Journal articles: 'Optimization of SQL queries'

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Ganski, Richard A., and Harry K. T. Wong. "Optimization of nested SQL queries revisited." ACM SIGMOD Record 16, no. 3 (December 1987): 23–33. http://dx.doi.org/10.1145/38714.38723.

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Ordonez, Carlos. "Optimization of Linear Recursive Queries in SQL." IEEE Transactions on Knowledge and Data Engineering 22, no. 2 (February 2010): 264–77. http://dx.doi.org/10.1109/tkde.2009.83.

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Ceri, S., and G. Gottlob. "Translating SQL Into Relational Algebra: Optimization, Semantics, and Equivalence of SQL Queries." IEEE Transactions on Software Engineering SE-11, no. 4 (April 1985): 324–45. http://dx.doi.org/10.1109/tse.1985.232223.

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Ji, Xuechun, Maoxian Zhao, Mingyu Zhai, and Qingxi Wu. "Query Execution Optimization in Spark SQL." Scientific Programming 2020 (February 7, 2020): 1–12. http://dx.doi.org/10.1155/2020/6364752.

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Spark SQL is a big data processing tool for structured data query and analysis. However, due to the execution of Spark SQL, there are multiple times to write intermediate data to the disk, which reduces the execution efficiency of Spark SQL. Targeting on the existing issues, we design and implement an intermediate data cache layer between the underlying file system and the upper Spark core to reduce the cost of random disk I/O. By using the query pre-analysis module, we can dynamically adjust the capacity of cache layer for different queries. And the allocation module can allocate proper memory for each node in cluster. According to the sharing of the intermediate data in the Spark SQL workflow, this paper proposes a cost-based correlation merging algorithm, which can effectively reduce the cost of reading and writing redundant data. This paper develops the SSO (Spark SQL Optimizer) module and integrates it into the original Spark system to achieve the above functions. This paper compares the query performance with the existing Spark SQL by experiment data generated by TPC-H tool. The experimental results show that the SSO module can effectively improve the query efficiency, reduce the disk I/O cost and make full use of the cluster memory resources.

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Seo, Kwangwon, Jinhyun Ahn, and Dong-Hyuk Im. "Optimization of Shortest-Path Search on RDBMS-Based Graphs." ISPRS International Journal of Geo-Information 8, no. 12 (December 1, 2019): 550. http://dx.doi.org/10.3390/ijgi8120550.

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Calculation of the shortest path between two nodes in a graph is a popular operation used in graph queries in applications such as map information systems, social networking services, and biotechnology. Recent shortest-path search techniques based on graphs stored in relational databases are able to calculate the shortest path efficiently, even in large data using frontier-expand-merge operations. However, previous approaches used a sequential bidirectional search method that causes a bottleneck, thus degrading performance. The repeated use of an aggregate SQL function also degrades performance. This paper proposes a parallel bi-directional search method using multithreading. In addition, an efficient optimization method is proposed that uses B-tree indexing instead of an aggregate SQL function. Various experiments using synthetic and real data reveal that the proposed optimization technique performs more efficiently than conventional methods. As the size of data in practical applications continues to grow, these optimizations will enable the shortest path in a graph to be found quickly and accurately.

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Khashan, Eman, Ali Eldesouky, and Sally Elghamrawy. "An adaptive spark-based framework for querying large-scale NoSQL and relational databases." PLOS ONE 16, no. 8 (August 19, 2021): e0255562. http://dx.doi.org/10.1371/journal.pone.0255562.

