TY - CHAP
T1 - Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads
AU - Nagarkar, Parth
AU - Candan, Kasim
AU - Bhat, Aneesha
PY - 2015
Y1 - 2015
N2 - In most spatial data management applications, objects are represented in terms of their coordinates in a 2-dimensional space and search queries in this space are processed using spatial index structures. On the other hand, bitmap-based indexing, especially thanks to the compression opportunities bitmaps provide, has been shown to be highly effective for query processing workloads including selection and aggregation operations. In this paper, we show that bitmapbased indexing can also be highly effective for managing spatial data sets. More specifically, we propose a novel compressed spatial hierarchical bitmap (cSHB) index structure to support spatial range queries. We consider query workloads involving multiple range queries over spatial data and introduce and consider the problem of bitmap selection for identifying the appropriate subset of the bitmap files for processing the given spatial range query workload. We develop cost models for compressed domain range query processing and present query planning algorithms that not only select index nodes for query processing, but also associate appropriate bitwise logical operations to identify the data objects satisfying the range queries in the given workload. Experiment results confirm the efficiency and effectiveness of the proposed compressed spatial hierarchical bitmap (cSHB) index structure and the range query planning algorithms in supporting spatial range query workloads.
AB - In most spatial data management applications, objects are represented in terms of their coordinates in a 2-dimensional space and search queries in this space are processed using spatial index structures. On the other hand, bitmap-based indexing, especially thanks to the compression opportunities bitmaps provide, has been shown to be highly effective for query processing workloads including selection and aggregation operations. In this paper, we show that bitmapbased indexing can also be highly effective for managing spatial data sets. More specifically, we propose a novel compressed spatial hierarchical bitmap (cSHB) index structure to support spatial range queries. We consider query workloads involving multiple range queries over spatial data and introduce and consider the problem of bitmap selection for identifying the appropriate subset of the bitmap files for processing the given spatial range query workload. We develop cost models for compressed domain range query processing and present query planning algorithms that not only select index nodes for query processing, but also associate appropriate bitwise logical operations to identify the data objects satisfying the range queries in the given workload. Experiment results confirm the efficiency and effectiveness of the proposed compressed spatial hierarchical bitmap (cSHB) index structure and the range query planning algorithms in supporting spatial range query workloads.
UR - http://www.scopus.com/inward/record.url?scp=84953853408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84953853408&partnerID=8YFLogxK
U2 - 10.14778/2824032.2824038
DO - 10.14778/2824032.2824038
M3 - Chapter
AN - SCOPUS:84953853408
T3 - Proceedings of the VLDB Endowment
SP - 1382
EP - 1393
BT - Proceedings of the VLDB Endowment
PB - Association for Computing Machinery
T2 - 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
Y2 - 11 September 2006 through 11 September 2006
ER -