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The larger the B+ tree, the more wasted space becomes. This is far inferior to the B-tree.
In addition, the B+ tree must follow a path from the root to the leaf node to find any node, and the efficiency is not necessarily higher than that of the B- tree.
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First, the keywords are different
1. Each keyword in the B tree appears only once, and all keywords are arranged in order from smallest to largest.
2. The non-leaf node of the b+ tree has n sub-trees and has n keywords, and the keywords will be stored as duplicates. Non-leaf nodes only store keywords, only contain the largest or smallest keywords of the subtree, and are only used for indexing, and the keywords are arranged from smallest to largest.
Second, the storage content is different
1. Each node of the B tree stores data in addition to keywords.
2. The storage content of all leaf nodes of the B+ tree contains all the keyword information, as well as pointers to the keyword records.
3. Find the difference
1. The B-tree lookup is equivalent to a bipartite search, which can end at the non-leaf node, and if the frequently accessed element is closer to the root node, the access will be faster.
2. The search path of the B+ tree is from the root to the leaf node, and the length of the search path is relatively stable each time.
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The similarities and differences between an M-order B+ tree and an M-order B-tree are as follows: All leaf nodes contain information about all keywords and pointers to the records containing these keywords, and the leaf nodes themselves are linked in order of the size of the keywords from the smallest to the largest. (The leaf nodes of the b-tree do not contain all the information that needs to be found) All non-terminal nodes can be considered as indexed parts, and the nodes contain only the largest (or smallest) keywords in the root nodes of their subtrees.
The non-terminal nodes of the b-tree also contain valid information that needs to be found).
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Definitions:The maximum number of children of all nodes in the B-tree is called the order of the B-tree, which is usually denoted by m. An M-order B tree is either an empty tree or an M-fork tree that satisfies the following characteristics.
Core features of M-order B trees:The height of the b-tree:Question: What is the minimum height and maximum height of an M-order B tree with n keywords?
5th order B tree - the number of node keywords
m 2) 1 n m-1, i.e., 2 n 4 (the failure node is omitted here).
Core Requirements:An M-rank B+ tree must meet the following conditions:
Tier B+ treeTier B+ tree
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A few episodes of crying chirp, that's too right.
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The B+ tree is a variant of the B-tree, which is also a balanced multi-path lookup tree, which has the same general structure as the B-tree, including root nodes, internal nodes, and leaf nodes.
The non-leaf nodes of the B tree have data, while the non-leaf nodes of the B + tree do not have a tree, the B tree is a multi-way balanced search tree, the B + tree is more suitable for external storage, all the leaf nodes in the B + tree are connected together by pointers, while the B tree does not.
Difference Between B-Tree and B+ Tree.
The B+ tree is a variant of the B-tree, and also belongs to the balanced multi-way lookup tree, only the leaf nodes in the B+ tree will have a pointer to the record rowid, the advantage of the B+ tree, the leaf nodes are connected by pointers, the range scanning will be very simple, all the leaf nodes in the B+ tree are connected together by pointers.
The b-tree has all nodes, and the index entries that appear in the inner nodes will no longer appear in the leaf nodes. The advantage of the b-tree is that the data in the internal nodes can be obtained directly, and it is not necessary to locate it according to the leaf nodes. A b-tree usually means that all values are stored sequentially, and each leaf is the same distance from the root.
b is the meaning of balance, so the b tree is first a balance tree, and the balance tree must first be a sorted number. So the b-tree is a balanced, sorted multi-forked tree.
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