Abstract
Newly emerging spatial applications such as the intelligent transportation system require high-performance access to databases. Although research prototypes and spatial extensions on top of commercial DBMSs have been built, the high-performance requirement is difficult to satisfy because most of them employ the traditional disk-based database architecture. With the steadily increasing memory capacity of computer systems, the main-memory database architecture becomes a feasible approach to meeting the requirement, and a few commercial products are developed recently. However, there has been little work on applying the main-memory database to the spatial domain. This paper presents Xmas-SX, a high-performance spatial storage system based on the main-memory database architecture. It provides the core subset of the OpenGIS geometry types, operators, and spatial indexes. Variable-length spatial data are efficiently managed by storing each of them as a sequence of fixed-size fragments. An experiment shows that, compared with a disk-based ODBMS with data fully cached, Xmas-SX shows only 6% better performance for the spatial range query. Before data fully cached, however, the performance gap is much bigger. For the update, Xmas-SX outperforms the ODBMS by more than ten times.
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Park, J.H., Kim, K., Cha, S.K., Song, M.S., Lee, S., Lee, J. (1999). A High-Performance Spatial Storage System Based on Main-Memory Database Architecture. In: Bench-Capon, T.J., Soda, G., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 1999. Lecture Notes in Computer Science, vol 1677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48309-8_100
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DOI: https://doi.org/10.1007/3-540-48309-8_100
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