Optimizing Queries with Universal Quantification in Object-Oriented and Object-Relational Databases

摘要

We investigate the optimization and evaluation of queries with universal quantification in the context of the object-oriented and object-relational data models. The queries are classified into 16 categories depending on the variables referenced in the so-called range and quantifier predicates. For the three most important classes we enumerate the known query evaluation plans and devise some new ones. These alternative plans are primarily based on anti-semijoin, division, generalized grouping with count aggregation, and set difference. In order to evaluate the quality of the many different evaluation plans a thorough performance analysis on some sample database configurations was carried out. The quantitative analysis reveals that-if applicable-the anti-semijoin-based plans are superior to all the other alternatives, even if we employ the most sophisticated division algorithms. Furthermore, exploiting object-oriented features, anti-semijoin plans can be derived even when this is not possible in the relational context.