Database Performance and Deadlock Testing

Database performance problems and deadlocks can bring applications to a halt, yet they are often discovered late under production load. Targeted testing of queries, indexing, and locking behaviour helps teams detect issues earlier and design safer access patterns. However, these tests must be designed carefully to avoid harming shared environments.

Performance and Query Behaviour

Performance-focused tests examine how queries behave with realistic data volumes, indexing strategies, and concurrency. Tools like EXPLAIN plans, query profiling, and slow query logs reveal whether operations use appropriate indexes or fall back to table scans. Testers can collaborate with developers and DBAs to interpret these results.

-- Example: inspecting a query plan

EXPLAIN ANALYZE
SELECT o.id, o.total_amount
FROM orders o
WHERE o.created_at > now() - interval '7 days';
Note: You do not need to be a DBA to notice red flags like very high execution times or repeated full-table scans in query plans.
Tip: Work with production-like data sets in non-production environments when evaluating performance; tiny test databases rarely reveal scaling issues.
Warning: Load and concurrency tests that target the database directly can impact other users of the environment. Coordinate and schedule them to avoid disruption.

Deadlock and locking tests explore how concurrent transactions interact. By simulating overlapping updates to the same rows or related tables, you can observe whether the database detects and resolves deadlocks and how the application handles resulting errors.

Designing Safe Deadlock and Locking Tests

Create controlled scenarios with two or more sessions that attempt to update resources in different orders. Monitor how long locks are held, whether deadlocks are reported, and whether the application retries or surfaces clear errors. Keep these tests small, well-documented, and confined to isolated environments.

Common Mistakes

Mistake 1 โ€” Assuming performance and locking will be fine because tests pass functionally

Functional success does not guarantee scalability.

โŒ Wrong: Ignoring slow queries or lock waits until after release.

โœ… Correct: Include performance and concurrency checks in pre-release testing where risk is high.

Mistake 2 โ€” Running heavy DB tests in production unintentionally

This can degrade live systems.

โŒ Wrong: Pointing performance scripts at production databases without planning.

โœ… Correct: Use designated environments and coordinate with operations for intense tests.

🧠 Test Yourself

What is a sensible goal of database performance and deadlock testing?