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
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Cubetree: organization of and bulk incremental updates on the data cube
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Maintenance of data cubes and summary tables in a warehouse
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Materialized views and data warehouses
ACM SIGMOD Record
An alternative storage organization for ROLAP aggregate views based on cubetrees
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
On supporting containment queries in relational database management systems
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
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
Selection of Views to Materialize in a Data Warehouse
ICDT '97 Proceedings of the 6th International Conference on Database Theory
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Efficient Execution of Range-Aggregate Queries in Data Warehouse Environments
ER '01 Proceedings of the 20th International Conference on Conceptual Modeling: Conceptual Modeling
QC-trees: an efficient summary structure for semantic OLAP
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Condensed Cube: An Efficient Approach to Reducing Data Cube Size
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Star-cubing: computing iceberg cubes by top-down and bottom-up integration
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
High-dimensional OLAP: a minimal cubing approach
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient evaluation of partially-dimensional range queries using adaptive r*-tree
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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In order to efficiently evaluate range-aggregate queries in data warehouse environments, several works on data cubes (such as the aggregate cubetree) are proposed. In the aggregate cubetree, each entry in every node stores the aggregate values of its corresponding subtree. Therefore, range-aggregate queries can be processed without visiting the child nodes whose parent nodes are fully included in the query range. However, the aggregate cubetree does not take range queries using partial dimensions and range queries without aggregation operations into account. That is, 1) a great deal of information that is irrelevant to the queries also has to be read from the disk for partially-dimensional range queries and 2) while it improves the performance of range queries with aggregate operations, it degrades the performance of the range queries without aggregate operations. In this paper, we proposed a novel index structure, called Aggregate-Tree (denoted as Ag-Tree), which gets rid of the above-mentioned weaknesses of the aggregate cubetree without any side effects. The experiments and discussions presented in this paper indicate that the new proposal is significant for range queries in data warehouse environments.