Finding Performance Issues in Database Systems by Exploiting Dormant Code Paths
For database developers and researchers, BFA provides a systematic way to detect performance bugs in optimization logic, addressing a long-standing challenge in DBMS testing.
The paper introduces Branch Flip Analysis (BFA), a white-box methodology to uncover performance issues in DBMSs by flipping code branches to test optimizations. Applied to four mature DBMSs, BFA found 21 previously unknown performance issues using TPC-H and TPC-DS benchmarks.
Performance is a critical characteristic of fundamental systems, such as Database Management Systems (DBMSs). Both academia and industry have invested decades in exploring efficient optimization algorithms. Despite these efforts, DBMSs are prone to performance issues, which incur suboptimal performance. Finding such issues is a longstanding challenge as no ground-truth performance is available. Existing work adopts black-box methods to examine performance consistency across executions, but cannot systematically test optimizations. In this work, we propose a novel, general white-box methodology, Branch Flip Analysis (BFA), to systematically and effectively uncover performance issues. BFA flips code branches to enforce or disable an optimization, and the performance is expected to be not significantly better. Otherwise, a performance issue exists. BFA provides a new perspective to finding performance issues and testing optimization logics in a fine-grained manner. We realized BFA in a prototype system QueryZen, and evaluated it on four widely-used and mature DBMSs: PostgreSQL, MySQL, CockroachDB, and MariaDB. QueryZen found 21 previously unknown and unique performance issues with the workload of the extensively used benchmarks TPC-H and TPC-DS. The core concept of BFA is simple and broadly applicable, and can be adapted to analyze the performance of other software systems.