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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... Engines with Global Page Ordering ................ Xiaohui Long, Torsten Suel (Polytechnic University, USA) XML Queries Processing I Path Queries on Compressed XML .............................................................
... Engines with Global Page Ordering ................ Xiaohui Long, Torsten Suel (Polytechnic University, USA) XML Queries Processing I Path Queries on Compressed XML .............................................................
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... Global Transactions from Multiple Recovery Log Files in a Partitioned Database System .......... 987 Chengfei Liu (University of South Australia, Australia), Bruce G. Lindsay (IBM Almaden Research Center, USA), Serge Bourbonnais ...
... Global Transactions from Multiple Recovery Log Files in a Partitioned Database System .......... 987 Chengfei Liu (University of South Australia, Australia), Bruce G. Lindsay (IBM Almaden Research Center, USA), Serge Bourbonnais ...
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... Global Optimization of Histograms. SIGMOD Conf. (2001) 223-234 [41] Jagadish H. V., Kapitskaia O., Ng R., Srivastava D.: Multi-Dimensional Substring Selectivity Estimation. VLDB Conf. (1999) 387-398 [42] Jagadish H. V., Koudas N ...
... Global Optimization of Histograms. SIGMOD Conf. (2001) 223-234 [41] Jagadish H. V., Kapitskaia O., Ng R., Srivastava D.: Multi-Dimensional Substring Selectivity Estimation. VLDB Conf. (1999) 387-398 [42] Jagadish H. V., Koudas N ...
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... global query pattern tree G-QPT by merging the query pattern trees in the database. Figure 5(a) shows the global query pattern obtained from the query pattern trees in Figure 3. The nodes in the G-QPT can be numbered using a preorder ...
... global query pattern tree G-QPT by merging the query pattern trees in the database. Figure 5(a) shows the global query pattern obtained from the query pattern trees in Figure 3. The nodes in the G-QPT can be numbered using a preorder ...
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... global village, databases should ideally support multilingual teact data equally efficiently. While current database systems do support management of multilingual data, we are not aware of any prior studies that compare and quantify ...
... global village, databases should ideally support multilingual teact data equally efficiently. While current database systems do support management of multilingual data, we are not aware of any prior studies that compare and quantify ...
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