Efficiently updating materialized views
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
ACM Transactions on Database Systems (TODS)
Maintaining views incrementally
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Efficient maintenance of materialized mediated views
SIGMOD '95 Proceedings of the 1995 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
On-line warehouse view maintenance
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Shrinking the warehouse update Window
SIGMOD '99 Proceedings of the 1999 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
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
DyDa: data warehouse maintenance in fully concurrent environments
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
The Strobe algorithms for multi-source warehouse consistency
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Efficient incremental view maintenance in data warehouses
Proceedings of the tenth international conference on Information and knowledge management
Batch data warehouse maintenance in dynamic environments
Proceedings of the eleventh international conference on Information and knowledge management
Optimizing Queries Across Diverse Data Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
A Transactional Model for Data Warehouse Maintenance
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Mariposa: a wide-area distributed database system
The VLDB Journal — The International Journal on Very Large Data Bases
Parallel multisource view maintenance
The VLDB Journal — The International Journal on Very Large Data Bases
Restructuring batch view maintenance efficiently
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Multiversion-based view maintenance over distributed data sources
ACM Transactions on Database Systems (TODS)
Asymmetric Batch Incremental View Maintenance
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
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Materialized views defined over distributed data sources can be utilized by many applications to ensure better access, reliable performance, and high availability. Technology for maintaining materialized views is thus critical for providing up-to-date results since a stale view extent may not help or even mislead these applications. State-of-the-art incremental view maintenance requires O(n^2) or more remote maintenance queries with n being the number of data sources in the view definition. In this work, we propose two novel maintenance strategies, namely adjacent grouping and conditional grouping, that dramatically reduce the number of maintenance queries required to maintain the materialized views. This reduction in the number of maintenance queries brings the basic trade-off between the complexity of each query and the total number of maintenance queries that can be exploited to improve maintenance performance. The proposed maintenance strategies have been implemented in a working prototype system called TxnWrap. Experimental studies illustrate that our proposed strategies are able to achieve about 400% performance improvement in terms of total processing time compared with existing batch algorithms in a majority of cases.