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The term B-tree may refer to a specific design or it may refer to a general class of designs. In the narrow sense, a B-tree stores keys in its internal nodes but need not store those keys in the records at the leaves. The general class includes variations such as the B+ tree, the B * tree and the B *+ tree.
A B+tree is thus particularly useful as a database system index, where the data typically resides on disk, as it allows the B+tree to actually provide an efficient structure for housing the data itself (this is described in [11]: 238 as index structure "Alternative 1").
Creating a one-node tree. Continuing, a '+' is read, and it merges the last two trees. Merging two trees. Now, a '*' is read. The last two tree pointers are popped and a new tree is formed with a '*' as the root. Forming a new tree with a root. Finally, the last symbol is read. The two trees are merged and a pointer to the final tree remains on ...
In computer science, a K-D-B-tree (k-dimensional B-tree) is a tree data structure for subdividing a k-dimensional search space. The aim of the K-D-B-tree is to provide the search efficiency of a balanced k-d tree , while providing the block-oriented storage of a B-tree for optimizing external memory accesses.
A tree whose root node has two subtrees, both of which are full binary trees. A perfect binary tree is a binary tree in which all interior nodes have two children and all leaves have the same depth or same level (the level of a node defined as the number of edges or links from the root node to a node). [18] A perfect binary tree is a full ...
2–3–4 trees are B-trees of order 4; [1] like B-trees in general, they can search, insert and delete in O(log n) time.One property of a 2–3–4 tree is that all external nodes are at the same depth.
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.
Bagwell [1] presented a time and space efficient solution for tries named Array Mapped Tree (AMT). The Hash array mapped trie (HAMT) is based on AMT. The compact trie node representation uses a bitmap to mark every valid branch – a bitwise trie with bitmap.