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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Page 36
... operators in our algebra, classified into four categories. All the operators listed in the table manipulate only Web relations, i.e., the result of any operator as well as its operands are plain, ranked, or ordered Web relations. In the ...
... operators in our algebra, classified into four categories. All the operators listed in the table manipulate only Web relations, i.e., the result of any operator as well as its operands are plain, ranked, or ordered Web relations. In the ...
Page 38
... operator (see Section 4.3) can be employed. 4.3 Ranking and ordering operators In the previous section, we extended the semantics of traditional relational algebra operators to handle ordered and ranked Web relations as operands. In ...
... operator (see Section 4.3) can be employed. 4.3 Ranking and ordering operators In the previous section, we extended the semantics of traditional relational algebra operators to handle ordered and ranked Web relations as operands. In ...
Page 40
... operator accepts two aggregation functions as parameters (A.): a defines how to combine page and link ranks and b specifies how to aggregate all the incoming ranks (since multiple links may may point to the same target page). For ...
... operator accepts two aggregation functions as parameters (A.): a defines how to combine page and link ranks and b specifies how to aggregate all the incoming ranks (since multiple links may may point to the same target page). For ...
Page 41
... operator and compute the outneighborhood of this ranked set of pages (labeled T, f). In the second part of the query graph, we join T, f with T to retrieve the domain of each page (the “ppomain” attribute), group on p[)omain (summing up ...
... operator and compute the outneighborhood of this ranked set of pages (labeled T, f). In the second part of the query graph, we join T, f with T to retrieve the domain of each page (the “ppomain” attribute), group on p[)omain (summing up ...
Page 43
... operators. So far, we have treated each navigation operation in isolation when identifying the ICS and computing costs. However, for queries involving multiple navigation operators, the estimated cost of one operator is influenced by ...
... operators. So far, we have treated each navigation operation in isolation when identifying the ICS and computing costs. However, for queries involving multiple navigation operators, the estimated cost of one operator is influenced by ...
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