CloudMdsQL: querying heterogeneous cloud data stores with a common language
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/6731 http://dx.doi.org/10.1007/s10619-015-7185-y |
Resumo: | The blooming of different cloud data management infrastructures, specialized for different kinds of data and tasks, has led to a wide diversification of DBMS interfaces and the loss of a common programming paradigm. In this paper, we present the design of a cloud multidatastore query language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The query engine has a fully distributed architecture, which provides important opportunities for optimization. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized, e.g. by pushing down select predicates, using bind join, performing join ordering, or planning intermediate data shipping. Our experimental validation, with three data stores (graph, document and relational) and representative queries, shows that CloudMdsQL satisfies the five important requirements for a cloud multidatastore query language. |
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7160 |
spelling |
CloudMdsQL: querying heterogeneous cloud data stores with a common languageThe blooming of different cloud data management infrastructures, specialized for different kinds of data and tasks, has led to a wide diversification of DBMS interfaces and the loss of a common programming paradigm. In this paper, we present the design of a cloud multidatastore query language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The query engine has a fully distributed architecture, which provides important opportunities for optimization. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized, e.g. by pushing down select predicates, using bind join, performing join ordering, or planning intermediate data shipping. Our experimental validation, with three data stores (graph, document and relational) and representative queries, shows that CloudMdsQL satisfies the five important requirements for a cloud multidatastore query language.2018-01-17T15:26:43Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6731http://dx.doi.org/10.1007/s10619-015-7185-yengKolev,BValduriez,PBondiombouy,CJimenez Peris,RPau,RJosé Orlando Pereirainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:53Zoai:repositorio.inesctec.pt:123456789/6731Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:45.849494Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
title |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
spellingShingle |
CloudMdsQL: querying heterogeneous cloud data stores with a common language Kolev,B |
title_short |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
title_full |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
title_fullStr |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
title_full_unstemmed |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
title_sort |
CloudMdsQL: querying heterogeneous cloud data stores with a common language |
author |
Kolev,B |
author_facet |
Kolev,B Valduriez,P Bondiombouy,C Jimenez Peris,R Pau,R José Orlando Pereira |
author_role |
author |
author2 |
Valduriez,P Bondiombouy,C Jimenez Peris,R Pau,R José Orlando Pereira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Kolev,B Valduriez,P Bondiombouy,C Jimenez Peris,R Pau,R José Orlando Pereira |
description |
The blooming of different cloud data management infrastructures, specialized for different kinds of data and tasks, has led to a wide diversification of DBMS interfaces and the loss of a common programming paradigm. In this paper, we present the design of a cloud multidatastore query language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The query engine has a fully distributed architecture, which provides important opportunities for optimization. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized, e.g. by pushing down select predicates, using bind join, performing join ordering, or planning intermediate data shipping. Our experimental validation, with three data stores (graph, document and relational) and representative queries, shows that CloudMdsQL satisfies the five important requirements for a cloud multidatastore query language. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2018-01-17T15:26:43Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.inesctec.pt/handle/123456789/6731 http://dx.doi.org/10.1007/s10619-015-7185-y |
url |
http://repositorio.inesctec.pt/handle/123456789/6731 http://dx.doi.org/10.1007/s10619-015-7185-y |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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