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Relevant bibliographies by topics / SQL

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Academic literature on the topic 'SQL'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 June 2025

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Journal articles on the topic "SQL"

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Zeng, Haiyan, Cheng Zhi Liu, Qishan Zhao, Xing Liu, Qian Liu, and Dan Wang. "The Research on Sequence Stratigraphy of Shahezi Formation in Xujiaweizi Depression." Advanced Materials Research 787 (September 2013): 651–54. http://dx.doi.org/10.4028/www.scientific.net/amr.787.651.

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By using the data of core, geological log and seism and the theory of sedimentology and sequence stratigraphy , the sequence of Shahezi formation in Xujiaweizi depression are divided into five third-order sequence, they are SQ1, SQ2, SQ3, SQ4 and SQ5 up towards. The range of SQ1 is limited, influenced by palaeogeomorphology. SQ5 are greatly influenced by the late sedimentary denudation, now only in the northwest of the study area can be seen, other part is missing in this layer. SQ1, SQ2, SQ3 are onlap filled. There are defective area in SQ4 and SQ5.

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Koymen, Kemal, and Qujun Cai. "SQL∗: A recursive SQL." Information Systems 18, no. 2 (1993): 121–28. http://dx.doi.org/10.1016/0306-4379(93)90009-p.

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Eisenberg, Andrew, and Jim Melton. "SQL." ACM SIGMOD Record 28, no. 1 (1999): 131–38. http://dx.doi.org/10.1145/309844.310075.

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Melton, Jim, and Andrew Eisenberg. "SQL multimedia and application packages (SQL/MM)." ACM SIGMOD Record 30, no. 4 (2001): 97–102. http://dx.doi.org/10.1145/604264.604280.

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Gusti Ayu Mas Ekayanti, Dewa Ayu Deby Cintiya, Putu Yoga Suartana, Rama Ngurah Putera Pinatih, Gede Arna Jude Saskara, and I Made Edy Listartha. "PERBANDINGAN TOOLS SQL SUS, SQL NINJA, DAN THE MOLE DALAM PENERAPAN SQL INJECTION." Jurnal Informatika Teknologi dan Sains 4, no. 4 (2022): 478–82. http://dx.doi.org/10.51401/jinteks.v4i4.2201.

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In this modern era, the rapid development of science and technology is certainly very beneficial for human life. However, this development can also bring threats, such as cyber attacks. One type of cyber attack that is often used is SQL injection, which targets database security. Three tools that can be used in testing SQL injection are SQL sus, SQL ninja, and The mole. Testing these three tools uses two operating systems, that is Kali Linux and Windows. The test results are measured based on several parameters, namely, the speed of the tool in responding to commands, the number of stages in its application, the features contained therein, and its efficiency. Based on the test results, it is known that only the sus SQL tool successfully injected a website, while the other two tools failed.

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Ndongala, Nathan Manzambi. "Light RAT-SQL: A RAT-SQL with More Abstraction and Less Embedding of Pre-existing Relations." TEXILA INTERNATIONAL JOURNAL OF ACADEMIC RESEARCH 10, no. 2 (2023): 1–11. http://dx.doi.org/10.21522/tijar.2014.10.02.art001.

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RAT-SQL is among the popular framework used in the Text-To-SQL challenges for jointly encoding the database relations and questions in a way to improve the semantic parser. In this work, we propose a light version of the RAT-SQL where we dramatically reduced the number of the preexisting relations from 55 to 7 (Light RAT-SQL-7) while preserving the same parsing accuracy. To ensure the effectiveness of our approach, we trained a Light RAT-SQL-2, (with 2 embeddings) to show that there is a statistically significant difference between RAT-SQL and Light RAT-SQL-2 while Light RAT-SQL-7 can compete with RAT-SQL. Keywords: Deep learning, Natural Language Processing, Neural Semantic Parsing, Relation Aware Transformer, RAT-SQL, Text-To-SQL, Transformer.

