Results 21 to 30 of about 34,853 (265)
Proceedings of the 2019 International Conference on Management of Data, 2019 In recent decades, we observed the rapid growth of several big data platforms. Each of them is designed for specific demands. For instance, Spark can efficiently process iterative queries, while Storm is designed for in-memory processing. In this context, the complexity of these distributed systems make it much harder to develop rigorous cost models ...
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LocationSpark: In-memory Distributed Spatial Query Processing and Optimization
Frontiers in Big Data, 2020 Due to the ubiquity of spatial data applications and the large amounts of spatial data that these applications generate and process, there is a pressing need for scalable spatial query processing.
Mingjie Tang +5 more
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Query optimization of distributed database based on multiple ant colony genetic algorithm
上海师范大学学报. 自然科学版, 2018 In the light of the defect of single algorithm of query optimization,this paper proposes a multiple ant colony genetic algorithm combining the advantages of ant colony algorithm and genetic algorithmwhich overcomes the blindness of early search of ant ...
Zhou Ying, Chen Junhua
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Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, 2022 Volume data yang sangat besar dari tim surveyor Perencanaan dan Pengendalian Penanganan Bencana(P3B) menciptakan masalah yang luas dan beragam sehingga dapat menghabiskan sumber daya sistem dan waktu pemrosesan yang terbilang lama.
Annisa Heparyanti Safitri +3 more
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Enhancing MongoDB query performance through index optimization [PDF]
E3S Web of ConferencesThis article delves into the critical aspect of enhancing query performance in MongoDB through meticulous index optimization. It begins with an introduction to MongoDB's unique document-oriented data storage approach and its inherent scalability, which ...
Nuriev Marat +4 more
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Query optimization for dynamic imputation [PDF]
Proceedings of the VLDB Endowment, 2017 Missing values are common in data analysis and present a usability challenge. Users are forced to pick between removing tuples with missing values or creating a cleaned version of their data by applying a relatively expensive imputation strategy. Our system, ImputeDB, incorporates imputation into a cost-based query optimizer, performing necessary ...
Cambronero, José +3 more
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SPARQL Query Optimization Based on Longest Property Path Filtering [PDF]
Jisuanji gongcheng, 2018 A large number of intermediate results during executing SPARQL query greatly affect the query efficiency.For this,a query optimization method with two phases is proposed.In the first phase,it divides a query that contains the same variable into a block ...
LIN Xiaoqing,ZHANG Fu,CHENG Jingwei
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Distributed Query Optimization by Query Trading
, 2004 Large-scale distributed environments, where each node is completely autonomous and offers services to its peers through external communication, pose significant challenges to query processing and optimization. Autonomy is the main source of the problem, as it results in lack of knowledge about any particular node with respect to the information it can ...
Pentaris, F., Loannidis, Y.
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Pipelining in multi-query optimization [PDF]
Journal of Computer and System Sciences, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
DALVI, NILESH N +3 more
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Multiple-query optimization [PDF]
ACM Transactions on Database Systems, 1988 Some recently proposed extensions to relational database systems, as well as to deductive database systems, require support for multiple-query processing. For example, in a database system enhanced with inference capabilities, a simple query involving a rule with multiple definitions may expand to more than one actual query that has to be run over the ...
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