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#227 in Data structures
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radixheap
Fast monotone priority queues.
A monotone priority queue is a priority queue that requires the extracted elements follow a monotonic sequence. This means that, for a maxradixheap, you cannot insert an element into a radix heap that is larger than the last extracted element.
The key of the last extracted element is called the "top" key of the radix heap. Thus any value pushed onto the heap must be less than or equal to the top key.
In return for this restriction, the radix heap provides two major benefits:

Inserts are
O(1)
and popping an element is amortizedO(log m)
wherem
is the difference between a popped key and the top key at the time the element was inserted.Note that this is independent of the number of elements in the radix heap. This means that for workloads where this difference is bounded by a constant, the radix heap has O(1) pop.

It is trivial to implement firstinlastout order for equal keys in a radix heap. When implementing pathfinding, this corresponds to "tiebreaking" which can significantly improve performance. This is also possible to implement with a binary heap, but comes for free with a radix heap.

A radix heap has generally better cache coherence than a binary heap.
Performance
Here is a summary of the benchmarks from running them on my machine:
astar_radix time: [2.6594 us 2.6622 us 2.6651 us]
astar_binary time: [5.3698 us 5.3762 us 5.3827 us]
pushpop_radix time: [97.601 us 97.784 us 97.987 us]
pushpop_binary time: [507.28 us 507.44 us 507.60 us]
astar
is a benchmark using a map from the
2D Pathfinding Banchmarks.
pushpop
is a more heapfocused benchmark where values are repeatedly pushed and popped off a heap.
Example
extern crate radix_heap;
let mut heap = radix_heap::RadixHeapMap::new();
heap.push(7, 'a');
heap.push(2, 'b');
heap.push(9, 'c');
assert!(heap.top() == None);
assert!(heap.pop() == Some((9, 'c')));
assert!(heap.top() == Some(9));
assert!(heap.pop() == Some((7, 'a')));
assert!(heap.top() == Some(7));
assert!(heap.pop() == Some((2, 'b')));
assert!(heap.top() == Some(2));
assert!(heap.pop() == None);
Dependencies
~40KB