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The growing popularity of big data analysis and cloud computing has created new big data management standards. Sometimes, programmers may interact with a number of heterogeneous data stores depending on the information they are responsible for: SQL and NoSQL data stores. Interacting with heterogeneous data models via numerous APIs and query languages imposes challenging tasks on multi-data processing developers. Indeed, complex queries concerning homogenous data structures cannot currently be performed in a declarative manner when found in single data storage applications and therefore require additional development efforts. Many models were presented in order to address complex queries Via multistore applications. Some of these models implemented a complex unified and fast model, while others’ efficiency is not good enough to solve this type of complex database queries. This paper provides an automated, fast and easy unified architecture to solve simple and complex SQL and NoSQL queries over heterogeneous data stores (CQNS). This proposed framework can be used in cloud environments or for any big data application to automatically help developers to manage basic and complicated database queries. CQNS consists of three layers: matching selector layer, processing layer, and query execution layer. The matching selector layer is the heart of this architecture in which five of the user queries are examined if they are matched with another five queries stored in a single engine stored in the architecture library. This is achieved through a proposed algorithm that directs the query to the right SQL or NoSQL database engine. Furthermore, CQNS deal with many NoSQL Databases like MongoDB, Cassandra, Riak, CouchDB, and NOE4J databases. This paper presents a spark framework that can handle both SQL and NoSQL Databases. Four scenarios’ benchmarks datasets are used to evaluate the proposed CQNS for querying different NoSQL Databases in terms of optimization process performance and query execution time. The results show that, the CQNS achieves best latency and throughput in less time among the compared systems.

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K Sirohi, Arjun. "Optimization of Dynamically Generated SQL Queries for Tiny-Huge, Huge-Tiny Problem." International Journal of Database Management Systems 5, no. 1 (February 28, 2013): 53–68. http://dx.doi.org/10.5121/ijdms.2013.5105.

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Zervoudakis, Petros, Haridimos Kondylakis, Nicolas Spyratos, and Dimitris Plexousakis. "Query Rewriting for Incremental Continuous Query Evaluation in HIFUN." Algorithms 14, no. 5 (May 8, 2021): 149. http://dx.doi.org/10.3390/a14050149.

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HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, where queries are evaluated. In this paper, we present a methodology based on the HIFUN language, and the corresponding algorithms for the incremental evaluation of continuous queries. In essence, our approach is able to process the most recent data batch by exploiting already computed information, without requiring the evaluation of the query over the complete dataset. We present the generic algorithm which we translated to both SQL and MapReduce using SPARK; it implements various query rewriting methods. We demonstrate the effectiveness of our approach in temrs of query answering efficiency. Finally, we show that by exploiting the formal query rewriting methods of HIFUN, we can further reduce the computational cost, adding another layer of query optimization to our implementation.

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Kumar, Deepak, Deepti Mehrotra, and Rohit Bansal. "Query Optimization in Crowd-Sourcing Using Multi-Objective Ant Lion Optimizer." International Journal of Information Technology and Web Engineering 14, no. 4 (October 2019): 50–63. http://dx.doi.org/10.4018/ijitwe.2019100103.

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Nowadays, query optimization is a biggest concern for crowd-sourcing systems, which are developed for relieving the user burden of dealing with the crowd. Initially, a user needs to submit a structured query language (SQL) based query and the system takes the responsibility of query compiling, generating an execution plan, and evaluating the crowd-sourcing market place. The input queries have several alternative execution plans and the difference in crowd-sourcing cost between the worst and best plans. In relational database systems, query optimization is essential for crowd-sourcing systems, which provides declarative query interfaces. Here, a multi-objective query optimization approach using an ant-lion optimizer was employed for declarative crowd-sourcing systems. It generates a query plan for developing a better balance between the latency and cost. The experimental outcome of the proposed methodology was validated on UCI automobile and Amazon Mechanical Turk (AMT) datasets. The proposed methodology saves 30%-40% of cost in crowd-sourcing query optimization compared to the existing methods.

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Kotenko, Igor, Andrey Krasov, Igor Ushakov, and Konstantin Izrailov. "An Approach for Stego-Insider Detection Based on a Hybrid NoSQL Database." Journal of Sensor and Actuator Networks 10, no. 2 (March 30, 2021): 25. http://dx.doi.org/10.3390/jsan10020025.

