Unit testing in MySQL validates stored procedures, functions, and queries by comparing actual results with expected values in isolated, repeatable tests.
Unit tests uncover logic defects in SQL long before they reach dashboards or applications, saving rework and protecting data quality.
Every test uses the Arrange-Act-Assert pattern: insert controlled data, call the routine under test, then compare the result with an expected value.
Wrap each test in a transaction and roll it back, or run tests in a dedicated schema created and dropped by the test runner.
The assert_equals()
procedure raises an error when expected and actual values differ, causing the test to fail and the runner to stop.
DELIMITER //
CREATE PROCEDURE test.assert_equals(
IN expected VARCHAR(255),
IN actual VARCHAR(255),
IN msg VARCHAR(255)
)
BEGIN
IF expected != actual THEN
SIGNAL SQLSTATE '45000'
SET MESSAGE_TEXT = CONCAT('Assertion failed: ', msg),
MYSQL_ERRNO = 1644;
END IF;
END //
DELIMITER ;
The example below validates a get_customer_lifetime_value()
function using ecommerce tables.Insert sample customers and orders, call the function, and assert the result.
Yes. Run mysql
with --batch
, use the mysqltest
utility, or integrate with pytest
/JUnit
by invoking scripts inside CI pipelines.
Keep fixtures small, reset state between tests, name tests descriptively, and fail fast with clear error messages.
.
Yes. Wrap the query in a view or CTE, run it inside the test, fetch the result into a variable, and assert it equals the expected value.
No, basic tests can be written with SQL and SIGNAL
. However, tools like mysqltest
or pytest
plugins add reporting and CI integration.
Place test scripts in your repo and execute them in CI with the MySQL client. The process exits non-zero if any assertion fails, breaking the build.