Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the VLDB Endowment
PublisherAssociation for Computing Machinery
Pages1382-1393
Number of pages12
Volume8
Edition12
StatePublished - 2015
Event3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: Sep 11 2006Sep 11 2006

Other

Other3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
CountryKorea, Republic of
CitySeoul
Period9/11/069/11/06

Fingerprint

Query processing
Processing
Planning
Information management
Agglomeration
Costs
Experiments

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

Cite this

Nagarkar, P., Candan, K., & Bhat, A. (2015). Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads. In Proceedings of the VLDB Endowment (12 ed., Vol. 8, pp. 1382-1393). Association for Computing Machinery.

Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads. / Nagarkar, Parth; Candan, Kasim; Bhat, Aneesha.

Proceedings of the VLDB Endowment. Vol. 8 12. ed. Association for Computing Machinery, 2015. p. 1382-1393.

Research output: Chapter in Book/Report/Conference proceedingChapter

Nagarkar, P, Candan, K & Bhat, A 2015, Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads. in Proceedings of the VLDB Endowment. 12 edn, vol. 8, Association for Computing Machinery, pp. 1382-1393, 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006, Seoul, Korea, Republic of, 9/11/06.
Nagarkar P, Candan K, Bhat A. Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads. In Proceedings of the VLDB Endowment. 12 ed. Vol. 8. Association for Computing Machinery. 2015. p. 1382-1393
Nagarkar, Parth ; Candan, Kasim ; Bhat, Aneesha. / Compressed spatial hierarchical bitmap (cSHB) indexes for efficiently processing spatial range query workloads. Proceedings of the VLDB Endowment. Vol. 8 12. ed. Association for Computing Machinery, 2015. pp. 1382-1393
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