openGauss is an open-source relational database management system (RDBMS) that originated from PostgreSQL. It is designed for high performance, high availability, and enterprise-grade features. Initially developed by Huawei, openGauss was later open-sourced to the community. The SQL optimizer in openGauss is based on PostgreSQL but has been significantly enhanced and modified to improve performance, scalability, and support for enterprise workloads. While the exact version of PostgreSQL from which openGauss inherited its initial codebase is not explicitly stated in the official documentation, it is widely believed that openGauss originated from PostgreSQL 9.2.4. As a result, some legacy SQL optimizer issues from older PostgreSQL versions may still persist in the current version of openGauss.
One common problem that often arises in less mature SQL optimizers involves the inefficient handling of IN subqueries. Below is an example of a SQL statement with an IN subquery. This query retrieves records from the employee table where the salary matches the salary in the emp_subsidiary table for rows with the same emp_id.
select *
from employee a
where a.emp_salary in (select b.emp_salary
from emp_subsidiary b
where a.emp_id = b.emp_id)
Here is the query plan; it takes 7.2 seconds to complete.
The query plan shows a sequence scan of the employee table and an index scan of the emp_subsidiary table. However, this query is not suitable for a scenario where the ratio of employee to emp_subsidiary is 30:1. If openGauss had a more robust SQL optimizer, it should include an internal SQL syntax rewrite mechanism to transform the IN statement into a JOIN or EXISTS statement, allowing for the exploration of more efficient query plans.
Let me rewrite the SQL using an EXISTS statement, as shown below:
select *
from employee a
where exists (select ‘x’
from emp_subsidiary b
where a.emp_salary = b.emp_salary and
a.emp_id = b.emp_id)
This rewritten SQL takes 0.34 seconds to complete and uses a Merge Semi Join in the query plan—a plan that cannot be generated with the original IN syntax. We can see that the cost of the rewritten SQL is significantly lower than that of the original SQL statement. This indicates that the Merge Semi Join plan is not within the plan space explored by openGauss during the SQL optimization stage for the original query
The rewritten SQL is more than 20 times faster than the original SQL. This type of optimization can also be achieved using Tosska SQL Tuning Expert for openGauss.
Tosska SQL Tuning Expert Pro (TSEG Pro™) for OpenGauss® – Tosska Technologies Limited