Find the corresponding primary key value according to the secondary index, and then find the data of the row where the primary key value is located through the primary key index

The B+Tree index structure is classified according to the storage form

Clustered Index

It is to construct a B+ tree according to the primary key of each table, in which the data stored in the leaf nodes is the record data of the row corresponding to this index; the data of all the leaf nodes add up to the record data of the entire table

Each table must have and only one clustered index

Election rules for clustered indexes - clustered indexes are generally primary key indexes

If there is a primary key, the primary key index is a clustered index

If no primary key exists, the first unique index will be used as the clustered index

If there is no primary key and unique index, InnDB will automatically generate a DB_ROW_ID as a hidden clustered index

Secondary Index

Secondary indexes can also be called non-primary key indexes, such as unique indexes (if the unique index is not a clustered index), joint indexes, etc. can be collectively referred to as secondary indexes

A B+ tree is also constructed according to the primary key of each table, but the data stored in the leaf nodes is the value of the primary key index corresponding to this index and the value of the column

Each table can have multiple secondary indexes

Classify according to index features

Primary key index - must be a clustered index

The primary key index is an index created for the primary key in the table. There can only be one primary key index per table

Each table has at most one primary key. By default, a primary key index is automatically created for the primary key when creating the primary key.

The primary key index must meet three conditions:

Primary key values must be unique
Cannot contain Null values
Make sure that the value is an auto-increment property

Create a primary key index - we only need to set the primary key constraint for the field to create a primary key index for the field

#Set the primary key when creating the table

CREATE TABLE table name (

Field 1 Type of field 1 PRIMARY KEY AUTO_INCREMENT,

……

);

#After the table is created successfully, set the field in the table as the primary key

ALTER TABLE table name MODIFY field name field type AUTO_INCREMENT PRIMARY KEY;

Unique index - can be a clustered index or a secondary index

The index can be set as a unique index by using the Unioue parameter

Uniqueness means that duplicate values are not allowed, but Null values are allowed and Null values are allowed to be repeated

There can be multiple unique indexes in a table

Create a unique index

#Set a unique index for the field when creating the table

CREATE TABLE table name (

field 1 type of field 1,

……,

UNIQUE KEY index name INDEX (field 1)

);

# After the table is created successfully, set a unique index for the fields in the table

CREATE UNIQUE INDEX index name ON table name (field 1);

Regular Index - Secondary Index

Also known as a non-unique index, it is the most basic index type in MySQL, which allows duplicate values in the indexed columns

The purpose of this index is only to improve query efficiency, quickly locate specific data, so that the database does not need full table scan

Can be created in any data structure; whether its value is unique and non-null is determined by the constraints of the field itself

create regular index

#Create a regular index for the field when creating the table

CREATE TABLE table name (

field 1 type of field 1,

……

KEY index name (field 1)

);

#After the table is created successfully, create a regular index for the fields of the table (common syntax)

CREATE INDEX index name ON table name (field 1);

#After the table is created successfully, create a regular index for the fields of the table (this syntax is not commonly used)

ALTER TABLE table name ADD INDEX index name (field 1);

Full-text index - Full-Tree index structure

The type of index built through the Full-Tree index structure; build an inverted index; find keywords in the text instead of comparing the values in the index

It is a key technology currently used by search engines. It can use word segmentation technology and other algorithms to intelligently analyze the frequency and importance of keywords in text, and then intelligently filter out the search results we want according to certain algorithm rules.

