Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
Optimization of nested queries in a complex object model
EDBT '94 Proceedings of the 4th international conference on extending database technology: Advances in database technology
A data model for supporting on-line analytical processing
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Integrating association rule mining with relational database systems: alternatives and implications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The PanQ tool and EMF SQL for complex data management
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Orthogonal optimization of subqueries and aggregation
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Optimizing object queries using an effective calculus
ACM Transactions on Database Systems (TODS)
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Starburst Mid-Flight: As the Dust Clears
IEEE Transactions on Knowledge and Data Engineering
Efficient OLAP query processing in distributed data warehouses
Information Systems - Special issue: Best papers from EDBT 2002
Optimizing Queries with Aggregate Views
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Complex Aggregation at Multiple Granularities
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Performing Group-By before Join
Proceedings of the Tenth 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
The MD-join: An Operator for Complex OLAP
Proceedings of the 17th International Conference on Data Engineering
Groupwise Processing of Relational Queries
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Materialized Views Selection in a Multidimensional Database
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Including Group-By in Query Optimization
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Aggregate-Query Processing in Data Warehousing Environments
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Eager Aggregation and Lazy Aggregation
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Querying Multiple Features of Groups in Relational Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Foundation for Multi-dimensional Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Proceedings of the International Workshop on Databases in Telecommunications
Generalized MD-Joins: Evaluation and Reduction to SQL
DBTel '01 Proceedings of the VLDB 2001 International Workshop on Databases in Telecommunications II
Modeling Multidimensional Databases, Cubes and Cube Operations
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Evaluation of Ad Hoc OLAP: In-Place Computation
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Nested Queries in Object Bases
DBLP-4 Proceedings of the Fourth International Workshop on Database Programming Languages - Object Models and Languages
Querying Multidimensional Databases
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Improved Unnesting Algorithms for Join Aggregate SQL Queries
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Reasoning with Aggregation Constraints
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
The Volcano Optimizer Generator: Extensibility and Efficient Search
Proceedings of the Ninth International Conference on Data Engineering
Spreadsheets in RDBMS for OLAP
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
On relational support for XML publishing: beyond sorting and tagging
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Advanced SQL modeling in RDBMS
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Bridging the gap between OLAP and SQL
VLDB '05 Proceedings of the 31st international conference on Very large data bases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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The SQL:2003 standard introduced window functions to enhance the analytical processing capabilities of SQL. The key concept of window functions is to sort the input relation and to compute the aggregate results during a scan of the sorted relation. For multi-dimensional OLAP queries with aggregation groups defined by a general @q condition an appropriate ordering does not exist, though, and hence expensive join-based solutions are required. In this paper we introduce @q@?constrained multi-dimensional aggregation (@q@?MDA), which supports multi-dimensional OLAP queries with aggregation groups defined by inequalities. @q@?MDA is not based on an ordering of the data relation. Instead, the tuples that shall be considered for computing an aggregate value can be determined by a general @q condition. This facilitates the formulation of complex queries, such as multi-dimensional cumulative aggregates, which are difficult to express in SQL because no appropriate ordering exists. We present algebraic transformation rules that demonstrate how the @q@?MDA interacts with other operators of a multi-set algebra. Various techniques for achieving an efficient evaluation of the @q@?MDA are investigated, and we integrate them into concrete evaluation algorithms and provide cost formulas. An empirical evaluation with data from the TPC-H benchmark confirms the scalability of the @q@?MDA operator and shows performance improvements of up to one order of magnitude over equivalent SQL implementations.