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Статті в журналах з теми "Database Operators"
Demetrovic, J., L. O. Libkin, and I. B. Muchnik. "Database models and closure operators." Cybernetics and Systems Analysis 27, no. 1 (January 1991): 53–67. http://dx.doi.org/10.1007/bf01068647.
Повний текст джерелаBandle, Maximilian, and Jana Giceva. "Database technology for the masses." Proceedings of the VLDB Endowment 14, no. 11 (July 2021): 2483–90. http://dx.doi.org/10.14778/3476249.3476296.
Повний текст джерелаSichert, Moritz, and Thomas Neumann. "User-defined operators." Proceedings of the VLDB Endowment 15, no. 5 (January 2022): 1119–31. http://dx.doi.org/10.14778/3510397.3510408.
Повний текст джерелаAl Marri, Wadha J., Qutaibah Malluhi, Mourad Ouzzani, Mingjie Tang, and Walid G. Aref. "The similarity-aware relational database set operators." Information Systems 59 (July 2016): 79–93. http://dx.doi.org/10.1016/j.is.2015.10.008.
Повний текст джерелаJacyna-Gołda, Ilona, Mariusz Izdebski, Piotr Klimek, and Rostislav Vašek. "Constructing a database structure in the problem of the assignment of air transport operators to commissioned tasks." MATEC Web of Conferences 294 (2019): 04004. http://dx.doi.org/10.1051/matecconf/201929404004.
Повний текст джерелаPetrosyan, Arthur S., and Gurgen S. Petrosyan. "Development of Management System for eduroam Database Updated Specification." Mathematical Problems of Computer Science 53 (July 10, 2020): 57–62. http://dx.doi.org/10.51408/1963-0081.
Повний текст джерелаPetrosyan, Arthur, and Gurgen Petrosyan. "Development of Management System for eduroam Database Updated Specification." Mathematical Problems of Computer Science 53 (July 10, 2020): 57–62. http://dx.doi.org/10.51408/1963-0075.
Повний текст джерелаFrieder, O. "Multiprocessor algorithms for relational-database operators on hypercube systems." Computer 23, no. 11 (November 1990): 13–28. http://dx.doi.org/10.1109/2.60877.
Повний текст джерелаJaziri, Wassim, Najla Sassi, and Dhouha Damak. "Using Temporal Versioning and Integrity Constraints for Updating Geographic Databases and Maintaining Their Consistency." Journal of Database Management 26, no. 1 (January 2015): 30–59. http://dx.doi.org/10.4018/jdm.2015010102.
Повний текст джерелаMaquen Nino, Gisella Luisa, Franklin Edinson Teran Santa Cruz, Consuelo Ivonne Del Castillo Castro, and Rafael Damian Villon Prieto. "Best Practices for Relational Database Optimization using Microsoft SQL." Universidad Ciencia y Tecnología 26, no. 114 (June 28, 2022): 29–38. http://dx.doi.org/10.47460/uct.v26i114.588.
Повний текст джерелаДисертації з теми "Database Operators"
Sjö, Kristoffer. "Semantics and Implementation of Knowledge Operators in Approximate Databases." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2438.
Повний текст джерелаIn order that epistemic formulas might be coupled with approximate databases, it is necessary to have a well-defined semantics for the knowledge operator and a method of reducing epistemic formulas to approximate formulas. In this thesis, two possible definitions of a semantics for the knowledge operator are proposed for use together with an approximate relational database:
* One based upon logical entailment (being the dominating notion of knowledge in literature); sound and complete rules for reduction to approximate formulas are explored and found not to be applicable to all formulas.
* One based upon algorithmic computability (in order to be practically feasible); the correspondence to the above operator on the one hand, and to the deductive capability of the agent on the other hand, is explored.
Also, an inductively defined semantics for a"know whether"-operator, is proposed and tested. Finally, an algorithm implementing the above is proposed, carried out using Java, and tested.