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Chen, Yao Fei, Wei Zheng, and Huan Tong Chen. "Automatic Marking of SQL Server Based on SQL-DMO." Applied Mechanics and Materials 303-306 (February 2013): 2369–72. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2369.

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SQL Server skill assessment is deficient. This article describes the SQL Server object model SQL-DMO. Propose the process of SQL Server skill assessment: test paper generation, Skill assessment and Automatic marking. Analysis two key techniques of skill assessment based on SQL-DMO. One is getting operating information based on SQL-DMO. The other is automatic marking for Skill and Operation. Besides, automatic marking rules for database object creating, modifying and deleting are focused on. The author uses SQL-DMO method to realize database object information acquisition, and implement automatic marking for SQL Server database skill assessment.

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Eisenberg, Andrew, and Jim Melton. "SQL standardization." ACM SIGMOD Record 29, no. 1 (2000): 63–67. http://dx.doi.org/10.1145/344788.344819.

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Englert, Susanne. "Nonstop SQL." ACM SIGMOD Record 23, no. 2 (1994): 491. http://dx.doi.org/10.1145/191843.191945.

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Roddick, John F. "SQL/SE." ACM SIGMOD Record 21, no. 3 (1992): 10–16. http://dx.doi.org/10.1145/140979.140985.

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Dissertations / Theses on the topic "SQL"

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Rani, Venkata. "Translating Temporal SQL to Nested SQL." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4966.

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Sequenced and nonsequenced semantics are the two previously researched semantics for the evaluation of an operation in a temporal database such as a query or data modification. Sequenced semantics evaluates an operation in each time instant using only the data alive at that time. Nonsequenced semantics, in contrast, means that an operation explicitly references and manipulates the timestamps in the data. In this thesis we propose a new framework that shows both semantics are variants of a general temporal semantics. We present the general semantics and show how additional semantics, such as preceding semantics can be realized. The semantics are specified using annotations. The primary contribution of this theses is the translation from temporal SQL to nested SQL. We focus on SQL's SELECT statement, which is used to query data. Temporal SQL is SQL annotated with temporal semantics. Nested SQL is SQL for non-1NF data, with additional operations, such as COGROUP and FLATTEN to create and un-nest, respectively, bags of tuples (non-1NF data). This thesis develops a denotational semantics for translating from temporal to nested SQL. We implemented the denotational semantics for an SQLite ANTLR grammar, and the thesis also reports on the implementation.

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Čebanauskas, Saulius. "SQL mokymosi sistema." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100826_112703-93241.

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Šiais laikais, kai praktiškai visų sričių „popieriniai“ duomenys jau baigia išnykti, didelę dalį IT visuomenėje sudaro vienokio ar kitokio tipo duomenų bazės. Paprastam vartotojui, kuris naudojasi tik vartojamojo tipo programomis, SQL užklausų mokėjimas nėra reikalingas, tačiau bet kuris programuotojas, kuris dirba su duomenimis, savo darbo ko gero nebeįsivaizduoja be duomenų bazių ir SQL užklausų. SQL užklausa (SQL Query) – tai užklausa, atliekama SQL kalbos komandų pagalba. SQL (Structured Query Language) kalba – struktūrizuota užklausų kalba, skirta duomenų, esančių duomenų bazėje apdorojimui. SQL kalba dirba tik su reliacinėmis DB. Vartotojas SQL pagalba kreipiasi į DBVS, kuri apdoroja užklausą, randa reikalingus duomenis ir pateikia juos vartotojui. SQL nėra nei DBVS, nei atskiras programinis produktas, tai yra neatsiejama DBVS dalis, instrumentas, kurio pagalba realizuojamas vartotojo ryšys su DBVS. SQL kalbos lankstumas ir nepriklausomumas nuo kompiuterinių technologijų specifikos, o taip pat jos palaikymas pagrindiniais lyderiais reliacinių duomenų bazių technologijų srityje padarė SQL kalbą pagrindine standartine duomenų bazių programavimo kalba [1]. SQL užklausos yra naudojamos visose dabartinėse duomenų bazėse, tokiose kaip MsSQL, MySQL, Firebird ir kitose. SQL sakiniai gali būti įterpiami į programas, sudaromas bazine programavimo kalba. Taigi SQL užklausos yra naudojamos visur, kur yra naudojamos ir duomenų bazės. Tą pačią SQL užklausą... [toliau žr. visą tekstą]<br>Nowadays, when “paper” data practically from all the scopes is on the edge of extinction, big part of IT society is made of one or another type of databases. SQL queries are used to work with database information. SQL (Structured Query Language) is designed for database information processing. For fast systems, related with databases operation, it is necessary to correctly write and optimize SQL queries. To learn write SQL queries correctly and optimize them, only the theoretical knowledge is not enough, it is necessary to do a lot of practical tasks. When learning to write SQL queries, basic problem is poor choice of practical tasks, and non-existence of good testing system, which allows writing SQL queries easily. On the job the existent SQL learning systems and learning materials analysis were performed, all found systems has its own problems, full freedom to write SQL queries for user is not granted. During designing, methods allowing for learner easily write various types of queries, view executed queries results and get the result if a written query is correct, were designed. Designed methods were used in remote SQL queries learning system design and implementation. Aim: The algorithms which are developed and implemented allows to test sql queries based on simple syntax and allows to execute queries of the different types. The object of research: Execution of various SQL queries.

