Exploiting Type and Space in a Main Memory Query Engine

More and more spatial data is accessible over the web or through portals of wireless service providers. In this context the main selection criteria for the data are the type of the requested data objects and their position in the real world. Integration and performance issues are challenged by the need to process ad hoc queries in an interactive fashion. In this paper we investigate how a main memory query engine can be used to meet these requirements. It has the added benefit of being easily deployable to many components in a large-scale data integration system. Hence, we analyze how such a query engine can best exploit the query characteristics by employing an index structure that leverages spatial and type dimensions. In order to support query processing in the best possible way we investigate a specific multi-dimensional main memory index structure. Compared to the straightforward approach using separate indexes on type and position we can increase the performance up to almost an order of magnitude in several important usage scenarios. This requires to tweak the mapping of type IDs to values in the type dimension, which we discuss extensively. This enables the overall system to be used interactively, even with large data sets.