Müller, Ingo [Verfasser], and P. [Akademischer Betreuer] Sanders. "Engineering Aggregation Operators for Relational In-Memory Database Systems / Ingo Müller. Betreuer: P. Sanders." Karlsruhe : KIT-Bibliothek, 2016. http://d-nb.info/1106329953/34.
Повний текст джерелаAmenabar, Leire, and Leire Carreras. "Augmented Reality Framework for Supporting and Monitoring Operators during Maintenance Operations in Industrial Environments." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15717.
Повний текст джерелаMcCormick, II Donald W. "Towards A Sufficient Set of Mutation Operators for Structured Query Language (SQL)." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/32526.
Повний текст джерелаMaster of Science
BHIDE, ASHWINI M. "ANALYSIS OF ACCIDENTS AND INJURIES OF CONSTRUCTION EQUIPMENT OPERATORS." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1147378056.
Повний текст джерелаJäkel, Tobias. "Role-based Data Management." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-224416.
Повний текст джерелаGonzaga, André dos Santos. "The Similarity-aware Relational Division Database Operator." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-17112017-135006/.
Повний текст джерелаO operador de Divisão (÷) da Álgebra Relacional permite representar de forma simples consultas com o conceito de para todos, e por isso é requerido em diversas aplicações reais. Entretanto, evidencia-se neste trabalho de mestrado que a divisão não atende às necessidades de diversas aplicações atuais, principalmente quando estas analisam dados complexos, como imagens, áudio, textos longos, impressões digitais, entre outros. Analisando o problema verifica-se que a principal limitação é a existência de comparações de valores de atributos intrínsecas à Divisão Relacional, que, por definição, são efetuadas sempre por identidade (=), enquanto objetos complexos devem geralmente ser comparados por similaridade. Hoje, encontram-se na literatura propostas de operadores relacionais com suporte à similaridade de objetos complexos, entretanto, nenhuma trata a Divisão Relacional. Este trabalho de mestrado propõe investigar e estender o operador de Divisão da Álgebra Relacional para melhor adequá-lo às demandas de aplicações atuais, por meio de suporte a comparações de valores de atributos por similaridade. Mostra-se aqui que a Divisão por Similaridade é naturalmente adequada a responder consultas diversas com um conceito de elementos candidatos e exigências descrito na monografia, envolvendo dados complexos de aplicações reais de alto impacto, com potencial por exemplo, para apoiar a agricultura, análises de dados genéticos, buscas em bibliotecas digitais, e até mesmo para controlar a qualidade de produtos manufaturados e a identificação de novos clientes em indústrias. Para validar a proposta, propõe-se estudar as duas primeiras aplicações citadas.
Liknes, Stian. "Database Operations on Multi-Core Processors." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-22990.
Повний текст джерелаBehzadnia, Peyman. "Dynamic Energy-Aware Database Storage and Operations." Scholar Commons, 2018. http://scholarcommons.usf.edu/etd/7125.
Повний текст джерелаTomé, Diego Gomes. "A near-data select scan operator for database systems." reponame:Repositório Institucional da UFPR, 2017. http://hdl.handle.net/1884/53293.