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Buso, Fabio. "SQL on Hops." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215692.

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In today’s world data is extremely valuable. Companies and researchers store every sort of data, from users activities to medical records. However, data is useless if one cannot extract meaning and insight from it. In 2004 Dean and Ghemawat introduced the MapReduce framework. This sparked the development of open source frameworks for big data storage (HDFS) and processing (Hadoop). Hops and Apache Hive build on top of this heritage. The former proposes a new distributed file system which achieves higher scalability and throughput by storing metadata in a database called MySQL-Cluster. The latter is an open source data warehousing solution built on top of the Hadoop ecosystems, which allows users to query big data stored on HDFS using a SQL-like query language.Apache Hive is a widely used and mature project, however it lacks of consistency between the data stored on the file system and the metadata describing it, stored on a relational database. This means that if users delete Hive’s data from the file system, Hive does not delete the related metadata. This causes two issues: (1) users do not get an error if the data is missing from the filesystem (2) if users forget to delete the metadata, it will become orphaned in the database. In this thesis we exploit the fact that both HopsFS’ metadata and Hive’s metadata is stored in a relational database, to provide a mechanisms to automatically delete Hive’s metadata if the data is delete from the file system.The second objective of this thesis is to integrate Apache Hive into the Hops ecosystem and in particular in the HopsWorks platform. HopsWorks is a multitenant, UI based service which allows users to store and process big data projects. In this thesis we develop a custom authenticator for Hive to allow HopsWorks users to authenticate with Hive and to integrate with its security model.

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Bahureková, Beáta. "Technika SQL injection - její metody a způsoby ochrany." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2020. http://www.nusl.cz/ntk/nusl-433304.

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SQL injection is a technique directed against web applications using an SQL database, which can pose a huge security risk. It involves inserting code into an SQL database, and this attack exploits vulnerabilities in the database or application layer. The main goal of my thesis is to get acquainted with the essence of SQL injection, to understand the various methods of this attack technique and to show ways to defend against it. The work can be divided into these main parts, which I will discuss as follows.In the introductory part of the work I mention the theoretical basis concerning SQL injection issues. The next chapter is focused on individual methods of this technique. The analytical part is devoted to mapping the current state of test subjects, scanning tools, which form the basis for optimal research and testing of individual SQL methods, which are discussed in this part from a practical point of view along with the analysis of commands. In the last part I will implement SQL methods on selected subjects and based on the outputs I will create a universal design solution how to defend against such attacks.

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(UPC), Universidad Peruana de Ciencias Aplicadas. "SQL Server - SI92 201801." Universidad Peruana de Ciencias Aplicadas (UPC), 2018. http://hdl.handle.net/10757/623250.

