concept
Feature
B-Tree There are many varieties, the most common is the B + Tree, for example, the widespread use of MySQL will implement its B + Tree index structure.
Compared with the B-Tree, B + Tree following point:
The upper limit of each node pointer not 2d 2d + 1.
The node does not store data, stores only Key; leaf node does not store a pointer.
FIG 3 is a simple schematic of the B + Tree.
image 3
Since not all nodes have the same domain, thus different B + Tree nodes and the nodes are generally middle size. This is different from the B-Tree, B-Tree though different nodes and storage key may not match the number of pointers, but the upper limit of the domain, and each node is the same, so the same B-Tree implementation for each node application tend the size of the space.
In general, B + Tree is more than the B-Tree index structure suitable for implementing the external memory, external memory and the specific reasons and principles related to the principle of computer access, will be discussed below.
With a sequence of the B + Tree Access Pointer
Generally used in the database system or file system B + Tree structure is optimized on the basis of B + Tree is a classic, an increase of sequential access pointer.
Figure 4
As shown, each of the B + Tree leaf node 4 increases pointer pointing to a leaf node adjacent, it is formed with a sequential access pointers B + Tree. This optimization is done in order to improve the performance of the access interval, e.g. in FIG. 4, if the query key is to record all the data from 18 to 49, 18 when they are found, and only along the node traversal order of the pointers can be one-time access all data nodes, referred to the great range of search efficiency.
This section of the B-Tree and B + Tree had a brief introduction, the following section describes the combined memory access principle why the current B + Tree is the preferred data structure of a database system implementation index.