Mysql database index

Index is the data structure of database to improve the efficiency of database query

MySQL What are the conditions that do not go through the index ？

• The index column participates in the calculation ;

• The index column uses the function ;

• The matching value uses the first percent sign ;

• String and number comparison ;

• The leftmost prefix principle of joint index is not followed ;

• The engine believes that full table scanning is cheaper than using indexes

Three data models of index

• Hashtable ： This structure of hash table is applicable to the scenario with only equivalent query  MemCached  etc. NoSQL engine

• Ordered array ： The performance of ordered array in the scene of equivalent query and range query is excellent . The principle of using binary tree . The time complexity is O  logN; But for updates , Low efficiency , So the ordered array index only applies to the static storage engine .

• Search tree ： Binary tree -> Balanced binary trees -> Balance N Fork tree

About B+Tree

Every index is in InnoDB It corresponds to a B+ Trees .

According to the content of leaf node , The types of indexes are divided into primary key indexes and non primary key indexes

• primary key     The leaf node stores the whole line of data ,InnoDB in , A primary key index is also called a clustered index （Clustered Index）

• Non primary key index    The leaf node stores the value of the primary key .InnoDB in , Non primary key indexes are also called secondary indexes （Seconday Index）

The smaller the primary key length , The smaller the leaf node of a normal index is , The less space a normal index takes （ID Do primary key ）

B Tree（B-Tree） and  B+Tree The difference between ：

B+Tree:

• All leaf nodes are connected by linked list ,
  Easy to find and traverse the interval
  .B Trees need to be recursively traversed at every level . Adjacent elements may not be adjacent in memory , So cache life is neutral B+ Good tree .

• b+ The middle node of the tree does not save data , Can accommodate more node elements .

B-Tree

B Every node of the tree contains key and value, So frequently accessed elements may be closer to the root , So the visit is faster

Index example

create table T(
id int primary key,
k int not null,
name varchar(16),
index (k))engine=InnoDB;

R1~R5 Of (ID,k) Values, respectively (100,1)、(200,2)、(300,3)、(500,5) and (600,6)

select * from T where ID=500    and   select * from T where k=5  difference

summary

  In practice , Indexing is very useful . therefore , At work , I usually build a table without an index , Instead, check the specific implementation in the test SQL. Establish the corresponding index according to the specific business , because MySQL When executing, you will choose an index that you think is the most appropriate , So if you can create a joint index, you can create a joint index , This is a way of trading space for time .