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One of the reasons for the implementation of information security threats in organizations is the insider activity of its employees. There is a big challenge to detect stego-insiders-employees who create stego-channels to secretly receive malicious information and transfer confidential information across the organization’s perimeter. Especially presently, with great popularity of wireless sensor networks (WSNs) and Internet of Things (IoT) devices, there is a big variety of information that could be gathered and processed by stego-insiders. Consequently, the problem arises of identifying such intruders and their transmission channels. The paper proposes an approach to solving this problem. The paper provides a review of the related works in terms of insider models and methods of their identification, including techniques for handling insider attacks in WSN, as well methods of embedding and detection of stego-embeddings. This allows singling out the basic features of stego-insiders, which could be determined by their behavior in the network. In the interests of storing these attributes of user behavior, as well as storing such attributes from large-scale WSN, a hybrid NoSQL database is created based on graph and document-oriented approaches. The algorithms for determining each of the features using the NoSQL database are specified. The general scheme of stego-insider detection is also provided. To confirm the efficiency of the approach, an experiment was carried out on a real network. During the experiment, a database of user behavior was collected. Then, user behavior features were retrieved from the database using special SQL queries. The analysis of the results of SQL queries is carried out, and their applicability for determining the attribute is justified. Weak points of the approach and ways to improve them are indicated.

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Spiliopoulou, Maria, and Michalis Hatzopoulos. "Translation of SQL queries into a graph structure: Query transformations and pre-optimization issues in a pipeline multiprocessor environment." Information Systems 17, no. 2 (March 1992): 161–70. http://dx.doi.org/10.1016/0306-4379(92)90010-k.

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CHEN, LIANGYOU, and HASAN M. JAMIL. "ON USING REMOTE USER DEFINED FUNCTIONS AS WRAPPERS FOR BIOLOGICAL DATABASE INTEROPERABILITY." International Journal of Cooperative Information Systems 12, no. 02 (June 2003): 161–95. http://dx.doi.org/10.1142/s021884300300070x.

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Similar to most scientific studies, biological analyses demand a great deal of computations and simulations involving sophisticated tools that are often found geographically distributed over the Internet. A worldwide effort in genomics research has resulted in a powerful collection of publicly available sequence analysis tools. These tools often require specialized local services and domain knowledge to function correctly, rendering them unlikely candidates for integration into remote database applications. Thus, integration of heterogeneous "functions" still remains an open problem. Providing a reasonable framework for seamless integration of these tools with database query engines will enable application developers to exploit and harness the power of these effective analysis tools. In this paper, we present an integration framework for such tools by enabling access to them in a user transparent way as part of database queries. In our system, such online tools are abstracted as remote user defined functions (RUDF). An extended SQL DDL language, called the Internet Function Definition Language (IFDL), is presented for the specification and definition of RUDFs. The interface between database system and the Internet is implemented using a layer based on a language called the Hyper Text Query Language (HTQL). The separation of IFDL, DDL, HTQL and SQL DML offers several optimization opportunities and makes it possible to develop an architecture for interoperability of heterogeneous databases with RUDFs in more simple and efficient ways.

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Imam, Abdullahi Abubakar, Shuib Basri, Rohiza Ahmad, Amirudin A. Wahab, María T. González-Aparicio, Luiz Fernando Capretz, Ammar K. Alazzawi, and Abdullateef O. Balogun. "DSP: Schema Design for Non-Relational Applications." Symmetry 12, no. 11 (October 30, 2020): 1799. http://dx.doi.org/10.3390/sym12111799.

