Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 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
Answering complex SQL queries using automatic summary tables
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Practical Applications of Triggers and Constraints: Success and Lingering Issues (10-Year Award)
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Aggregate Maintenance for Data Warehousing in Informix Red Brick Vista
Proceedings of the 27th International Conference on Very Large Data Bases
GPIVOT: Efficient Incremental Maintenance of Complex ROLAP Views
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Incremental maintenance of aggregate and outerjoin expressions
Information Systems
Efficient incremental maintenance of data cubes
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Incremental maintenance for non-distributive aggregate functions
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Lazy maintenance of materialized views
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
The Tradeoff of Delta Table Merging and Re-writing Algorithms in What-If Analysis Application
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
An efficient method for maintaining data cubes incrementally
Information Sciences: an International Journal
An incremental maintenance scheme of data cubes
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Preprocessing for fast refreshing materialized views in DB2
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
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Materialized views (or Automatic Summary Tables—ASTs) are commonly used to improve the performance of aggregation queries by orders of magnitude. In contrast to regular tables, ASTs are synchronized by the database system. In this paper, we present techniques for maintaining cube ASTs. Our implementation is based on IBM DB2 UDB.