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Curso electivo para las carreras de Ingeniería de Software (ISW), Ingeniería de Sistemas de Información (ISI) y Ciencias de la Computación (CC), de carácter teórico-práctico, dirigido a los estudiantes de séptimo nivel para (CC), noveno nivel para (ISI) y decimo nivel para (ISW), que busca desarrollar la competencia DISEÑA SISTEMAS, COMPONENTES O PROCESOS PARA ENCONTRAR SOLUCIONES EN LA ATENCIÓN DE NECESIDADES TENIENDO EN CUENTA RESTRICCIONES ECONÓMICAS, SOCIALES, POLÍTICAS, ÉTICAS, DE SALUD Y SEGURIDAD Y OTRAS PROPIAS DEL ENTORNO EMPRESARIAL. Acorde al ABET Student Outcome (C) para (ISW). En este curso el estudiante podrá diseñar, implementar y administrar soluciones de bases de datos orientadas a empresas, utilizando como motor el Microsoft SQL Server 2012. En la actualidad la mayoría de proyectos informáticos necesita de un sólido conocimiento de base de datos.

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Waß, Christopher. "Demotisch, hieratisch und SQL." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-201797.

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Im Fokus des vorgestellten Projektes steht die Untersuchung der Verwendung von zwei ägyptischen Kursivschriften in einem homogenen Textkorpus. Hierbei handelt es sich zum einen um Hieratisch, einer Kursivschrift, die etwa zeitgleich mit den Hieroglyphen im 3. Jtd. v. Chr. entstand und für Texte auf Papyrus verwendet wurde. Mit beiden Schriftarten wurde in der Regel dieselbe Phase der ägyptischen Sprache geschrieben. Zum anderen um Demotisch, einer um 650 v. Chr. entwickelten Kursivschrift, die ebenfalls für Texte auf Papyrus verwendet wurde, und eine historisch jüngere Sprachstufe beschreibt. Beide Schriftsysteme erscheinen nebeneinander in den vier magischen Papyri der sog. „Theban Magical Library“ aus dem 3. Jhd. n. Chr., die sich heute in London, Leiden und Paris befinden. Das zu untersuchende Textkorpus umfasst etwa 157 Einzeltexte, die sich auf mehr als 1700 Zeilen Text verteilen. Ein Großteil der Texte ist in demotischer Schrift und Grammatik geschrieben. Daneben finden sich einige Passagen in hieratischer, griechischer und in einer Zauberschrift. Auch sprachliche sind die Texte keineswegs homogen. Kürzere Passagen weisen häufig eine ältere Sprachstufe als das Demotische auf. Auch die Schriftart kann innerhalb eines Satzes, in einigen Fällen sogar innerhalb eines Wortes, wechseln. Die Gründe für die Verwendung von demotischer und hieratischer Schrift sind bisher nicht untersucht worden. Da die einzelnen Sprüche auf unterschiedliche Vorlagen aus verschiedenen Kulturkreisen zurückgehen, liegt der Schwerpunkt des Vorhabens auf der Untersuchung der Beziehung von Schriftart, Sprache oder Sprachstufe und Inhalt. Bisher wird in der Forschung davon ausgegangen, dass hieratische Schrift zur Schreibung von Götterbezeichnungen oder bestimmter Termini, bevorzugt also bei Passagen mit religiösem Inhalt Verwendung fand. Jüngere Überlegungen konnten jedoch zeigen, dass hieratische Schrift in einigen Fällen mit sprachlich altertümlichen Merkmalen einhergeht, wobei es sich wohl um die Reste eines Vorläufers handelt, der nicht vollständig in demotische Schrift und Sprache übertragenen wurde. Um das Quellenmaterial adäquat zu untersuchen, ist eine genaue Analyse von Schrift, Sprache und Inhalt der Einzeltexte nötig. In einem ersten Schritt wird jeder Papyrus unabhängig von den anderen untersucht. Hierfür wird der Text in eine Excel-Tabelle aufgenommen. Jeder Eintrag wird mit verschiedenen Merkmalen versehen, die für die spätere Auswertung von Bedeutung sind. Die Texte werden in Hinblick auf die verwendete Schriftart, Sprachstufe, der zeitlichen Bezeugung eines Wortes oder grammatikalischen Konstruktion, Wortart, Herkunft (ägyptisch, griechisch, jüdisch etc.), Kontext (Vorkommen in Titeln, direkter Rede u. ä.) und, falls vorhanden, Anmerkungen des Schreibers analysiert. In einem ersten Schritt werden die Texte in ägyptologischer Umschrift in eine Exceltabelle eingetragen. Hierbei erhält jedes Wort einen Eintrag und wird mit den für die Analyse benötigten Merkmale versehen. Im Anschluss wird die Tabelle in eine mySQL Datenbank eingelesen. Diese wurde in Zusammenarbeit mit Dr. C. Riepl von der IT-Group Geisteswissenschaften der LMU München erstellt. Anhand dieser Datenbank erfolgt die Analyse der Texte.