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The way a database schema is designed has a high impact on its performance in relational databases, which are symmetric in nature. While the problem of schema optimization is even more significant for NoSQL (“Not only SQL”) databases, existing modeling tools for relational databases are inadequate for this asymmetric setting. As a result, NoSQL modelers rely on rules of thumb to model schemas that require a high level of competence. Several studies have been conducted to address this problem; however, they are either proprietary, symmetrical, relationally dependent or post-design assessment tools. In this study, a Dynamic Schema Proposition (DSP) model for NoSQL databases is proposed to handle the asymmetric nature of today’s data. This model aims to facilitate database design and improve its performance in relation to data availability. To achieve this, data modeling styles were aggregated and classified. Existing cardinality notations were empirically extended using synthetically generated queries. A binary integer formulation was used to guide the mapping of asymmetric entities from the application’s conceptual data model to a database schema. An experiment was conducted to evaluate the impact of the DSP model on NoSQL schema production and its performance. A profound improvement was observed in read/write query performance and schema production complexities. In this regard, DSP has significant potential to produce schemas that are capable of handling big data efficiently.

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Moore, Joseph A., Wuyang Yang, Kim Evans, Avani Satish Dholakia, Albert Koong, Daniel Tandel Chang, Karyn A. Goodman, Joseph M. Herman, and Todd R. McNutt. "Clinical deployment of automatic treatment planning for pancreas SBRT patients." Journal of Clinical Oncology 32, no. 3_suppl (January 20, 2014): 219. http://dx.doi.org/10.1200/jco.2014.32.3_suppl.219.

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219 Background: To clinically utilize an SQL relational database of prior treated patients to generate objectives for future treatment plans. A database approach allows for more rapid planning by starting with a better initial solution and improves safety by providing good known achievable dose values for the initial optimization. The use of a database allows for trending of dose, structure and toxicity data. Methods: A database of fifty-three patients from three institutions is populated with dose and structure data via an automatic script within the treatment planning system. For each new patient, overlap volume histograms (OVHs) are generated to describe the relationship between targets and critical structures. To aid in database consistency, a renaming interface is used which maps known alternative structure names to common names in the database. To ensure all required structures are present, the user is prompted with the names of missing structures. This interface allows selection of machine, energy and commonly used beam sets. The database is queried for all prior patients with the same or closer relationship between the target and each critical structure. The dose objectives reported are the lowest achievable dose from all patients as difficult or harder to plan as determined by OVH. Queried dose objectives are automatically loaded into the treatment planning system and optimized. A protocol quality tool is developed to quickly assess how well plans adhere to specified protocols. Results: Twenty-seven SBRT patients have been planned and clinically approved using the automatic planning tool and future patients continue to be added to the database. OVH computation required approximately 2 minutes, while typical plan optimization required 2.5 minutes. If auto-planned patients require even one fewer optimization to achieve an acceptable plan, total planning time is reduced. Safety is improved by reducing the number of protocol violations from 35% to 6% for one objective. Conclusions: Automatic treatment planning allows for rapid planning while reducing normal tissue dose to known achievable values. The continued addition of patients to the database allows for improvement of the automatically selected planning objectives.

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Nurhadi, Nurhadi, Rabiah Abdul Kadir, and Ely Salwana Mat Surin. "CLASSIFICATION COMPLEX QUERY SQL FOR DATA LAKE MANAGEMENT USING MACHINE LEARNING." Journal of Information System and Technology Management 6, no. 22 (September 1, 2021): 15–24. http://dx.doi.org/10.35631//jistm.622002.

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A query is a request for data or information from a database table or a combination of tables. It allows for a more accurate database search. SQL queries are divided into two types, namely, simple queries and complex queries. Complex SQL is the use of SQL queries that go beyond standard SQL by using the SELECT and WHERE commands. Complex SQL queries often involve the use of complex joins and subqueries, where the queries are nested in a WHERE clause. Complex SQL queries can be grouped into two types of queries, namely, Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) queries. In the implementation of complex SQL queries in the NoSQL database, a classification process is needed due to the varying data formats, namely, structured, semi-structured, and unstructured data. The classification process aims to make it easier for the query data to be organized by type of query. The classification method used in this research is the Naive Bayes Classifier (NBC) which is generally often used in text data, and the Support Vector Machine (SVM), which is known to work very well on data with large dimensions. The two methods will be compared to determine the best classification result. The results showed that SVM was 84.61% accurate in terms of classification, and comparatively, NBC was at 76.92%.

