URI | http://purl.tuc.gr/dl/dias/6076C420-0BBC-4841-AD75-54DEEA60248B | - |
Αναγνωριστικό | http://www.vldb.org/conf/2002/S13P03.pdf | - |
Γλώσσα | en | - |
Μέγεθος | 12 pages | en |
Τίτλος | Structure and value synopses for XML data graphs | en |
Δημιουργός | Polyzotis, Neoklis | en |
Δημιουργός | Garofalakis Minos | en |
Δημιουργός | Γαροφαλακης Μινως | el |
Περίληψη | All existing proposals for querying XML (e.g.,
XQuery) rely on a pattern-specification language that
allows (1) path navigation and branching through the
label structure of the XML data graph, and (2) predicates
on the values of specific path/branch nodes, in
order to reach the desired data elements. Optimizing
such queries depends crucially on the existence of concise
synopsis structures that enable accurate compiletime
selectivity estimates for complex path expressions
over graph-structured XML data. In this paper, we
extent our earlier work on structural XSKETCH synopses
and we propose an (augmented) XSKETCH synopsis
model that exploits localized stability and valuedistribution
summaries (e.g., histograms) to accurately
capture the complex correlation patterns that can exist
between and across path structure and element values in
the data graph. We develop a systematic XSKETCH estimation
framework for complex path expressions with
value predicates and we propose an efficient heuristic
algorithm based on greedy forward selection for building
an effective XSKETCH for a given amount of space
(which is, in general, an N P-hard optimization problem).
Implementation results with both synthetic and
real-life data sets verify the effectiveness of our approach. | en |
Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
Τύπος | Conference Full Paper | en |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2015-12-01 | - |
Ημερομηνία Δημοσίευσης | 2002 | - |
Θεματική Κατηγορία | Databases | en |
Βιβλιογραφική Αναφορά | N. Polyzotis and M. Garofalakis, "Structure and value synopses for XML data graphs", in 28th International Conference on Very Large Data Bases, August 2002, pp. 466-477. | en |