Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An efficient processing of range-MIN/MAX queries over data cube
Information Sciences: an International Journal
Range queries in dynamic OLAP data cubes
Data & Knowledge Engineering
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Hierarchical Prefix Cubes for Range-Sum Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Probabilistic Optimization of Top N Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Hierarchical Compact Cube for Range-Max Queries
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Range-Max/Min Query in OLAP Data Cube
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
Range Top/Bottom k Queries in OLAP Sparse Data Cubes
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Range Sum Queries in Dynamic OLAP Data Cubes
CODAS '01 Proceedings of the Third International Symposium on Cooperative Database Systems for Advanced Applications
Relative Prefix Sums: An Efficient Approach for Querying Dynamic OLAP Data Cubes
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Analysis of pre-computed partition top method for range top-k queries in OLAP data cubes
Proceedings of the eleventh international conference on Information and knowledge management
Histogram-by: A grouping operator for continuous domains
Data & Knowledge Engineering
Pruning attribute values from data cubes with diamond dicing
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
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In decision-support systems, the top k values are more informative than the max/min value. Unfortunately, the existing methods for range-max queries could not answer range top-k queries efficiently if applied directly. In this paper, we propose an efficient approach for range top-k processing, termed the Adaptive Pre-computed Partition Top method (APPT). The APPT method pre-computes a set of maximum values for each partitioned sub-block. The number of stored maximum values can be adjusted dynamically during run-time to adopt to the distribution of the query and the data. We show with experiments that our dynamic adaptation method improves in query cost as compared to other alternative methods.