A framework for query optimization in temporal databases
SSDBM V Proceedings of the fifth international conference on Statistical and scientific database management
Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
Selectivity estimation of temporal data manipulations
Information Sciences: an International Journal
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ACM Computing Surveys (CSUR)
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ACM SIGMOD Record
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Principles of distributed database systems (2nd ed.)
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VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
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VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
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Proceedings of the Ninth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
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ICDE '00 Proceedings of the 16th International Conference on Data Engineering
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IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
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ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
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Proceedings of the 2003 ACM SIGMOD international conference on Management of data
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Time-referenced data are pervasive in most real-world databases. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query optimization and evaluation mechanisms must be provided, either within the DBMS proper or as a source level translation from temporal queries to conventional SQL. This paper proposes a new approach: using a middleware component on top of a conventional DBMS. This component accepts temporal SQL statements and produces a corresponding query plan consisting of algebraic as well as regular SQL parts. The algebraic parts are processed by the middleware, while the SQL parts are processed by the DBMS. The middleware uses performance feedback from the DBMS to adapt its partitioning of subsequent queries into middleware and DBMS parts. The paper describes the architecture and implementation of the temporal middleware component, termed TANGO, which is based on the Volcano extensible query optimizer and the XXL query processing library. Experiments with the system demonstrate the utility of the middleware's internal processing capability and its cost-based mechanism for apportioning the processing between the middleware and the underlying DBMS.