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С, Тичко О. "МЕТОДИ РЕСТРУКТУРИЗАЦІЇ ЗАПИТІВ SQL". Thesis, Київ, Національний авіаційний університет, 2015. http://er.nau.edu.ua/handle/NAU/19747.

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Оптимізація запитів – процес зміни запиту з метою зменшення використання обчислювальних ресурсів при виконанні запиту. Метою оптимізації запитів є пошук альтернативних способів отримання результуючого набору від серверу баз даних. Перетворення запиту в еквівалентну форму дає більш високу ефективність при виконанні

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Horák, Jan. "SQL backend pro Subversion." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237115.

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The thesis analyzes version control system Subversion and its available backends for storing data in a repository. It compares these backends and describes basic features of a new SQL database backend. Design and implementation of the new backend, based on MySQL database, is described and the new backend is then compared with existing backends BDB and FSFS.

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Laibaças, Hugo Alexandre Lopes. "Laboratório online de SQL." Master's thesis, Universidade de Évora, 2013. http://hdl.handle.net/10174/16391.

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As bases de dados consubstanciam umas das áreas do saber no domínio da informática, designadamente, as bases de dados relacionais, que se apresentam como as mais populares e difundidas. Neste contexto, surge o SQL, uma linguagem de programação desenhada para permitir fazer a gestão dos dados em SGBD relacionais. Não tendo sido identificada na Internet, a existência de qualquer ferramenta que incorpore o conceito de laboratório online de SQL, decidiuse criar uma ferramenta ampla e que auxilie na aprendizagem desta linguagem e seus conceitos, proporcionando um ambiente agregador de vários vetores essenciais para uma aprendizagem consistente. A componente teórica será muito privilegiada. No entanto, é a componente prática que desempenhará o papel principal, revestindo-se de um ambiente de ensaio onde cada membro poderá explorar o SQL e aprimorar as suas habilidades na utilização desta linguagem, através das experiências que poderá fazer com as bases de dados colocadas ao seu dispor; ABSTRACT: The databases embody one of the areas of knowledge in the field of computer science, namely, the relational databases, which are considered the most popular and widespread. In this context there is SQL, a programming language designed to allow data management in Relational Database Management Systems (RDBMS). Not having been identified on the Internet, the existence of any tool that incorporates the concept of online laboratory of SQL, it was decided to create a such a tool, to assist in learning this language and its concepts, providing a multi-vector aggregator platform, essential for consistent learning. The theoretical component will be very privileged. However, it is the practical component that plays the main role, by taking up a test environment where each member can explore SQL and improve their skills, through the experiences that can be done by using the databases placed at their disposal.

