The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
The Asilomar report on database research
ACM SIGMOD Record
Making B+- trees cache conscious in main memory
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimizing multidimensional index trees for main memory access
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Main-memory index structures with fixed-size partial keys
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Improving index performance through prefetching
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
O-Trees: A Constraint-Based Index Structure
ADC '00 Proceedings of the Australasian Database Conference
SSDBM '01 Proceedings of the 13th International Conference on Scientific and Statistical Database Management
An efficient cache conscious multi-dimensional index structure
Information Processing Letters
An Extended R-Tree Indexing Method Using Selective Prefetching in Main Memory
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
An efficient cache conscious multi-dimensional index structure
Information Processing Letters
An efficient compression technique for a multi-dimensional index in main memory
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
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Cache-conscious behaviour of data structures becomes more important as memory sizes increase and whole databases fit into main memory. For spatial data, R-trees, originally designed for disk-based data, can be adopted for in-memory applications. In this paper, we will investigate how the small amount of space in an in-memory R-tree node can be used better to make R-trees more cache-conscious. We observe that many entries share sides with their parents, and introduce the partial R-tree which only stores information that is not given by the parent node. Our experiments showed that the partial R-tree shows up to 30 per cent better performance than the traditional R-tree. We also investigated if we could improve the search performance by storing more descriptive information instead of the standard minimum bounding box without decreasing the fanout of the R-tree. The partial static O-tree is based on the O-tree, but stores only the most important part of the information of an O-tree box. Experiments showed that this approach reduces the search time for line data by up to 60 per cent.