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The B * tree balances more neighboring internal nodes to keep the internal nodes more densely packed. [2] This variant ensures non-root nodes are at least 2/3 full instead of 1/2. [13] As the most costly part of operation of inserting the node in B-tree is splitting the node, B *-trees are created to postpone splitting operation as long as they ...
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, a 2–3 tree is a tree data structure, where every node with children (internal node) has either two children (2-node) and one data element or three children (3-node) and two data elements. A 2–3 tree is a B-tree of order 3. [1] Nodes on the outside of the tree have no children and one or two data elements. [2] [3] 2–3 ...
A B+ tree consists of a root, internal nodes and leaves. [1] The root may be either a leaf or a node with two or more children. A B+ tree can be viewed as a B-tree in which each node contains only keys (not key–value pairs), and to which an additional level is added at the bottom with linked leaves.
In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: a 2-node has one data element, and if internal has two child nodes;
The algorithms for bulk operations aren't just applicable to the red–black tree, but can be adapted to other sorted sequence data structures also, like the 2–3 tree, 2–3–4 tree and (a,b)-tree. In the following different algorithms for bulk insert will be explained, but the same algorithms can also be applied to removal and update.
Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.
The amortized times of all operations on Fibonacci heaps is constant, except delete-min. [ 1 ] [ 2 ] Deleting an element (most often used in the special case of deleting the minimum element) works in O ( log n ) {\displaystyle O(\log n)} amortized time, where n {\displaystyle n} is the size of the heap. [ 2 ]