using this approach to sort a full vector is slower than the sort function from the standard library:
test tests::c_lazy_bench ... bench: 7264361 ns/iter (+/- 273508)
test tests::c_standard_bench ... bench: 2996623 ns/iter (+/- 86006)
These benchmarks are for sorting 50,000 random uints in the range 0 <= x < 1000000. Run cargo bench to run them.
So what's the point of lazy sorting? As per the linked blog post, they're useful when you do not need or intend to need every value; for example you may only need the first 1,000 ordered values from a larger set.
Comparing the lazy approach data.iter().sorted().take(x) vs a standard approach of sorting a vector then taking the first x values gives the following.
The first 1,000 out of 50,000:
test tests::a_lazy_bench ... bench: 906559 ns/iter (+/- 847740)
test tests::a_standard_bench ... bench: 2885885 ns/iter (+/- 570331)
The lazy approach is quite a bit faster; this is due to the 50,000 only being sorted enough to identify the first 1,000, the rest remain unsorted.
The first 10,000 out of 50,000:
test tests::b_lazy_bench ... bench: 2217510 ns/iter (+/- 680408)
test tests::b_standard_bench ... bench: 2891829 ns/iter (+/- 54678)
The lazy approach is still faster, slightly.
These results change on a regular basis as Rust is a fast-moving target, run cargo bench to see for yourself the latest numbers. Earlier versions of Rust had the performance more closely matched, but the latest nightlies have a wider gap; the performance of lazysort has improved with the latest builds, but the performance of the built-in sort has improved even more.
License
Copyright 2014 Ben Ashford
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.