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Suarez-Cabal, M. J., and J. Tuya. "Coverage Measurement for SQL Queries." IEEE Latin America Transactions 3, no. 1 (March 2005): 49–55. http://dx.doi.org/10.1109/tla.2005.1468662.

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Negri, M., G. Pelagatti, and L. Sbattella. "Formal semantics of SQL queries." ACM Transactions on Database Systems 16, no. 3 (September 1991): 513–34. http://dx.doi.org/10.1145/111197.111212.

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Лапко А, Н., А. Куцакин М, А. Дунаев В, and В. Чемодуров М. "METHODOLOGICAL TOOLS FOR THE AUTOMATED VERIFICATION OF SQL QUERIES CORRECTNESS." СИСТЕМЫ УПРАВЛЕНИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ, no. 4(82) (December 1, 2020): 97–101. http://dx.doi.org/10.36622/vstu.2020.13.30.022.

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Статья посвящена автоматизации проверки правильности составления SQL-запросов. Детально описана методика проверки SQL-запросов на основе запросов-образцов и наборов тестирующих инструкций. Приведена структурная схема автоматизированной системы и схема логической структуры базы заданий. The article is devoted to the automated verification of SQL queries correctness. The technique of verification of SQL queries based on sample queries and sets of testing instructions is described in detail. The automated system structural schema and the logical diagram of the task database are presented.

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Liu, Guoxiu, Geng Yang, Huaqun Wang, Yang Xiang, and Hua Dai. "A Novel Secure Scheme for Supporting Complex SQL Queries over Encrypted Databases in Cloud Computing." Security and Communication Networks 2018 (July 3, 2018): 1–15. http://dx.doi.org/10.1155/2018/7383514.

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With the advance of database-as-a-service (DaaS) and cloud computing, increasingly more data owners are motivated to outsource their data to cloud database for great convenience and economic savings. Many encryption schemes have been proposed to process SQL queries over encrypted data in the database. In order to obtain the desired data, the SQL queries contain some statements to describe the requirement, e.g., arithmetic and comparison operators (+, -, ×, <, >, and =). However, to support different operators (+, -, ×, <, >, and =) in SQL queries over encrypted data, multiple encryption schemes need to be combined and adjusted to work together. Moreover, repeated encryptions will reduce the efficiency of execution. This paper presents a practical and secure homomorphic order-preserving encryption (FHOPE) scheme, which allows cloud server to perform complex SQL queries that contain different operators (such as addition, multiplication, order comparison, and equality checks) over encrypted data without repeated encryption. These operators are data interoperable, so they can be combined to formulate complex SQL queries. We conduct security analysis and efficiency evaluation of the proposed scheme FHOPE. The experiment results show that, compared with the existing approaches, the FHOPE scheme incurs less overhead on computation and communication. It is suitable for large batch complex SQL queries over encrypted data in cloud environment.

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Rahman, Nayem. "SQL Scorecard for Improved Stability and Performance of Data Warehouses." International Journal of Software Innovation 4, no. 3 (July 2016): 22–37. http://dx.doi.org/10.4018/ijsi.2016070102.

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Scorecard-based measurement techniques are used by organizations to measure the performance of their business operations. A scorecard approach could be applied to a database system to measure performance of SQL (Structured Query Language) being executed and the extent of resources being used by SQL. In a large data warehouse, thousands of jobs run daily via batch cycles to refresh different subject areas. Simultaneously, thousands of queries by business intelligence tools and ad-hoc queries are being executed twenty-four by seven. There needs to be a controlling mechanism to make sure these batch jobs and queries are efficient and do not consume database systems resources more than optimal. The authors propose measurement of SQL query performance via a scorecard tool. The motivation behind using a scorecard tool is to make sure that the resource consumption of SQL queries is predictable and the database system environment is stable. The experimental results show that queries that pass scorecard evaluation criteria tend to utilize optimal level of database systems computing resources. These queries also show improved parallel efficiency (PE) in using computing resources (CPU, I/O and spool space) that demonstrate the usefulness of SQL scorecard.

