Index indexes are used to quickly search for records with specific values. All MySQL indexes are saved as B-trees. If no index exists, MySQL must scan all the records of the entire table from the first record until the required records are found. The more records in the table, the higher the operation cost. If the column is used as the search condition
Index indexes are used to quickly search for records with specific values. All MySQL indexes are saved as B-trees. If no index exists, MySQL must scan all the records of the entire table from the first record until the required records are found. The more records in the table, the higher the operation cost. If the column is used as the search condition
Index
Indexes are used to quickly search for records with specific values. All MySQL indexes are saved as B-trees. If no index exists, MySQL must scan all the records of the entire table from the first record until the required records are found. The more records in the table, the higher the operation cost. If an index has been created on the column used as a search condition, MySQL can quickly obtain the location of the target record without scanning any records. If the table has 1000 records, the index search records should be at least 100 times faster than the Sequential Scan records.
Suppose we have created a table named "people:
CREATE TABLE people ( peopleid SMALLINT NOT NULL, name CHAR(50) NOT NULL ); |
Then, we randomly insert 1000 different name values into the people table. Displays a small part of the data file of the people table:
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We can see that there is no clear order for the name column in the data file. If we create an index for the name column, MySQL will sort the name column in the index:
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For each item in the index, MySQL internally stores the "Pointer" of the actual record location in a data file for it ". Therefore, if we want to find the peopleid of the record whose name is equal to "Mike" (the SQL command is "SELECT peopleid FROM people WHERE name = 'Mike ';"), mySQL can search for the "Mike" value in the name index, and then directly go to the corresponding row in the data file to return the peopleid (999) of the row accurately ). In this process, MySQL only needs to process one row to return results. If there is no index for the "name" column, MySQL will scan all records in the data file, that is, 1000 records! Obviously, the less records that need to be processed by MySQL, the faster it can complete the task.
Index type
MySQL provides multiple index types:
Common Index
This is the most basic index type, and it has no limitations such as uniqueness. Common indexes can be created in the following ways:
CREATE an INDEX, for example, CREATE INDEX
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ON tablename (column list); Modify a TABLE, such as alter table tablename add index [INDEX name] (column list); specify an INDEX when creating a TABLE, for example, create table tablename ([...], INDEX [INDEX name] (column list ));
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Unique Index
This index is basically the same as the previous "normal index", but there is a difference: all values of the index column can only appear once, that is, they must be unique. You can create a unique index in the following ways:
CREATE an INDEX, for example, CREATE UNIQUE INDEX
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ON tablename (column list); Modify a TABLE, such as alter table tablename add unique [index name] (column list); specify an index when creating a TABLE, for example, create table tablename ([...], UNIQUE [index name] (column list ));
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Primary Key
A primary key is a unique index, but it must be specified as a "primary key ". If you have used columns of the AUTO_INCREMENT type, you may already be familiar with primary keys and other concepts. The primary key is generally specified during TABLE creation, for example, "create table tablename ([...], primary key (column list ));". However, we can also ADD a primary key by modifying the TABLE, for example, "alter table tablename add primary key (column list );". Each table can have only one primary key.
Full-text index
MySQL supports full-text indexing and full-text retrieval from version 3.23.23. In MySQL, the full-text index type is FULLTEXT. Full-TEXT indexes can be created on VARCHAR or TEXT columns. It can be created using the create table command or the alter table or create index Command. For large-scale datasets, using the alter table (or create index) command to CREATE a full-text INDEX is faster than inserting a record into an empty TABLE with a full-text INDEX. Full-text indexing is not covered in the following discussions. For more information, see MySQL documentation.
Single Column index and multi-column Index
An index can be a single-column index or multiple-column index. The following is an example to illustrate the differences between the two indexes. Suppose there is a people table:
CREATE TABLE people ( peopleid SMALLINT NOT NULL AUTO_INCREMENT, firstname CHAR(50) NOT NULL, lastname CHAR(50) NOT NULL, age SMALLINT NOT NULL, townid SMALLINT NOT NULL, PRIMARY KEY (peopleid) ); |
The following figure shows the data we inserted into the people table:
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In this data segment, there are four people named "Mikes" (two named Sullivans and two named McConnells), two 17-year-olds, and one named Joe Smith.
This table is mainly used to return the corresponding peopleid Based on the specified user name, name, and age. For example, we may need to find the peopleid of a user named Mike Sullivan AND a 17-year-old user (the SQL command is SELECT peopleid FROM people WHERE firstname = 'Mike 'AND lastname = 'sullivan' AND age = 17; ). Because we don't want MySQL to scan the entire table every time it executes a query, we need to consider using indexes here.
First, we can consider creating an index on a single column, such as the firstname, lastname, or age column. If we create an INDEX for the firstname column (alter table people add index firstname (firstname);), MySQL will use this INDEX to quickly limit the search range to those records whose firstname = 'Mike, then, search for other conditions on the intermediate result set: it first excluded the records whose lastname is not equal to "Sullivan", and then excluded those records whose age is not equal to 17. After all the search conditions are met, MySQL returns the final search result.
Because the index of the firstname column is created, MySQL is much more efficient than the full scan of the execution table. However, we require that the number of records scanned by MySQL still far exceed the actual needs. Although we can delete the index on the firstname column and then create the index on the lastname or age column, it seems that no matter which column is created, the search efficiency is still similar.
To improve search efficiency, we need to consider using multi-column indexes. If you create a multi-column index for the columns firstname, lastname, and age, MySQL only needs to retrieve the correct results once! The following is an SQL command to create this multi-column index:
ALTER TABLE people ADD INDEX fname_lname_age (firstname,lastname,age); |
Because the index file is saved in B-tree format, MySQL can immediately convert it to the appropriate firstname, then to the appropriate lastname, and finally to the appropriate age. Without scanning any record of the data file, MySQL finds the target record correctly!
So, if you create a single column index on the columns firstname, lastname, and age respectively, will the effect be the same as creating a multi-column index with firstname, lastname, and age? The answer is no. The two are completely different. When we perform a query, MySQL can only use one index. If you have three single-column indexes, MySQL will try to select the most restrictive index. However, even if it is the most restrictive single-column index, its capacity is certainly far lower than the multiple-column index of the three columns firstname, lastname, and age.
