Abstract
Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express both a relational query and the layout of its data. Our language can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems. We use deductive program synthesis to turn a high-level relational representation of a database query into a highly optimized low-level implementation which operates on a specialized layout of the dataset. We build an optimizing compiler for this language and conduct experiments using a popular database benchmark, which shows that the performance of our specialized queries is better than a state-of-the-art in memory compiled database system while achieving an order-of-magnitude reduction in memory use.
Highlights
Traditional database systems are generic and powerful, but they are not well optimized for static databases
This paper introduces Castor: a domain specific language and compiler for building static databases
We show that Castor is competitive with the state of the art in-memory compiled database system Hyper [Neumann 2011] while using significantly less memory
Summary
Traditional database systems are generic and powerful, but they are not well optimized for static databases. A static database is one where the data changes slowly or not at all and the queries are fixed. These two constraints introduce opportunities for aggressive optimization and specialization. Castor achieves high performance by combining query compilation techniques from state-of-the-art in-memory databases [Neumann 2011] with a new deductive synthesis approach for generating specialized data structures. Not all of the data in the original database is needed, and some attributes are only used in aggregates. As another example, consider a company which is shipping.
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