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Junkkari, Marko, Johanna Vainio, Kati Iltanen, Paavo Arvola, Heidi Kari, and Jaana Kekäläinen. "Path Expressions in SQL." Journal of Database Management 27, no. 3 (July 2016): 1–22. http://dx.doi.org/10.4018/jdm.2016070101.

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This article focuses on testing a path-oriented querying approach to hierarchical data in relational databases. The authors execute a user study to compare the path-oriented approach and traditional SQL from two perspectives: correctness of queries and time spent in querying. They also analyze what kinds of errors are typical in path-oriented SQL. Path-oriented query languages are popular in the context of object-orientation and XML. However, relational databases are the most common paradigm for storing data and SQL is most common for manipulating data. When querying hierarchical data in SQL, the user must specify join conditions explicitly between hierarchy levels. Path-oriented SQL is a new alternative for expressing hierarchical queries in relational databases. In the authors' study, the users spent significantly less time in writing path-oriented SQL queries and made fewer errors in query formulation.

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Khaidarova, Sapiahon. "CREATING SQL-QUERIES IN RELATIONAL DATABASES." RSUH/RGGU Bulletin. Series Information Science. Information Security. Mathematics, no. 3 (2020): 8–19. http://dx.doi.org/10.28995/2686-679x-2020-3-8-19.

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The article outlines the methods for creating SQL queries in relational databases. The use of the structured query language SQL in relational databases is substantiated. It provides information about the SQL standard and the three-tier database organization system. The author describes the choice of a data model based on the conceptual level using to that end an example of the Kokand Pedagogical Institute as the relational database model. A relational conceptual diagram of the information model of a pedagogical institute is compiled. Such a conceptual diagram is depicted using a cluster. Objects of the subject area are depicted in the form of tables, which differ from each other in geometric shapes or colors. The relationships between tables in Microsoft Access are presented. The basic rules for creating and filling tables in SQL using the instructions CREATE TABLE and INSERT INTO are considered. The syntax of the SELECT statement is given. All offers of the SELECT statement and their order are listed. Examples are given for compiling simple queries and subqueries in SQL using the SELECT statement for the database of the Kokand Pedagogical Institute. Information about the order of execution of internal and external requests is given. The article considers the ORDER BY offer of a SELECT statement for sorting query results.

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S.N, Kavitha. "Tuning SQL Queries for Better Performance." International Journal of Psychosocial Rehabilitation 24, no. 5 (May 25, 2020): 7002–5. http://dx.doi.org/10.37200/ijpr/v24i5/pr2020703.

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Barioni, M. C. N., H. L. Razente, A. J. M. Traina, and C. Traina. "Seamlessly integrating similarity queries in SQL." Software: Practice and Experience 39, no. 4 (March 25, 2009): 355–84. http://dx.doi.org/10.1002/spe.898.

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von Bultzingsloewen, G. "Optimizing SQL queries for parallel execution." ACM SIGMOD Record 18, no. 4 (December 1989): 17–22. http://dx.doi.org/10.1145/74120.74123.

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Dadashzadeh, Mohammad, and David W. Stemple. "Converting SQL queries into relational algebra." Information & Management 19, no. 5 (December 1990): 307–23. http://dx.doi.org/10.1016/0378-7206(90)90045-j.

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Dadashzadeh, Mohammad. "Converting Paradoxs QBE Set Queries Into Access 2000 SQL." Review of Business Information Systems (RBIS) 6, no. 2 (April 1, 2002): 43–56. http://dx.doi.org/10.19030/rbis.v6i2.4570.

