MyISAM is the default storage engine for versions before MySQL 5.5. After 5.5, InnoDB begins to become the default storage engine for MySQL.
MyISAM uses B-Tree to implement primary key index, unique index and non-primary key index.
The non-primary key index in InnoDB uses the B-Tree data structure, while the primary key index uses the B-Tree.
B-Tree
B-tree (multi-way search tree, not binary) is a common data structure. Using the B-tree structure can significantly reduce the intermediate process experienced when locating records, thereby speeding up access. According to translation, B is usually considered to be the abbreviation of Balance. This data structure is generally used for database indexing and has high overall efficiency.
Performance(Recommended learning:MySQL video tutorial)
B-tree has the following characteristics:
1. Keywords The collection is distributed throughout the tree;
2. Any keyword appears and only appears in one node;
3. The search may end at a non-leaf node;
4. Its search performance is equivalent to a binary search in the complete set of keywords;
5. Automatic hierarchical control;
B Tree
Different storage engines may use different data structures for storage. InnoDB uses B Tree;
So what is B Tree?
B Tree is a variant of B-Tree required by the file system. The difference between an m-order B-tree and an m-order B-tree is:
B and B- (that is, B) are because the keywords on each node are different. One more, one less.
For B-tree, its node structure is the same as B-tree. The difference is the keyword of each node and the number of child nodes it can have. For example, in an m-order B-tree, each node can have at most m child nodes. Non-root nodes have at least [m/2] child nodes, and the number of keywords is one more than B-tree, which is [m/2]~m.
The differences between these two data structures for processing indexes:
1. The same key value will not appear multiple times in the B-tree, and it may appear in leaf nodes or non-leaf nodes. The keys of the B-tree will definitely appear in leaf nodes, and may also appear repeatedly in non-leaf nodes to maintain the balance of the B-tree.
2. Because the B-tree key position is uncertain and only appears once in the entire tree structure, although it can save storage space, it significantly increases the complexity of insertion and deletion operations. B-trees are a better compromise in comparison.
3. The query efficiency of B-tree is related to the position of the key in the tree. The maximum time complexity is the same as that of B-tree (when it is at the leaf node), and the minimum time complexity is 1 (when it is at the root node). The time complexity of B-tree is fixed for a certain built tree.
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