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Manzi, Eric R. "SQL-ACT : content-based and history-aware input prediction for non-trivial SQL queries." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/119534.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 79-81).<br>This thesis presents SqlAct, a SQL auto-completion system that uses content-based and history-aware input prediction to assist in the process of composing non-trivial queries. By offering the most relevant suggestions to complete the partially typed query first at the word-level and then at the statement-level, SqlAct hopes to help both novice and expert SQL developers to increase their productivity. Two approaches are explored: word-level suggestions are optimized based on the database's schema and content statistics, and statement-level suggestions that rely on Long Short-term Memory (LSTM) Recurrent Neural Networks language models trained on historical queries. The word-level model is integrated in a responsive command-line interface database client which is evaluated quantitatively and qualitatively. Results shows SqlAct provides a highly-responsive interface that makes high quality suggestions to complete the currently typed query. Possible directions for integration with the word-level model in the command-line tool are explored as well as the planned evaluation techniques.<br>by Eric R. Manzi.<br>M. Eng.

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Books on the topic "SQL"

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Adams, Ralf. SQL. Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432789.

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Marsch, Jürgen, and Jörg Fritze. SQL. Vieweg+Teubner Verlag, 1995. http://dx.doi.org/10.1007/978-3-322-83954-1.

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Marsch, Jürgen, and Jörg Fritze. SQL. Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-87800-7.

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SQL. 3rd ed. Peachpit Press, 2008.

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Oppel, Andrew J. SQL. McGraw-Hill, 2008.

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Harkins, Susan Sales, and Martin W. P. Reid. SQL: Access to SQL Server. Apress, 2002. http://dx.doi.org/10.1007/978-1-4302-1573-8.

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Brimhall, Jason, Jonathan Gennick, and Wayne Sheffield. SQL Server T-SQL Recipes. Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0061-2.

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Brimhall, Jason, David Dye, Jonathan Gennick, Andy Roberts, and Wayne Sheffield. SQL Server 2012 T-SQL Recipes. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4201-7.

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de Haan, Lex. Mastering Oracle SQL and SQL*Plus. Apress, 2005. http://dx.doi.org/10.1007/978-1-4302-0000-0.

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Sack, Joseph. SQL Server 2008 Transact-SQL recipes. Apress, 2008.

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Book chapters on the topic "SQL"

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Billington, Adrian. "PL/SQL from SQL." In Expert PL/SQL Practices. Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3486-9_9.

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Bamford, Carl, and Paul Curran. "SQL." In Data Structures, Files and Databases. Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-12615-6_13.

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Kofler, Michael. "SQL." In MySQL. Apress, 2001. http://dx.doi.org/10.1007/978-1-4302-0853-2_6.

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Janson, Robert W. "SQL." In Beginning Java with WebSphere. Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6302-9_14.

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Thew, David. "SQL." In Essential Series. Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0767-5_8.

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Simpkins, Stacy. "SQL." In Troubleshooting SharePoint. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3138-8_5.

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Smith, William. "SQL." In Systems Building with Oracle. Macmillan Education UK, 2004. http://dx.doi.org/10.1007/978-0-230-00094-0_6.

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Kilger, Bernhard. "SQL." In Xpert.press. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56671-4_6.

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Shekhar, Shashi, and Hui Xiong. "SQL." In Encyclopedia of GIS. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1340.

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Schubert, Matthias. "SQL." In Datenbanken. Vieweg+Teubner Verlag, 2004. http://dx.doi.org/10.1007/978-3-322-92113-0_10.

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Conference papers on the topic "SQL"

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Silva, Yasin N., Isadora Almeida, and Michell Queiroz. "SQL." In the 47th ACM Technical Symposium. ACM Press, 2016. http://dx.doi.org/10.1145/2839509.2844560.

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Dyreson, Curtis, and Venkata A. Rani. "Translating Temporal SQL to Nested SQL." In 2016 23rd International Symposium on Temporal Representation and Reasoning (TIME). IEEE, 2016. http://dx.doi.org/10.1109/time.2016.24.

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Ping, Chen, Wang Jinshuang, Yang Lanjuan, and Pan Lin. "SQL Injection Teaching Based on SQLi-labs." In 2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2020. http://dx.doi.org/10.1109/iciscae51034.2020.9236904.

