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The decrease-key operation requires a reference to the node we wish to decrease the key of. However, the decrease-key operation itself sometimes swaps the key of a node and the key root. Assume that the insert operation returns some opaque reference that we can call decrease-key on, as part of the public API.
The decrease key operation replaces the value of a node with a given value with a lower value, and the increase key operation does the same but with a higher value. This involves finding the node with the given value, changing the value, and then down-heapifying or up-heapifying to restore the heap property. Decrease key can be done as follows:
[1] [2] Deleting an element (most often used in the special case of deleting the minimum element) works in () amortized time, where is the size of the heap. [2] This means that starting from an empty data structure, any sequence of a insert and decrease-key operations and b delete-min operations would take O ( a + b log n ...
The analysis of pairing heaps' time complexity was initially inspired by that of splay trees. [1] The amortized time per delete-min is O(log n), and the operations find-min, meld, and insert run in O(1) time. [3] When a decrease-key operation is added as well, determining the precise asymptotic running time of pairing heaps has turned out to be ...
Example of a binary max-heap with node keys being integers between 1 and 100. In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key (the value) of P is greater than or equal to the key of C.
A simple B+ tree example linking the keys 1–7 to data values d 1-d 7. The linked list (red) allows rapid in-order traversal. This particular tree's branching factor is =4. Both keys in leaf and internal nodes are colored gray here. By definition, each value contained within the B+ tree is a key contained in exactly one leaf node.
To merge two binomial trees of the same order, first compare the root key. Since 7>3, the black tree on the left (with root node 7) is attached to the grey tree on the right (with root node 3) as a subtree. The result is a tree of order 3. The operation of merging two heaps is used as a subroutine in most other operations. A basic subroutine ...
Remove and save the middle value to get a 3-node. Split the remaining 3-node up into a pair of 2-nodes (the now missing middle value is handled in the next step). If this is the root node (which thus has no parent): the middle value becomes the new root 2-node and the tree height increases by 1. Ascend into the root.