Optimizing the performance of the MySQL Join algorithm can start from many aspects. The following is a detailed introduction to the specific optimization methods from the perspectives of index optimization, table structure design, query statement optimization, system configuration adjustment, etc.
1. Index optimization
-
Create the right index
- Make sure to be in
JOIN
Create indexes on columns involved in the condition, which helps MySQL use the index nested loop join (INLJ) algorithm to reduce the overhead of full table scanning. For example, for the followingJOIN
Query:
- Make sure to be in
SELECT * FROM orders JOIN customers ON orders.customer_id = customers.customer_id;
Should beorders
Tablecustomer_id
Column andcustomers
Tablecustomer_id
Create an index on the column.
- For frequently used
WHERE
The columns filtered by clauses should also create an index, which can reduce the amount of data participating in the connection before the connection. For example:
SELECT * FROM orders JOIN customers ON orders.customer_id = customers.customer_id WHERE orders.order_date > '2023-01-01';
Can be inorders
Tableorder_date
Create an index on the column.
-
Use of composite indexeswhen
JOIN
When conditions involve multiple columns, consider creating a composite index. For example:
SELECT * FROM products JOIN product_categories ON products.category_id = product_categories.category_id AND products.subcategory_id = product_categories.subcategory_id;
Can be inproducts
Table(category_id, subcategory_id)
Column andproduct_categories
Table(category_id, subcategory_id)
Create a composite index on the column.
2. Table structure design optimization
-
Reasonable table splittingFor tables with very large data volumes, vertical splits or horizontal splits can be considered. Vertical splitting is to split the table by column, put the columns that are often queried together in one table, and the columns that are not commonly used in another table; horizontal splitting is to split the table by row, such as split by time range or business rules. This can reduce each time
JOIN
The amount of data to be processed by the operation. -
Standardization and anti-standardizationStandardized design can reduce data redundancy, but may lead to more
JOIN
Operation; anti-standardization design can appropriately increase data redundancy and reduceJOIN
operate. Trade-offs need to be made based on actual business scenarios. For example, in some scenarios where more reads and less writes, it can be appropriately de-normalized, and some commonly used related data can be stored in a table redundantly to reduceJOIN
operate.
3. Query statement optimization
-
Select the right driver tableMySQL is executing
JOIN
During operation, one table is selected as the driver table and another table is selected as the driven table. Usually, tables with fewer rows are selected as driver tables, which can reduce the number of outer loops. Can be passedEXPLAIN
Statement to view the driver table selected by MySQL and use it as neededSTRAIGHT_JOIN
Keywords force the driver table to be specified. For example:
EXPLAIN SELECT * FROM orders JOIN customers ON orders.customer_id = customers.customer_id; -- Forced designation orders The table is a driver table SELECT * FROM orders STRAIGHT_JOIN customers ON orders.customer_id = customers.customer_id;
- reduce
SELECT
The listListOnly select the required columns to avoid usingSELECT *
, this can reduce the overhead of data transmission and processing. For example:
-- Select only the columns you want SELECT orders.order_id, customers.customer_name FROM orders JOIN customers ON orders.customer_id = customers.customer_id;
4. System configuration adjustment
-
Adjustment
join_buffer_size join_buffer_size
Parameters control block nested loop connection (BNLJ) algorithmjoin buffer
Size. Appropriately increasing this parameter can reduce disk I/O and improve the performance of the BNLJ algorithm. This parameter can be viewed and modified through the following command:
-- View the current join_buffer_size Value of SHOW VARIABLES LIKE 'join_buffer_size'; -- Revise join_buffer_size Value of SET GLOBAL join_buffer_size = 262144; -- Units are bytes
-
Adjustment
sort_buffer_size
existJOIN
During operation, if you need to sort the data,sort_buffer_size
Parameters will affect the performance of sorting. Increased this parameter appropriately reduces the disk I/O required for sorting. It can also be passedSHOW VARIABLES
andSET GLOBAL
Commands to view and modify this parameter.
5. Regularly maintain database
-
Analysis and optimization tablesRegular use
ANALYZE TABLE
Statement analysis table index distribution, allowing the MySQL optimizer to estimate query costs more accurately;OPTIMIZE TABLE
Statements defragment the table to improve the storage efficiency of the table. For example:
ANALYZE TABLE orders; OPTIMIZE TABLE orders;
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Update statisticsStatistics are important for the MySQL optimizer to choose the right execution plan. Can be used
UPDATE STATISTICS
Statistics of statement update table. For example:
UPDATE STATISTICS ON orders;
Through the comprehensive use of the above optimization methods, the performance of the MySQL Join algorithm can be significantly improved.
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