Повний текст джерелаCoorientador : Marco Antonio Zanata Alves
Dissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 21/12/2017
Inclui referências : p. 61-64
Resumo: Um dos grandes gargalos em sistemas de bancos de dados focados em leitura consiste em mover dados em torno da hierarquia de memória para serem processados na CPU. O movimento de dados é penalizado pela diferença de desempenho entre o processador e a memória, que é um problema bem conhecido chamado memory wall. O surgimento de memórias inteligentes, como o novo Hybrid Memory Cube (HMC), permitem mitigar o problema do memory wall executando instruções em chips de lógica integrados a uma pilha de DRAMs. Essas memórias possuem potencial para computação de operações de banco de dados direto em memória além do armazenamento de bancos de dados. O objetivo desta dissertação é justamente a execução do operador algébrico de seleção direto em memória para reduzir o movimento de dados através da memória e da hierarquia de cache. O foco na operação de seleção leva em conta o fato que a leitura de colunas a serem filtradas movem grandes quantidades de dados antes de outras operações como junções (ou seja, otimização push-down). Inicialmente, foi avaliada a execução da operação de seleção usando o HMC como uma DRAM comum. Posteriormente, são apresentadas extensões à arquitetura e ao conjunto de instruções do HMC, chamado HMC-Scan, para executar a operação de seleção próximo aos dados no chip lógico do HMC. Em particular, a extensão HMC-Scan tem o objetivo de resolver internamente as dependências de instruções. Contudo, nós observamos que o HMC-Scan requer muita interação entre a CPU e a memória para avaliar a execução de filtros de consultas. Portanto, numa segunda contribuição, apresentamos a extensão arquitetural HIPE-Scan para diminuir esta interação através da técnica de predicação. A predicação suporta a avaliação de predicados direto em memória sem necessidade de decisões da CPU e transforma dependências de controle em dependências de dados (isto é, execução predicada). Nós implementamos a operação de seleção próximo aos dados nas estratégias de execução de consulta orientada a linha/coluna/vetor para a arquitetura x86 e para nas duas extensões HMC-Scan e HIPE-Scan. Nossas simulações mostram uma melhora de desempenho de até 3.7× para HMC-Scan e 5.6× para HIPE-Scan quando executada a consulta 06 do benchmark TPC-H de 1 GB na estratégia de execução orientada a coluna. Palavras-chave: SGBD em Memória, Cubo de Memória Híbrido, Processamento em Memória.
Abstract: A large burden of processing read-mostly databases consists of moving data around the memory hierarchy rather than processing data in the processor. The data movement is penalized by the performance gap between the processor and the memory, which is the well-known problem called memory wall. The emergence of smart memories, as the new Hybrid Memory Cube (HMC), allows mitigating the memory wall problem by executing instructions in logic chips integrated to a stack of DRAMs. These memories can enable not only in-memory databases but also have potential for in-memory computation of database operations. In this dissertation, we focus on the discussion of near-data query processing to reduce data movement through the memory and cache hierarchy. We focus on the select scan database operator, because the scanning of columns moves large amounts of data prior to other operations like joins (i.e., push-down optimization). Initially, we evaluate the execution of the select scan using the HMC as an ordinary DRAM. Then, we introduce extensions to the HMC Instruction Set Architecture (ISA) to execute our near-data select scan operator inside the HMC, called HMC-Scan. In particular, we extend the HMC ISA with HMC-Scan to internally solve instruction dependencies. To support branch-less evaluation of the select scan and transform control-flow dependencies into data-flow dependencies (i.e., predicated execution) we propose another HMC ISA extension called HIPE-Scan. The HIPE-Scan leads to less iteration between processor and HMC during the execution of query filters that depends on in-memory data. We implemented the near-data select scan in the row/column/vector-wise query engines for x86 and two HMC extensions, HMC-Scan and HIPE-Scan achieving performance improvements of up to 3.7× for HMC-Scan and 5.6× for HIPE-Scan when executing the Query-6 from 1 GB TPC-H database on column-wise. Keywords: In-Memory DBMS, Hybrid Memory Cube, Processing-in-Memory.
Книги з теми "Database Operators"
Satellite anomalies: Benefits of a centralized anomaly database and methods for securely sharing information among satellite operators. Santa Monica, CA: RAND, 2014.
Знайти повний текст джерелаM, Gaier Eric, and Langley Research Center, eds. Air cargo operations cost database. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Знайти повний текст джерелаM, Gaier Eric, and Langley Research Center, eds. Air cargo operations cost database. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Знайти повний текст джерелаDominique, Jeunot, ed. Oracle database operator for Windows NT. Redwood Shores, CA: Oracle, 1999.
Знайти повний текст джерелаFilippi, Stephen Charles. Implementing relational operations in an object-oriented database. Monterey, Calif: Naval Postgraduate School, 1992.
Знайти повний текст джерелаMavroedis, John. Update operations in indefinite temporal constraint databases. Manchester: UMIST, 1995.
