Pre-aggregation in Spatial Data Warehouses

Data warehouses are becoming increasingly popular in the spatial domain, where they are used to analyze large amounts of spatial information for decision-making purposes. The data warehouse must provide very fast response times if popular analysis tools such as On-Line Analytical Processing [2](OLAP) are to be applied successfully. In order for the data analysis to have an adequate performance, pre-aggregation, i.e., pre-computation of partial query answers, is used to speed up query processing. Normally, the data structures in the data warehouse have to be very "well-behaved" in order for pre-aggregation to be feasible. However, this is not the case in many spatial applications.In this paper, we analyze the properties of topological relationships between 2D spatial objects with respect to pre-aggregation and show why traditional preaggregation techniques do not work in this setting. We then use this knowledge to significantly extend previous work on pre-aggregation for irregular data structures to also cover special spatial issues such as partially overlapping areas.

[1]  Torben Bach Pedersen,et al.  Multidimensional data modeling for complex data , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[2]  Jiawei Han,et al.  GeoMiner: a system prototype for spatial data mining , 1997, SIGMOD '97.

[3]  Nectaria Tryfona,et al.  An extended entity-relationship model for geographic applications , 1997, SGMD.

[4]  Nectaria Tryfona,et al.  Using abstractions for spatio-temporal conceptual modeling , 2000, SAC '00.

[5]  Donald R. Slutz,et al.  TerraServer: A Spatial Data Warehouse. , 2000, SIGMOD 2000.

[6]  Torben Bach Pedersen,et al.  Pre-Aggregation for Irregular OLAP Hierarchies with the TreeScape System , 2001, ICDE Demo Sessions.

[7]  MAX J. EGENHOFER,et al.  Point Set Topological Relations , 1991, Int. J. Geogr. Inf. Sci..

[8]  Torben Bach Pedersen,et al.  Extending Practical Pre-Aggregation in On-Line Analytical Processing , 1999, VLDB.

[9]  Jim Gray,et al.  Microsoft TerraServer , 1998, SIGMOD 2000.

[10]  Arie Shoshani,et al.  Summarizability in OLAP and statistical data bases , 1997, Proceedings. Ninth International Conference on Scientific and Statistical Database Management (Cat. No.97TB100150).

[11]  Hans-Peter Kriegel,et al.  Spatial Data Mining: A Database Approach , 1997, SSD.

[12]  Arie Shoshani,et al.  STORM: A Statistical Object Representation Model , 1990, IEEE Data Eng. Bull..

[13]  Torben Bach Pedersen,et al.  The TreeScape System: Reuse of Pre-Computed Aggregates over Irregular OLAP Hierarchies , 2000, VLDB.

[14]  Jeffrey F. Naughton,et al.  Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies , 1996, VLDB.

[15]  Jeffrey D. Ullman,et al.  Implementing data cubes efficiently , 1996, SIGMOD '96.

[16]  Jiawei Han,et al.  Efficient Polygon Amalgamation Methods for Spatial OLAP and Spatial Data Mining , 1999, SSD.

[17]  Christian S. Jensen,et al.  A foundation for capturing and querying complex multidimensional data , 2001, Inf. Syst..

[18]  Nectaria Tryfona,et al.  Conceptual Data Modeling for Spatiotemporal Applications , 1999, GeoInformatica.

[19]  Ashish Gupta,et al.  Aggregate-Query Processing in Data Warehousing Environments , 1995, VLDB.