Can only be created on fields of CHAR, VATCHAR, TEXT types and their series types

Multiple full-text indexes can be created in a table

Create a full-text index FULLTEXT

#Create a full-text index for the field when creating a table (the tokenizer is ngram)

CREATE TABLE table name (

field 1 type of field 1,

……

FULLTEXT INDEX (field 1) WITH PARSER tokenizer type (generally use ngram)

);

#After the table is created successfully, create a full-text index for the fields of the table (common syntax)

CREATE FULLTEXT INDEX index name ON table name (field 1) WITH PARSER tokenizer type;

#After the table is created successfully, create a full-text index for the fields of the table (this syntax is not commonly used)

ALTER TABLE table name ADD FULLTEXT INDEX index name (field 1) WITH PARSER tokenizer type;

Full-text index query

Keywords for full-text index queries

MATCH: Columns to match (columns with full-text indexes)

AGAINST: what to find

Full-text index query statement (build a full-text index for the name field in the following table)

select * from test.emp where match ( name ) against ( ' playing mobile phone ' ) ; #Segment the word for playing mobile phone, extract the value after the word segmentation

select * from test.emp where match ( name ) against ( ' like to learn ' ) ; #For those who like to learn word segmentation, extract the value after word segmentation

Through the above experiments: we can understand that for the InnoDB storage engine, its tokenizer ngram will tokenize the value in the field when indexing; it will also tokenize the content to be searched when querying

Spatial index - R-Tree index structure

The index type established by the R-Tree index data structure; it is mainly used to store geographic location data, and it is rarely used

#After creating the table successfully, create a spatial index for the field

CREATE SPATIAL INDEX index name ON table name (field name);

Sort by number of fields indexed

Single-column index - clustered index and secondary index

As long as the index is established on a single column, it is called a single-column index

The above primary key indexes, unique indexes, regular indexes, full-text indexes, and spatial indexes are all types of single-column indexes

Joint Index - Secondary Index

Create an index for multiple columns on the table, that is, an index contains multiple columns, it becomes a joint index

In a business scenario, if there are multiple query conditions, it is recommended to create a joint index when considering building an index for the query field to avoid querying back to the table

The index points to multiple fields corresponding to the creation time, and the leftmost matching principle should be followed when querying

Create a joint index

CREATE INDEX index name ON table name (field 1, field 2,...);

When creating a joint index, pay attention to the order (sort from left to right according to the frequency of use, and place the frequently used ones on the far left)

For example: first sort by field 1, if the values of field 1 are consistent, then sort by field 2

Why do this is because the joint index needs to follow the leftmost matching principle

Two Indexes to Optimize Indexes

Prefix Index - Secondary Index

When the field type is a string (varchar, text, etc.), sometimes a very long string needs to be indexed, which will make the index large and waste a lot of disk IO during query, affecting query efficiency

At this time, only a part of the prefix of the string can be indexed, which greatly saves the index space and improves the index efficiency

Create a prefix index

CREATE INDEX index name ON table name (field name (extract the first few digits of the string));

How to choose the prefix length

It can be determined according to the selectivity of the index. Selectivity refers to the ratio of the unique index value (cardinality) to the total number of records in the data table

The higher the selectivity, the higher the query efficiency. The selectivity of the unique index is 1, which is the best index selectivity

How to Calculate Index Selectivity

SELECT COUNT(DISTINCT field) / COUNT(*) FROM table name; #Calculate the index selectivity of this field

SELECT COUNT(DISTINCT SUBSTRING(field,1,end bit n)) /count(*) FROM table name; #Calculate the index selectivity of the first n bits of the string

Covering index - an optimization method for index query

When we create an index, we actually create an index for the column

Covering index means that the index is used for conditional judgment when querying, and the column returned by the query is in the index column or the primary key index column

for example

For a table named user, there are id, name, age, job_number fields; create a primary key index for the id column; create a joint index for name and age; create a unique index for job_number

select * from user where id = 2; #This is the covering index;

Although the data of the row with id=2 is returned, since the id is the primary key index, that is, the clustered index, the data saved to the leaf node is the data of each row

select * from user where job_number = 123456; #At this time, it is not a covering index and needs to be returned to the table for query ;

We created a unique index for job_number. At this time, the entire table already has a clustered index, so this unique index is a secondary index. The data stored in its leaf nodes is the primary key index value and the key value of job_number; the data we want to divide is job_number=123456 All the data in this row, at this time, you need to use the value of the primary key index to find the corresponding row data according to the B+ tree generated by the primary key index

select id, job_number from user where job_number = 123456; #This is the covering index

select name, age from user where name = ' Zhang San'; #This is the covering index; because name and age have established a joint index; non-leaf nodes store the values of name and age and the primary key index value

