All Products
Document Center

PolarDB:Use window functions to accelerate parallel queries

Last Updated:Mar 18, 2024

Window function is a feature introduced in MySQL Community Edition 8.0 to improve query and analysis capabilities. Window function is fully supported in PolarDB for MySQL 8.0 and can be executed in parallel.


  • Your cluster is of PolarDB for MySQL Cluster Edition 8.0 and its revision version is or later. For more information about how to query the version of a cluster, see Query the engine version.

  • Only window functions that use the PARTITION BY clause can be executed in parallel.

Usage notes

  • Syntax

    In PolarDB, you can use only the EXPLAIN FORMAT=TREE statement to check whether window functions are used.

  • Examples

    In the following example, a table named employee_salaries is created and data is inserted into the table:

    CREATE TABLE `employee_salaries` (
      `dept` varchar(20) DEFAULT NULL,
      `name` varchar(20) DEFAULT NULL,
      `salary` int DEFAULT NULL
    ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
    INSERT INTO `employee_salaries` VALUES

    The following example shows the parallel query execution plan for the employee_salaries table:

    explain format=tree select ROW_NUMBER() OVER(partition by dept order by salary desc) AS 'row_number' from employee_salaries\G
    *************************** 1. row ***************************
    -> Gather (slice: 1; workers: 4)  (cost=26.42 rows=12)
        -> Window aggregate  (cost=15.67 rows=3)
            -> Repartition (hash keys: employee_salaries.dept; slice: 2; workers: 4)  (cost=15.33 rows=3)
                -> Sort: employee_salaries.dept, employee_salaries.salary DESC  (cost=1.55 rows=13)
                    -> Parallel table scan on employee_salaries, with parallel partitions: 4

    In the preceding execution plan, after the employee_salaries table is scanned in parallel, data is distributed to the worker in the next stage by the key (employee_salaries.dept) specified in the Partition By clause. This ensures that the window functions can complete parallel computing and the results are correct. Finally, the leader summarizes the results.