Efficiently updating materialized views
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Maintaining views incrementally
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
EDBT '94 Proceedings of the 4th international conference on extending database technology: Advances in database technology
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Algorithms for deferred view maintenance
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
How to roll a join: asynchronous incremental view maintenance
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimizing queries using materialized views: a practical, scalable solution
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Performing Group-By before Join
Proceedings of the Tenth International Conference on Data Engineering
Optimizing Queries with Materialized Views
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th 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
The Complexity of Transformation-Based Join Enumeration
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
The Volcano Optimizer Generator: Extensibility and Efficient Search
Proceedings of the Ninth International Conference on Data Engineering
OPT++ : an object-oriented implementation for extensible database query optimization
The VLDB Journal — The International Journal on Very Large Data Bases
The GMAP: a versatile tool for physical data independence
The VLDB Journal — The International Journal on Very Large Data Bases
Selecting and using views to compute aggregate queries
ICDT'05 Proceedings of the 10th international conference on Database Theory
Query evaluation using overlapping views: completeness and efficiency
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Query optimization using restructured views
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Efficient exploitation of similar subexpressions for query processing
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Query optimization using restructured views: Theory and experiments
Information Systems
Equivalence of nested queries with mixed semantics
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Incremental aggregation on multiple continuous queries
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
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Appropriately selected materialized views (also called indexed views) can speed up query execution by orders of magnitude. Most database systems limit support for materialized views to select-project-join expressions, possibly with a group-by, over base tables because this class of views can be efficiently maintained incrementally and thus kept up to date with the underlying source tables. However, limiting views to reference only base tables restricts the class of queries that can be supported by materialized views. View stacking (also called views on views) relaxes one restriction by allowing a materialized view to reference both base tables and other materialized views. This extends materialized view support to additional types of queries. This paper describes a prototype implementation of stacked views within Microsoft SQL Server and explains which classes of queries can be supported. To support view matching for stacked views, a signature mechanism was added to the optimizer. This mechanism turned out to be beneficial also for regular views by significantly speeding up view matching.