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[10] [11] Join: The function Join is on two weight-balanced trees t 1 and t 2 and a key k and will return a tree containing all elements in t 1, t 2 as well as k. It requires k to be greater than all keys in t 1 and smaller than all keys in t 2. If the two trees have the balanced weight, Join simply create a new node with left subtree t 1, root ...
0:0 and 3:2 (adjacent) 2:0, 2:2 and 2:3 (neighbors) Height-Balanced. BATON is considered balanced if and only if the height of its two sub-trees at any node in the tree differs by at most one. If any node detects that the height-balanced constraint is violated, a restructuring process is initiated to ensure that the tree remains balanced.
To ensure that all balanced binary search trees contain O(log M) elements, one splits T into two balanced binary trees and removes its representative from the x-fast trie if it contains more than 2 log M elements. Each of the two new balanced binary search trees contains at most log M + 1 elements. One picks a representative for each tree and ...
A B-tree of depth n+1 can hold about U times as many items as a B-tree of depth n, but the cost of search, insert, and delete operations grows with the depth of the tree. As with any balanced tree, the cost grows much more slowly than the number of elements. Some balanced trees store values only at leaf nodes, and use different kinds of nodes ...
To turn a regular search tree into an order statistic tree, the nodes of the tree need to store one additional value, which is the size of the subtree rooted at that node (i.e., the number of nodes below it). All operations that modify the tree must adjust this information to preserve the invariant that size[x] = size[left[x]] + size[right[x]] + 1
In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, [1] is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic.
If the two trees are balanced, join simply creates a new node with left subtree t 1, root k and right subtree t 2. Suppose that t 1 is heavier (this "heavier" depends on the balancing scheme) than t 2 (the other case is symmetric). Join follows the right spine of t 1 until a node c which is balanced with t 2.
[1] [note 1] It consists of a main routine with three subroutines. The main routine is given by Allocate a node, the "pseudo-root", and make the tree's actual root the right child of the pseudo-root. Call tree-to-vine with the pseudo-root as its argument. Call vine-to-tree on the pseudo-root and the size (number of elements) of the tree.