MultiMap: Preserving disk locality for multidimensional datasets

Tuesday April 10, 2007
Hamerschlag Hall D-210
4:30 pm

Minglong Shao
Carnegie Mellon University

MultiMap is an algorithm for mapping multidimensional datasets so as to preserve the data's spatial locality on disks. Without revealing disk-specific details to applications, MultiMap exploits modern disk characteristics to provide full streaming bandwidth for one (primary) dimension and maximally efficient non-sequential access (i.e., minimal seek and no rotational latency) for the other dimensions.

This is in contrast to existing approaches, which either severely penalize non-primary dimensions or fail to provide full streaming bandwidth for any dimension. Experimental evaluation of a prototype implementation demonstrates MultiMap’s superior performance for range and beam queries. On average, MultiMap reduces total I/O time by over 50% when compared to traditional linearized layouts and by over 30% when compared to space-filling curve approaches such as Z-ordering and Hilbert curves. For scans of the primary dimension, MultiMap and traditional linearized layouts provide almost two orders of magnitude higher throughput than space-filling curve approaches.

Minglong Shao is a Ph.D. candidate in the Computer Science Department at Carnegie Mellon University, working with Prof. Anastassia Ailamaki. Her research interests focus on new data organization and management for database systems.