MySQL index

Index is help MySQL Data structure for efficient data acquisition .

Ordered data structure for quick search

The database is outside the storage data itself , It also maintains a data structure that satisfies a specific search algorithm , These data structures point to data in some way , Based on these data structures, advanced search algorithms are implemented , This data structure is the index .

Index principle

The purpose of indexing is to improve query efficiency , The essence is to filter out the final desired results by constantly narrowing the range of data you want to obtain , And turn random events into sequential events , With this mechanism , We can always use the same lookup method to lock data . With the help of the index , When executing a query, you can quickly find the required data without scanning the entire table .

Index advantage

Improve the efficiency of data retrieval , Reduce the IO cost .

Sort data through index columns , Reduce the cost of sorting data , To reduce the CPU Consume .

Index disadvantage

Index is also a table , The table holds the primary key and index fields , And points to the record of the entity table , Therefore, the index column also takes up disk space .

Although the index greatly improves the query speed , At the same time, it will reduce the speed of updating the table , For example, make changes to the table INSERT,UPDATE and DELETE, Because when updating tables ,MySQL Not only to save data , And save the index file , Each update adds the field of the index column , Will adjust the index information after the key value changes due to the update .

When to use index

Primary key Build unique index by default

Columns as query criteria (where after )

Columns as foreign keys , Index foreign key relationship

Sorted fields

Grouped fields

When you don't need to use an index

There are too few records

Frequently added, deleted and modified tables , Query fewer tables , Add index to the required class

where Columns not used in conditions

Columns with repeated and average data ( Such as gender )

Index data structure

B+ Trees (InnoDB The storage engine just uses B+ Tree implementation index ).

A well ordered node can store multiple data structures

Non leaf nodes do not store data , Value store index , More indexes can be placed .

Data records are stored in leaf nodes

There is a chain pointer between all leaf nodes .

B+ By sorting the data, the tree can

Index classification

primary key : After setting it as the primary key, the database will automatically create an index .

ALTER TABLE Table name add PRIMARY KEY Table name ( Name );

Delete primary key index :

ALTER TABLE Table name drop PRIMARY KEY;

Single value index : That is, an index contains only a single column , A table can have multiple single-column indexes .

Create a single value index :CREATE INDEX Index name ON Table name ( Name );

DROP INDEX Index name ;

unique index : The value of the index column must be unique , Allow for null

CREATE UNIQUE INDEX Index name ON Table name ( Name );

DROP INDEX Index name ON Table name ;

Composite index ( Composite index ): That is, an index contains multiple columns , During database operations , Composite indexes require less overhead than single valued indexes ( Index multiple columns of the same ), A composite index can be used when the number of rows in a table is much larger than the number of indexed columns .

Create composite index :CREATE INDEX Index name ON Table name ( Column 1, Column 2)

DROP INDEX Name ON Table name ;

The leftmost prefix principle of Composite Index

For example, there are a,b,c The three column , by a,b Create a composite index with two columns , Then the leftmost index principle should be met when using . When using the column of the composite index as the condition , The leftmost column must appear as a condition , Otherwise, the combined index will not take effect .

Full-text index

When fuzzy query is needed , General index is invalid , At this time, you can use full-text index .

CREATE FULLTEXT INDEX Index name ON Table name ( Field name )WITH PARSER ngram;

Select structure from Table name where match( Name ) AGAINST( Search terms ).

Look at the index

SHOW INDEX FROM Table name ;

Clustered index and non clustered index

When you find the index, you find the data you need , So this index is a cluster index , So the primary key is the clustered index .

The storage of index and data is separated , In other words, the index was found but the data was not found , According to the value on the index ( Primary key ), Go back to the table again , Non clustered index is also called auxiliary index .