\(\text {Touchstone}^{+}\) : Query Aware Database Generation for Match Operators

Query-aware database generator (QAGen) expects to generate an application scenario based on the anonymized query plans as well as the cardinality constraints of all operators. It prefers to have the similar performance to the in-production real performance if applying the generated workload on the generated database. Touchstone is the first work achieving simulating the application with the first 16 queries in TPC-H. However, it is designed based on heuristic rules, and has a weak ability to guarantee the cardinality constraints from match operators, i.e., IN and LIKE, which are important operators for performance optimization. So in this paper, we propose \(\text {Touchstone}^+\) to solve the problem QAGen involving match operators by modeling constraints from IN and LIKE into a Constraint Programming (CP) problem. After solving the CP problem, it provides an initial data distribution satisfying cardinality constraints from all match operators for the iterative parameter search algorithm of Touchstone. Experiments have verified the effectiveness of our design and we also open code sources [12] for reproducing all results.