Знайти повний текст джерелаA, Watkins William, and Woods Hole Oceanographic Institution, eds. SOUND database of marine animal vocalizations: Structure and operations. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1992.
Знайти повний текст джерелаAlston, Darrell W. The instrumentation of a parallel and scalable database computer--the Multi-Backend Database Computer, for benchmarking its complex operations. Monterey, Calif: Naval Postgraduate School, 1989.
Знайти повний текст джерелаGlossary of operations research (English-Hindi): Computerised database = Saṅkriyāvijñāna śabdāvalī (Angrejī-Hindī) : kampyuṭarīkr̥ta dāṭābesa. New Delhi: Commission for Scientific and Technical Terminology, Ministry of Human Resource Development, Department of Higher Education, 2013.
Знайти повний текст джерелаKerr, Pauline. US & Soviet naval & air operations in the North Pacific, 1981-1989: A database. Canberra: Peace Research Centre, Research School of Pacific and Asian Studies, The Australian National University, 1996.
Знайти повний текст джерелаЧастини книг з теми "Database Operators"
Beard, Bradley. "Notifying Database Operators." In Practical Maintenance Plans in SQL Server, 189–203. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1895-2_12.
Повний текст джерелаTrushkowsky, Beth. "Crowd Database Operators." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_80660-1.
Повний текст джерелаTrushkowsky, Beth. "Crowd Database Operators." In Encyclopedia of Database Systems, 684–89. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80660.
Повний текст джерелаZhou, Jingren. "Evaluation of Relational Operators." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_154-2.
Повний текст джерелаZhou, Jingren. "Evaluation of Relational Operators." In Encyclopedia of Database Systems, 1024–29. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_154.
Повний текст джерелаZhou, Jingren. "Evaluation of Relational Operators." In Encyclopedia of Database Systems, 1348–54. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_154.
Повний текст джерелаNuijten, Alex, and Patrick Barel. "Pagination and Set Operators." In Modern Oracle Database Programming, 107–27. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9166-5_5.
Повний текст джерелаYager, Ronald R. "Implementing Quotient Operators in Fuzzy Data Bases Using OWA Operators." In Fuzziness in Database Management Systems, 186–206. Heidelberg: Physica-Verlag HD, 1995. http://dx.doi.org/10.1007/978-3-7908-1897-0_9.
Повний текст джерелаCherniack, Mitch, and Stan Zdonik. "Stream-Oriented Query Languages and Operators." In Encyclopedia of Database Systems, 1–8. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_368-2.
Повний текст джерелаMaier, David, Jin Li, Peter Tucker, Kristin Tufte, and Vassilis Papadimos. "Semantics of Data Streams and Operators." In Database Theory - ICDT 2005, 37–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30570-5_3.
Повний текст джерелаТези доповідей конференцій з теми "Database Operators"
Lee, Seungjae, Changhwa Kim, and Sangkyung Kim. "New Database Operators for Sensor Networks." In 5th ACIS International Conference on Software Engineering Research, Management & Applications (SERA 2007). IEEE, 2007. http://dx.doi.org/10.1109/sera.2007.101.
Повний текст джерелаGold, Brian, Anastassia Ailamaki, Larry Huston, and Babak Falsafi. "Accelerating database operators using a network processor." In the 1st international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1114252.1114260.
Повний текст джерелаKara, Kaan, and Gustavo Alonso. "Fast and robust hashing for database operators." In 2016 26th International Conference on Field Programmable Logic and Applications (FPL). IEEE, 2016. http://dx.doi.org/10.1109/fpl.2016.7577353.
Повний текст джерелаCieslewicz, John, William Mee, and Kenneth A. Ross. "Cache-conscious buffering for database operators with state." In the Fifth International Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1565694.1565704.
Повний текст джерелаdos Santos, Sairo R., Francis B. Moreira, Tiago R. Kepe, and Marco A. Z. Alves. "Advancing Database System Operators with Near-Data Processing." In 2022 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE, 2022. http://dx.doi.org/10.1109/pdp55904.2022.00028.
