DBM-Tree: trading height-balancing for performance in metric access methods
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Computer Society |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100004 |
Resumo: | Metric Access Methods (MAM) are employed to accelerate the processing of similarity queries, such as the range and the k-nearest neighbor queries. Current methods, such as the Slim-tree and the M-tree, improve the query performance minimizing the number of disk accesses, keeping a constant height of the structures stored on disks (height-balanced trees). However, the overlapping between their nodes has a very high influence on their performance. This paper presents a new dynamic MAM called the DBM-tree (Density-Based Metric tree), which can minimize the overlap between high-density nodes by relaxing the height-balancing of the structure. Thus, the height of the tree is larger in denser regions, in order to keep a tradeoff between breadth-searching and depth-searching. An underpinning for cost estimation on tree structures is their height, so we show a non-height dependable cost model that can be applied for DBM-tree. Moreover, an optimization algorithm called Shrink is also presented, which improves the performance of an already built DBM-tree by reorganizing the elements among their nodes. Experiments performed over both synthetic and real world datasets showed that the DBM-tree is, in average, 50% faster than traditional MAM and reduces the number of distance calculations by up to 72% and disk accesses by up to 66%. After performing the Shrink algorithm, the performance improves up to 40% regarding the number of disk accesses for range and k-nearest neighbor queries. In addition, the DBM-tree scales up well, exhibiting linear performance with growing number of elements in the database. |
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Journal of the Brazilian Computer Society |
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DBM-Tree: trading height-balancing for performance in metric access methodsMetric Access MethodMetric TreeIndexingSimilarity QueriesMetric Access Methods (MAM) are employed to accelerate the processing of similarity queries, such as the range and the k-nearest neighbor queries. Current methods, such as the Slim-tree and the M-tree, improve the query performance minimizing the number of disk accesses, keeping a constant height of the structures stored on disks (height-balanced trees). However, the overlapping between their nodes has a very high influence on their performance. This paper presents a new dynamic MAM called the DBM-tree (Density-Based Metric tree), which can minimize the overlap between high-density nodes by relaxing the height-balancing of the structure. Thus, the height of the tree is larger in denser regions, in order to keep a tradeoff between breadth-searching and depth-searching. An underpinning for cost estimation on tree structures is their height, so we show a non-height dependable cost model that can be applied for DBM-tree. Moreover, an optimization algorithm called Shrink is also presented, which improves the performance of an already built DBM-tree by reorganizing the elements among their nodes. Experiments performed over both synthetic and real world datasets showed that the DBM-tree is, in average, 50% faster than traditional MAM and reduces the number of distance calculations by up to 72% and disk accesses by up to 66%. After performing the Shrink algorithm, the performance improves up to 40% regarding the number of disk accesses for range and k-nearest neighbor queries. In addition, the DBM-tree scales up well, exhibiting linear performance with growing number of elements in the database.Sociedade Brasileira de Computação2006-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100004Journal of the Brazilian Computer Society v.11 n.3 2006reponame:Journal of the Brazilian Computer Societyinstname:Sociedade Brasileira de Computação (SBC)instacron:UFRGS10.1007/BF03192381info:eu-repo/semantics/openAccessVieira,Marcos R.Traina Jr.,CaetanoChino,Fabio J. T.Traina,Agma J. M.eng2010-10-26T00:00:00Zoai:scielo:S0104-65002006000100004Revistahttps://journal-bcs.springeropen.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpjbcs@icmc.sc.usp.br1678-48040104-6500opendoar:2010-10-26T00:00Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)false |
dc.title.none.fl_str_mv |
DBM-Tree: trading height-balancing for performance in metric access methods |
title |
DBM-Tree: trading height-balancing for performance in metric access methods |
spellingShingle |
DBM-Tree: trading height-balancing for performance in metric access methods Vieira,Marcos R. Metric Access Method Metric Tree Indexing Similarity Queries |
title_short |
DBM-Tree: trading height-balancing for performance in metric access methods |
title_full |
DBM-Tree: trading height-balancing for performance in metric access methods |
title_fullStr |
DBM-Tree: trading height-balancing for performance in metric access methods |
title_full_unstemmed |
DBM-Tree: trading height-balancing for performance in metric access methods |
title_sort |
DBM-Tree: trading height-balancing for performance in metric access methods |
author |
Vieira,Marcos R. |
author_facet |
Vieira,Marcos R. Traina Jr.,Caetano Chino,Fabio J. T. Traina,Agma J. M. |
author_role |
author |
author2 |
Traina Jr.,Caetano Chino,Fabio J. T. Traina,Agma J. M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Vieira,Marcos R. Traina Jr.,Caetano Chino,Fabio J. T. Traina,Agma J. M. |
dc.subject.por.fl_str_mv |
Metric Access Method Metric Tree Indexing Similarity Queries |
topic |
Metric Access Method Metric Tree Indexing Similarity Queries |
description |
Metric Access Methods (MAM) are employed to accelerate the processing of similarity queries, such as the range and the k-nearest neighbor queries. Current methods, such as the Slim-tree and the M-tree, improve the query performance minimizing the number of disk accesses, keeping a constant height of the structures stored on disks (height-balanced trees). However, the overlapping between their nodes has a very high influence on their performance. This paper presents a new dynamic MAM called the DBM-tree (Density-Based Metric tree), which can minimize the overlap between high-density nodes by relaxing the height-balancing of the structure. Thus, the height of the tree is larger in denser regions, in order to keep a tradeoff between breadth-searching and depth-searching. An underpinning for cost estimation on tree structures is their height, so we show a non-height dependable cost model that can be applied for DBM-tree. Moreover, an optimization algorithm called Shrink is also presented, which improves the performance of an already built DBM-tree by reorganizing the elements among their nodes. Experiments performed over both synthetic and real world datasets showed that the DBM-tree is, in average, 50% faster than traditional MAM and reduces the number of distance calculations by up to 72% and disk accesses by up to 66%. After performing the Shrink algorithm, the performance improves up to 40% regarding the number of disk accesses for range and k-nearest neighbor queries. In addition, the DBM-tree scales up well, exhibiting linear performance with growing number of elements in the database. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100004 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100004 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1007/BF03192381 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Computação |
publisher.none.fl_str_mv |
Sociedade Brasileira de Computação |
dc.source.none.fl_str_mv |
Journal of the Brazilian Computer Society v.11 n.3 2006 reponame:Journal of the Brazilian Computer Society instname:Sociedade Brasileira de Computação (SBC) instacron:UFRGS |
instname_str |
Sociedade Brasileira de Computação (SBC) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Journal of the Brazilian Computer Society |
collection |
Journal of the Brazilian Computer Society |
repository.name.fl_str_mv |
Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC) |
repository.mail.fl_str_mv |
jbcs@icmc.sc.usp.br |
_version_ |
1754734669907099648 |