Efficiently updating materialized views
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
ACM Transactions on Database Systems (TODS)
Updating derived relations: detecting irrelevant and autonomously computable updates
ACM Transactions on Database Systems (TODS)
ACM SIGMOD Record
Materialized view maintenance and integrity constraint checking: trading space for time
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
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Journal of the ACM (JACM)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
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DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
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SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Streaming queries over streaming data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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BIRTE'06 Proceedings of the 1st international conference on Business intelligence for the real-time enterprises
An architecture for recycling intermediates in a column-store
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
An architecture for recycling intermediates in a column-store
ACM Transactions on Database Systems (TODS)
Indexing forecast models for matching and maintenance
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
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Real-time materialized view maintenance has become increasingly popular, especially in real-time data warehousing and data streaming environments. Upon updates to base relations, maintaining the corresponding materialized views can bring a heavy burden to the RDBMS. A traditional method to mitigate this problem is to use the where clause condition in the materialized view definition to detect whether an update to a base relation is relevant and can affect the materialized view. However, this detection method does not consider the content in the base relations and hence misses a large number of filtering opportunities. In this paper, we propose a content-based method for detecting irrelevant updates to base relations of a materialized view. At the cost of using more space, this method increases the probability of catching irrelevant updates by judiciously designing filtering relations to capture the content in the base relations. Based on the content-based method, a prototype real-time data warehouse has been implemented on top of IBM's System S using IBM DB2. Using an analytical model and our prototype, we show that the content-based method can catch most (or all) irrelevant updates to base relations that are missed by the traditional method. Thus, when the fraction of irrelevant updates is non-negligible, the load on the RDBMS due to materialized view maintenance can be significantly reduced.