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Ambasana, Jatin, Sameer Sahasrabudhe, and Sridhar Iyer. "SQL-Wordle: Gamification of SQL Programming Exercises." In CompEd 2023: ACM Global Computing Education Conference 2023. ACM, 2023. http://dx.doi.org/10.1145/3617650.3624949.

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Mozhaiskii, G., V. Korkhov, and I. Gankevich. "SQL QUERY EXECUTION OPTIMIZATION ON SPARK SQL." In 9th International Conference "Distributed Computing and Grid Technologies in Science and Education". Crossref, 2021. http://dx.doi.org/10.54546/mlit.2021.37.73.001.

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Abstract:

Spark and Hadoop ecosystem includes a wide variety of different components and can be integratedwith any tool required for Big Data nowadays. From release-to-release developers of theseframeworks optimize the inner work of components and make their usage more flexible and elaborate.Nevertheless, since inventing MapReduce as a programming model and the first Hadoop releases dataskew has been the main problem of distributed data processing. Data skew leads to performancedegradation, i.e., slowdown of application execution due to idling while waiting for the resources tobecome available. The newest Spark framework versions allow handling this situation easily from thebox. However, there is no opportunity to upgrade versions of tools and appropriate logic in the case ofcorporate environments with multiple large-scale projects development of which was started yearsago. In this article we consider approaches to execution optimization of SQL query in case of dataskew on concrete example with HDFS and Spark SQL 2.3.2 version usage.

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Englert, Susanne. "Nonstop SQL." In the 1994 ACM SIGMOD international conference. ACM Press, 1994. http://dx.doi.org/10.1145/191839.191945.

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de Amo, Sandra, and Marcos Roberto Ribeiro. "CPref-SQL." In the 2009 ACM symposium. ACM Press, 2009. http://dx.doi.org/10.1145/1529282.1529633.

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Sheykhkanloo, Naghmeh Moradpoor. "SQL-IDS." In SIN '15: The 8th International Conference on Security of Information and Networks. ACM, 2015. http://dx.doi.org/10.1145/2799979.2800011.

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Pryor, Edward E., and Jacquelyn S. Fetrow. "PDB-SQL." In the 45th annual southeast regional conference. ACM Press, 2007. http://dx.doi.org/10.1145/1233341.1233388.

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Grust, Torsten, Manuel Mayr, Jan Rittinger, Sherif Sakr, and Jens Teubner. "A SQL." In the 2007 ACM SIGMOD international conference. ACM Press, 2007. http://dx.doi.org/10.1145/1247480.1247642.

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Reports on the topic "SQL"

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Gallagher, Leonard, and Joan Sullivan. Database language SQL:. National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4902.

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Engle, Charles, Robert Firth, Mark H. Graham, and William G. Wood. Interfacing Ada and SQL. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada199634.

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Morris, Katherine C. Translating Express to SQL:. National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.4341.

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Shafranovich, Y. The application/sql Media Type. RFC Editor, 2013. http://dx.doi.org/10.17487/rfc6922.

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Nickerson, Deborah A. The NIST SQL database loader:. National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.4337.

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Daugherty, P. F., and P. T. Singley. SQTTEXT: A tool for editing Structured Query Language (SQL) text within ORACLE SQL*Forms applications. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6445416.

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Augustenborg, E. C. Microsoft SQL Server 6.0{reg_sign} Workbook. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/392659.

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Schoedel, Rob. PROxy Based Estimation (PROBE) for SQL. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada452977.

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Furniss, Peter, and Alastair Green. SQL/PGQ data model and graph schema. Linked Data Benchmark Council, 2018. http://dx.doi.org/10.54285/ldbc.qzsk3559.

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Xin, Reynold, Josh Rosen, Matei Zaharia, Michael J. Franklin, Scott Shenker, and Ion Stoica. Shark: SQL and Rich Analytics at Scale. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada570737.

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