A dynamically prioritizable priority queue.

Related tags

Utilities binary-heap
Overview

bheap

ci-tests rustdoc FOSSA Status

A generic binary max heap implementation for implementing a dynamically prioritizable priority queue.

This implementation uses a vector as the underlying data-structure. Hence, there is no oppurtunity for fine grained locking. Users of this crate are request to wrap bheap::BinaryMaxHeap with the required concurrency primitive for use in multithreaded contexts.

Why is this necessary?

The binary heap implementation provided by the standard library (use std::collections::binary_heap::BinaryHeap;), assumes that the ordering of the elements in the domain is fixed. I needed a binary heap implementation which allowed for change in ordering of elements at runtime.

How does it work?

bheap::BinaryMaxHeap enforces the Ord + bheap::Uid trait bounds on the element type. The Uid trait, simply presents a method for returing a unique u64 uid for the type.

The struct maintains a Vec<T> as the underlying storage buffer and a HashMap<u64, usize> for maintaining a mapping from T::uid() to position in vector. This map is updated on every heap operation to remain consistent.

When the ordering of an element changes, its position in the heap can be looked up in the heap using the hashmap. Then, we heapify_up() or heapify_down() as required to restore heap property.

Limitations

Since, we use u64 for uniquely identitfying elements, this heap can only scale up 2^64 = 18446744073709551616 elements. This was more than enough for my purposes.

Another interesting property of this library is that it has no third party dependencies other than the standard libary.

License

bheap is licensed under the MIT License. See LICENSE for the full license text.

FOSSA Status

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Comments
Releases(v0.1.0)

  • v0.1.0(Oct 11, 2021)

    Initial release.

    • Basic heap interface implemented.
      • Priority queue operations supported.
      • Dynamic re-ordering supported.
    • Added comprehensive tests to ensure the correctness of all invariants.
    Source code(tar.gz)
    Source code(zip)
Owner
Arindam Das
Specializes in Deep Learning model serving and AI SaaS at scale.
Arindam Das
GitHub https://arindas.github.io/bheap/bheap/index.html
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