Proceedings 2003 VLDB Conference: 29th International Conference on Very Large Databases (VLDB)Morgan Kaufmann, 2003 M12 2 - 1050 pages Proceedings of the 29th Annual International Conference on Very Large Data Bases held in Berlin, Germany on September 9-12, 2003. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology. |
From inside the book
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... .................................................. 632 Dengfeng Gao, Richard T. Snodgrass (University of Arizona, USA) Aggregation, Prediction & Constraints The Generalized Pre-Grouping Transformation: Aggregate-Query Optimization.
... .................................................. 632 Dengfeng Gao, Richard T. Snodgrass (University of Arizona, USA) Aggregation, Prediction & Constraints The Generalized Pre-Grouping Transformation: Aggregate-Query Optimization.
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... Query Optimization in the Presence of Dependencies ... 644 Aris Tsois, Timos Sellis (National Technical University of Athens, Greece) Estimating the Output Cardinality of Partial Preaggregation with a Measure of Clusteredness ...
... Query Optimization in the Presence of Dependencies ... 644 Aris Tsois, Timos Sellis (National Technical University of Athens, Greece) Estimating the Output Cardinality of Partial Preaggregation with a Measure of Clusteredness ...
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... query decomposition (a source of accuracy issues for hand-coded tasks), query optimization for reasonable responsiveness, translation between incoming/outgoing SQL and native APIs, connection management as well as data type and platform ...
... query decomposition (a source of accuracy issues for hand-coded tasks), query optimization for reasonable responsiveness, translation between incoming/outgoing SQL and native APIs, connection management as well as data type and platform ...
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... query optimization (for the former) or pre-execution user-level query feedback (for both). Our discussion below focuses exactly on these two, especially rangequery selectivity estimation as this is the most popular issue in the ...
... query optimization (for the former) or pre-execution user-level query feedback (for both). Our discussion below focuses exactly on these two, especially rangequery selectivity estimation as this is the most popular issue in the ...
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... query answering, note that typically indices are built assuming all values ... Optimization Workshop”, which was organized in conjunction with SIGMOD'89 in ... query optimization, we started collaborating with him on the error propagation ...
... query answering, note that typically indices are built assuming all values ... Optimization Workshop”, which was organized in conjunction with SIGMOD'89 in ... query optimization, we started collaborating with him on the error propagation ...
Contents
17 | |
31 | |
Part 4 Industrial Sessions | 935 |
Part 5 Panels | 1041 |
Part 6 Demo Sessions | 1051 |
Author Index | 1153 |
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Common terms and phrases
ACM SIGMOD algorithm applications approach attribute average bisimulation bucket buffer cache misses clustering compressed compute Conf constraints contains context nodes corresponding cost Data Bubble data mining data set data stream database systems DBLP defined denote distance distributed edge efficient elements engine estimation evaluation example execution experiments Figure function global graph hash join hash table histograms ICDE implementation input integration interface join join algorithm load matching merge algorithm method micro-clusters MJoin operator optimization output PAC-Man Pagerank parameter partition path expression performance predicate probe problem Proc query optimization query plan query processing ranking relation repository retrieval rithm scalability scan schema Section selection semantics sequence server shows SIGMOD storage stored structure subtree techniques tion tree pattern tuples Unicode update VLDB Web.Views window workload XFDs XML document XML query XPath