Query rewriting for semantic query optimization in spatial databases
Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a str...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mella, Eduardo [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Geoinformatica - Springer US, 1997, 23(2019), 1 vom: Jan., Seite 79-104 |
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| Übergeordnetes Werk: |
volume:23 ; year:2019 ; number:1 ; month:01 ; pages:79-104 |
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10.1007/s10707-018-00335-w |
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| 520 | |a Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). | ||
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| 700 | 1 | |a Bravo, Loreto |4 aut | |
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10.1007/s10707-018-00335-w doi (DE-627)OLC2038964769 (DE-He213)s10707-018-00335-w-p DE-627 ger DE-627 rakwb eng 550 VZ Mella, Eduardo verfasserin aut Query rewriting for semantic query optimization in spatial databases 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). Spatial databases Semantic optimization Spatial query rewriting Spatial integrity constraints Rodríguez, M. Andrea aut Bravo, Loreto aut Gatica, Diego aut Enthalten in Geoinformatica Springer US, 1997 23(2019), 1 vom: Jan., Seite 79-104 (DE-627)223334499 (DE-600)1357836-4 (DE-576)307633454 1384-6175 nnns volume:23 year:2019 number:1 month:01 pages:79-104 https://doi.org/10.1007/s10707-018-00335-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO GBV_ILN_11 GBV_ILN_70 AR 23 2019 1 01 79-104 |
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10.1007/s10707-018-00335-w doi (DE-627)OLC2038964769 (DE-He213)s10707-018-00335-w-p DE-627 ger DE-627 rakwb eng 550 VZ Mella, Eduardo verfasserin aut Query rewriting for semantic query optimization in spatial databases 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). Spatial databases Semantic optimization Spatial query rewriting Spatial integrity constraints Rodríguez, M. Andrea aut Bravo, Loreto aut Gatica, Diego aut Enthalten in Geoinformatica Springer US, 1997 23(2019), 1 vom: Jan., Seite 79-104 (DE-627)223334499 (DE-600)1357836-4 (DE-576)307633454 1384-6175 nnns volume:23 year:2019 number:1 month:01 pages:79-104 https://doi.org/10.1007/s10707-018-00335-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO GBV_ILN_11 GBV_ILN_70 AR 23 2019 1 01 79-104 |
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10.1007/s10707-018-00335-w doi (DE-627)OLC2038964769 (DE-He213)s10707-018-00335-w-p DE-627 ger DE-627 rakwb eng 550 VZ Mella, Eduardo verfasserin aut Query rewriting for semantic query optimization in spatial databases 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). Spatial databases Semantic optimization Spatial query rewriting Spatial integrity constraints Rodríguez, M. Andrea aut Bravo, Loreto aut Gatica, Diego aut Enthalten in Geoinformatica Springer US, 1997 23(2019), 1 vom: Jan., Seite 79-104 (DE-627)223334499 (DE-600)1357836-4 (DE-576)307633454 1384-6175 nnns volume:23 year:2019 number:1 month:01 pages:79-104 https://doi.org/10.1007/s10707-018-00335-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO GBV_ILN_11 GBV_ILN_70 AR 23 2019 1 01 79-104 |
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10.1007/s10707-018-00335-w doi (DE-627)OLC2038964769 (DE-He213)s10707-018-00335-w-p DE-627 ger DE-627 rakwb eng 550 VZ Mella, Eduardo verfasserin aut Query rewriting for semantic query optimization in spatial databases 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). Spatial databases Semantic optimization Spatial query rewriting Spatial integrity constraints Rodríguez, M. Andrea aut Bravo, Loreto aut Gatica, Diego aut Enthalten in Geoinformatica Springer US, 1997 23(2019), 1 vom: Jan., Seite 79-104 (DE-627)223334499 (DE-600)1357836-4 (DE-576)307633454 1384-6175 nnns volume:23 year:2019 number:1 month:01 pages:79-104 https://doi.org/10.1007/s10707-018-00335-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO GBV_ILN_11 GBV_ILN_70 AR 23 2019 1 01 79-104 |
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Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2038964769</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503062830.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10707-018-00335-w</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2038964769</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10707-018-00335-w-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mella, Eduardo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Query rewriting for semantic query optimization in spatial databases</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. 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