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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... parameter (Webster's “classes”) the number of pixels that have this value (Webster's “frequencies”). Such a ... parameter (the next characteristic), and its subclass endbiased, which requires at most one non-singleton bucket. • Sort ...
... parameter (Webster's “classes”) the number of pixels that have this value (Webster's “frequencies”). Such a ... parameter (the next characteristic), and its subclass endbiased, which requires at most one non-singleton bucket. • Sort ...
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... parameter values into a bucket. Following [67], we use p(s,v) to denote a serial histogram class with partition constraint p, sort parameter 8, and source parameter u. Construction Algorithm: Given a particular partition rule, this is ...
... parameter values into a bucket. Following [67], we use p(s,v) to denote a serial histogram class with partition constraint p, sort parameter 8, and source parameter u. Construction Algorithm: Given a particular partition rule, this is ...
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... parameter*. Ten years ago The above result might have not had the impact it did if it had remained true only for the restricted query class it was first proved for. Soon afterwards, however, in VLDB'93, it was generalized for arbitrary ...
... parameter*. Ten years ago The above result might have not had the impact it did if it had remained true only for the restricted query class it was first proved for. Soon afterwards, however, in VLDB'93, it was generalized for arbitrary ...
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... 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 multi-dimensional equi ...
... 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 multi-dimensional equi ...
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... parameter values. A key contribution in this direction has been the proposal of a dynamic-programming based algorithm that identifies the v-optimal histogram (for any sort and source parameter) in time that is quadratic in the number of ...
... parameter values. A key contribution in this direction has been the proposal of a dynamic-programming based algorithm that identifies the v-optimal histogram (for any sort and source parameter) in time that is quadratic in the number of ...
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