Beaver

Schema mapping is used to transform data to a desired schema from data sources with different schemas. Manually writing complete schema mapping specifications requires a deep understanding of the source and target schemas, which can be burdensome for the user. Programming By Example (PBE) schema mapping methods allow the user to describe the schema mapping using data records. However, real data records are still harder to specify compared to other useful insights about the desired schema mapping the user might have. In this project, we develop a new schema mapping technique, Beaver, that enables an interaction model that gives the user more flexibility in describing the desired schema mapping. The end user is not limited to providing exact and complete target schema data examples but may also provide incomplete or ambiguous examples. Moreover, the user can provide other types of descriptions, like data type or value range, about the target schema. We design an explore-and-verify search-based algorithm to efficiently discover all satisfying schema mapping specifications. We implemented a prototype of our schema mapping technique and experimentally evaluated the efficiency of the system in handling traditional PBE schema mapping test cases, as well as our newly-proposed declarative schema mapping test cases. The experiment results show that the declarative queries, which we believe are easier for non-expert user to input, often cost around zero to five seconds more than the traditional PBE queries. This suggests we retain a system efficiency comparable to traditional PBE schema mapping systems.