In Python 2.X and 3.x, heaps are supported through an importable library, heapq. It supplies numerous functions to work with the heap data structure modelled in a Python list. Example: >>> from heapq import heappush, heappop >>> heap = [] >>> data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0] >>> for … Read more
Heap storage has nothing to do with these heaps. Heap just means records themselves are not ordered (i. e. not linked to one another). When you insert a record, it just gets inserted into the free space the database finds. Updating a row in a heap based table does not affect other records (though it … Read more
It depends on what the type of the heap is. If it’s a standard heap where every node has up to two children and which gets filled up that the leaves are on a maximum of two different rows, you cannot get better than O(n) for merge. Just put the two arrays together and create … Read more
Well, your intuition was right that we need extra data structure to achieve O(klogk) because if we simply perform operations on the original heap, the term logn will remain in the resulting complexity. Guessing from the targeted complexity O(klogk), I feel like creating and maintaining a heap of size k to help me achieve the … Read more
This is just some information I found while doing this in a class, that I shared with my classmates. I thought I’d make it easier for folks to find it, and I had left this post up so that I could answer it when I found a solution. Note: I’m assuming for this example that … Read more
heapreplace(a, x) returns the smallest value originally in a regardless of the value of x, while, as the name suggests, heappushpop(a, x) pushes x onto a before popping the smallest value. Using your data, here’s a sequence that shows the difference: >>> from heapq import * >>> a = [2,7,4,0,8,12,14,13,10,3,4] >>> heapify(a) >>> b = … Read more
The logical argument is as follows std::priority_queue is a container adaptor; basic memory considerations make the back the preferred place for modifications (with pop_back() and push_back()) for sequence containers such as std::vector. the priority_queue primitives are based on std::make_heap (constructor), std::pop_heap + container::pop_back (priority_queue::pop) and on container::push_back + std::push_heap (priority_queue::push) pop_heap will take the front … Read more
No, the standard Java collections API does not contain an implementation of a Fibonacci heap. I’m not sure why this is, but I believe it is because while Fibonacci heaps are asymptotically great in an amortized sense, they have huge constant factors in practice. The collections framework also doesn’t have a binomial heap, which would … Read more
You need to search through every element in the heap in order to determine if an element is inside. One optimization is possible, though (we assume a max heap here). If you have reached a node with a lower value than the element you are searching for, you don’t need to search further from that … Read more
You might need to implement such a heap yourself. You need to have some handle to the position of the item in the heap, and some methods to push the item up or down when its priority has changed. Some years ago I wrote such a heap as part of a school work. Pushing an … Read more