Abstract
R-Trees have been traditionally optimized for I/O performance with disk pages as tree nodes. Recently, researchers have proposed cache-conscious variations of R-Trees optimized for CPU cache performance in main memory environments, where the node size is wider than the cache line size and more entries are packed in a node by compressing MBR keys. However, because there is a big difference between the node sizes of two types of R-Trees, disk-optimized R-Trees show poor cache performance while cache-optimized R-Trees exhibit poor disk performance. In this paper, we propose a cache and disk optimized R-Tree, called the TR-Tree (Two-way optimized R-Tree). We evaluate the in-page leaf and non-leaf node sizes and the height of the in-page tree to minimize the cache miss cost for searching a TR-Tree. In addition, we fit nodes into disk pages to maximize the disk I/O performance. Our implementation achieves better cache and disk performance than disk-optimized R-Trees: a factor of 6-28 improvement for insertions and a factor of 1.28-2.00 improvement for range queries.
This work was supported by the Brain Korea 21 Project.
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Park, M., Lee, S. (2003). Optimizing Both Cache and Disk Performance of R-Trees. In: MaÅ™Ãk, V., Retschitzegger, W., Å tÄ›pánková, O. (eds) Database and Expert Systems Applications. DEXA 2003. Lecture Notes in Computer Science, vol 2736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45227-0_15
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DOI: https://doi.org/10.1007/978-3-540-45227-0_15
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