Index Syntax Summary

CREATE INDEX

Create a primary key index - we only need to set the primary key constraint for the field to create a primary key index for the field

#Set the primary key when creating the table

CREATE TABLE table name (

       Field 1 Type of field 1 PRIMARY KEY AUTO_INCREMENT,

       ……

);

#After the table is created successfully, set the field in the table as the primary key

ALTER TABLE table name MODIFY field name field type AUTO_INCREMENT PRIMARY KEY;

Create a unique index

#Set a unique index for the field when creating the table

CREATE TABLE table name (

       field 1 type of field 1,

       ……,

       UNIQUE KEY index name INDEX (field 1)

);

# After the table is created successfully, set a unique index for the fields in the table

CREATE UNIQUE INDEX index name ON table name (field 1);

create regular index

#Create a regular index for the field when creating the table

CREATE TABLE table name (

       field 1 type of field 1,

       ……

KEY index name (field 1)

);

#After the table is created successfully, create a regular index for the fields of the table (common syntax)

CREATE INDEX index name ON table name (field 1);

#After the table is created successfully, create a regular index for the fields of the table (this syntax is not commonly used)

ALTER TABLE table name ADD INDEX index name (field 1);

Create a full-text index FULLTEXT

#Create a full-text index for the field when creating a table (the tokenizer is ngram)

CREATE TABLE table name (

       field 1 type of field 1,

       ……

      FULLTEXT INDEX (field 1) WITH PARSER tokenizer type (generally use ngram)

);

#After the table is created successfully, create a full-text index for the fields of the table (common syntax)

CREATE FULLTEXT INDEX index name ON table name (field 1) WITH PARSER tokenizer type;

#After the table is created successfully, create a full-text index for the fields of the table (this syntax is not commonly used)

ALTER TABLE table name ADD FULLTEXT INDEX index name (field 1) WITH PARSER tokenizer type;

create spatial index

CREATE SPATIAL INDEX index name ON table name (field name);

Create a joint index

CREATE INDEX index name ON table name (field 1, field 2,...);

View index SHOW INDEX

View all indexes in the specified table

SHOW INDEX FROM table name;

Tabele : table name

Non_unique : Whether to allow duplicate values

If it is 1, it means that duplicate values are allowed; if it is 0, it means that duplicate values are not allowed

Key_name : The index name to create the index (primary key is PRIMARY by default)

Seq_in_index : The serial number of the column in the index (for a joint index, it means the serial number of the column in the joint index, the smaller the more left)

Column_name : the field name in the table involved in the index

Collation : collation

A means ascending order (default), NULL means not sortable

Cardinality : the cardinality of the index

Indicates the number of unique values in the index; estimated value; index optimization can be done based on this value

Sub_part : the prefix length of the index

Packed : Whether the index is compressed (Null means it is not compressed)

NULL : Whether the column contains NULL values (Yes means to allow inclusion)

Index_type : Indicates the data structure used by the index (BTREE, Hash, FULLTEXT, etc.)

Comment : Comments for the index

DROP INDEX

Delete an index in the specified table

DROP INDEX index name ON table name;

MySQL index 2 - type of index and index creation

Index Category Summary

The B+Tree index structure is classified according to the storage form

Clustered Index

Secondary Index

Classify according to index features

Primary key index - must be a clustered index

Unique index - can be a clustered index or a secondary index

Regular Index - Secondary Index

Full-text index - Full-Tree index structure

Spatial index - R-Tree index structure

Sort by number of fields indexed

Single-column index - clustered index and secondary index

Joint Index - Secondary Index

Two Indexes to Optimize Indexes

Prefix Index - Secondary Index

Covering index - an optimization method for index query

Index Syntax Summary

CREATE INDEX

View index SHOW INDEX

DROP INDEX

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