Query Optimization and Execution for Multi-Dimensional OLAP
Ahmad Taleb · Spectrum Research Repository (Concordia University) · 2011
Online Analytical Processing (OLAP) is a database paradigm that supports the rich analysis of multi-dimensional data. While current OLAP tools are primarily constructed as extensions to conventional relational databases, the unique modeling and processing requirements of OLAP systems often make for a relatively awkward fit with RDBM systems in general, and their embedded string-based query languages in particular. In this thesis, we discuss the design, implementation, and evaluation of a robust multi-dimensional OLAP server. In fact, we focus on several distinct but related themes. To begin, we investigate the integration of an open source embedded storage engine with our own OLAP-specific indexing and access methods. We then present a comprehensive OLAP query algebra that ultimately allows developers to create expressive OLAP queries in native client languages such as Java. By utilizing a formal algebraic model, we are able to support an intuitive Object Oriented query API, as well as a powerful query optimization and execution engine. The thesis describes both the optimization methodology and the related algorithms for the efficient execution of the associated query plans. The end result of our research is a comprehensive OLAP DBMS prototype that clearly demonstrates new opportunities for improving the accessibility, functionality, and performance of current OLAP database management systems.