Повний текст джерелаRodiger, Wolf, Tobias Muhlbauer, Philipp Unterbrunner, Angelika Reiser, Alfons Kemper, and Thomas Neumann. "Locality-sensitive operators for parallel main-memory database clusters." In 2014 IEEE 30th International Conference on Data Engineering (ICDE). IEEE, 2014. http://dx.doi.org/10.1109/icde.2014.6816684.
Повний текст джерелаDrewes, Tobias, Jan Moritz Joseph, Bala Gurumurthy, David Broneske, Gunter Saake, and Thilo Pionteck. "Efficient Inter-Kernel Communication for OpenCL Database Operators on FPGAs." In 2018 International Conference on Field-Programmable Technology (FPT). IEEE, 2018. http://dx.doi.org/10.1109/fpt.2018.00050.
Повний текст джерелаTaniguchi, Tetsuki, and Takeo Fujii. "Interference Management with Beamforming Utilizing Spectrum Database for Micro Operators." In 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall). IEEE, 2020. http://dx.doi.org/10.1109/vtc2020-fall49728.2020.9348725.
Повний текст джерелаJiang, Feng, and Guozhu Liu. "Rough Relational Operators and Rough Entropy in Rough Relational Database." In 2009 Second International Workshop on Knowledge Discovery and Data Mining (WKDD). IEEE, 2009. http://dx.doi.org/10.1109/wkdd.2009.115.
Повний текст джерелаGonzaga, André S., and Robson L. F. Cordeiro. "Fast and Scalable Relational Division on Database Systems." In Simpósio Brasileiro de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2016. http://dx.doi.org/10.5753/sbbd.2016.24323.
Повний текст джерелаЗвіти організацій з теми "Database Operators"
McKee and Poerner. PR-015-08200-R01 PRCI State-of-the-Art Pipeline Pump Station Technology Study. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2008. http://dx.doi.org/10.55274/r0010965.
Повний текст джерелаKolovitch, Haines, and Trench. L52317 Pipeline Facility Incident Data Review and Statistical Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2008. http://dx.doi.org/10.55274/r0010675.
Повний текст джерелаSkow, Jason, Dongliang Lu, and Smitha Koduru. PR-244-133731-R01 In-line Inspection Crack Tool Performance Evaluation. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 2015. http://dx.doi.org/10.55274/r0010580.
Повний текст джерелаChien, Stanley, Lauren Christopher, Yaobin Chen, Mei Qiu, and Wei Lin. Integration of Lane-Specific Traffic Data Generated from Real-Time CCTV Videos into INDOT's Traffic Management System. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317400.
Повний текст джерелаNeuert, Mark, and Smitha Koduru. PR-244-173856-R01 In-line Inspection Crack Tool Reliability and Performance Evaluation. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 2019. http://dx.doi.org/10.55274/r0011599.
Повний текст джерелаThost, Veronika, Jan Holste, and Özgür Özçep. On Implementing Temporal Query Answering in DL-Lite. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.218.
Повний текст джерелаChien, Stanley, Yaobin Chen, Lauren Christopher, Mei Qiu, and Zhengming Ding. Road Condition Detection and Classification from Existing CCTV Feed. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317364.
Повний текст джерелаMorandi, Paula, and Amy Lewis. 2021 IDB Climate Finance Database. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004645.
Повний текст джерелаKlise, Geoffrey Taylor, Peter Holmes Kobos, Roger Ray Hill, Colin Joseph Hamman, Vipin P. Gupta, Benjamin Bing-Yeh Yang, and Nadav Enbar. PV Reliability Operations and Maintenance (PVROM) Database Initiative: 2014 Project Report. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1504104.
Повний текст джерелаRobinett, Fred. PR-471-14207-Z03 Evaluation of Field Pump Performance Testing Procedure. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 2019. http://dx.doi.org/10.55274/r0011616.
Повний текст джерела