Affiliation:
1. University of Oxford, United Kingdom
2. Samsung AI, United Kingdom
3. 1X2 Network
4. Google
Abstract
Reasoning-based query planning has been explored in many contexts, including relational data integration, the SemanticWeb, and query reformulation. But infrastructure to build reasoning-based optimization in the relational context has been slow to develop. We overview PDQ 2.0, a platform supporting a number of reasoningenhanced querying tasks. We focus on a major goal of PDQ 2.0: obtaining a more modular and flexible architecture for reasoning-based query optimization.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
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