Resources
Takeaways:
- Priority Queues are often implemented using binary heaps.
- Accessing the highest priority item (front of the queue) is fast.
O(1)
(constant). - However, enqueuing/dequeueing (adding/removing) items is slower than regular queues at
O(log n)
(logarithmic). This is due to items having a priority - so each time an item is introduced/removed behind the scenes a reshuffling/ordering of the items might take place. - Priority queues often get used in graph algorithms (like Dijkstra's algorithm or Prim's algorithm). They can be useful for scheduling things as well - such as jobs/tasks. There is also an interesting Microsoft Azure article explaining the use cases/patterns for priority queues.
- Space is
O(n)
.
As I had just learned binary heaps, priority queues were straightforward. All I needed to do to implement one was alter my previous min-heap and add a thin class for the queuing operations.
Here's the finished implementation, with test code, of a priority queue with a min-heap (smaller means higher priority). For readability, I moved the min-heap code below the priority queue and Main()
method:
As always, if you found any errors in this post please let me know!
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