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. |
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... Constraints The Generalized Pre-Grouping Transformation: Aggregate-Query Optimization in the Presence of Dependencies ... 644 Aris Tsois, Timos Sellis (National Technical University of Athens, Greece) Estimating the Output Cardinality ...
... Constraints The Generalized Pre-Grouping Transformation: Aggregate-Query Optimization in the Presence of Dependencies ... 644 Aris Tsois, Timos Sellis (National Technical University of Athens, Greece) Estimating the Output Cardinality ...
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... Constraint: This is a mathematical constraint on the source parameter that uniquely identifies a single histogram within its partition class. Several partition constraints have been proposed so far, e.g., equi-sum, v-optimal, macdiff ...
... Constraint: This is a mathematical constraint on the source parameter that uniquely identifies a single histogram within its partition class. Several partition constraints have been proposed so far, e.g., equi-sum, v-optimal, macdiff ...
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... constraint and source parameter used. In combination with the most effective partition constraints and source parameters (i.e., v-optimal or maxdiff with frequency or area), MHIST-2 represented a dramatic improvement over the original ...
... constraint and source parameter used. In combination with the most effective partition constraints and source parameters (i.e., v-optimal or maxdiff with frequency or area), MHIST-2 represented a dramatic improvement over the original ...
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... constraint. Most such constraints (e.g., equi-sum, maxdiff, compressed) have straightforward calculations that are efficient. This is not the case, however, for what has been shown to be the most effective constraint, i.e., v-optimal ...
... constraint. Most such constraints (e.g., equi-sum, maxdiff, compressed) have straightforward calculations that are efficient. This is not the case, however, for what has been shown to be the most effective constraint, i.e., v-optimal ...
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... constraints in a data stream environment. To attain the feature of one data scan, the occurrence frequency of a temporal pattern is first defined in accordance with the time constraint of sliding windows. Specifically, the data ...
... constraints in a data stream environment. To attain the feature of one data scan, the occurrence frequency of a temporal pattern is first defined in accordance with the time constraint of sliding windows. Specifically, the data ...
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