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One of the most important promises of the move to an SQL-based accounting software package has been that it frees the accountant from the necessity of resorting to a programmer when retrieving information from the organization's database in response to unanticipated managerial needs. That promise is founded, in part, on the availability of a very high-level, visual relational query language interface known as Query By Example (QBE). Unfortunately, the implementation of QBE in Microsoft Access 2000 fails to support users in formulating complex queries involving set comparison that tend to arise in on-line analytical processing (OLAP) situations. And, while Paradoxs implementation of QBE makes the formulation of such queries quite intuitive, its built-in SQL translation feature fails to provide a clue on how to convert such queries into SQL. This paper presents a systematic approach based on formulating complex set queries in Paradoxs richer QBE notation and translating them into SQL queries that can be handled by Access 2000.

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Dzhidzhoyev, Vladislav Muratovich, Ruben Arturovich Buchatskiy, Michael Vyacheslavovich Pantilimonov, and Alexander Nikolaevich Tomilin. "Dynamic Compilation of User-Defined Functions in PL/pgSQL Language." Proceedings of the Institute for System Programming of the RAS 32, no. 5 (2020): 67–80. http://dx.doi.org/10.15514/ispras-2020-32(5)-5.

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Many modern RDBMS provide procedural extensions for SQL programming language, which allow users to perform server-side complex computations. Use of such extensions improves modularity and code reuse, simplifies programming of application logic, and helps developers to avoid network overhead and enhance performance. Interpretation is mostly used to execute SQL queries and procedural extensions code, resulting in significant computational overhead because of indirect function calls and performing of generic checks. Moreover, most RDBMS use different engines for SQL queries execution and procedural extensions code execution, and it is necessary to perform additional computations to switch between different engines. Thus, interpretation of SQL queries combined with interpretation of procedural extensions code may drastically degrade performance of RDBMS. One solution is to use a dynamic compilation technique. In this paper, we describe the technique of dynamic compilation of PL/pgSQL procedural language for the PostgreSQL database system using LLVM compiler infrastructure. Dynamic compiler of PL/pgSQL procedural language is developed as part of PostgreSQL queries dynamic compiler. Proposed technique helps to get rid of computational overhead caused by interpretation usage. Synthetic performance tests show that the developed solution speeds up SQL queries execution by several times.

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Klassen, R. K., and I. A. Kazantsev. "AUTOMATICAL PRETRANSLATION OF SQL-QUERIES TO A REGULAR PLAN IN CLUSTERIX-LIKE DBMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 196 (October 2020): 11–20. http://dx.doi.org/10.14489/vkit.2020.10.pp.011-020.

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Previously completed designs for pretranslating SQL queries did not bring significant success. Nevertheless, such a pretranslator is necessary for the possibility of using Clusterix-like database management systems (DBMSs) by a wide circle of specialists. The article proposes an original approach to pretranslating SQL queries without writing operations to the regular plan for Clusterix-like DBMSs. The possibility of implementing such a pretranslator is discussed. The concepts of a hard and a simple SQL query are given. The basis of the pretranslator is a library for parsing arbitrary grammars antlr4, which is used to build a SQL query tree. A software-implemented pretranslator uses it to build queries that meet the regular plan.

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Klassen, R. K., and I. A. Kazantsev. "AUTOMATICAL PRETRANSLATION OF SQL-QUERIES TO A REGULAR PLAN IN CLUSTERIX-LIKE DBMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 196 (October 2020): 11–20. http://dx.doi.org/10.14489/vkit.2020.10.pp.011-020.

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Previously completed designs for pretranslating SQL queries did not bring significant success. Nevertheless, such a pretranslator is necessary for the possibility of using Clusterix-like database management systems (DBMSs) by a wide circle of specialists. The article proposes an original approach to pretranslating SQL queries without writing operations to the regular plan for Clusterix-like DBMSs. The possibility of implementing such a pretranslator is discussed. The concepts of a hard and a simple SQL query are given. The basis of the pretranslator is a library for parsing arbitrary grammars antlr4, which is used to build a SQL query tree. A software-implemented pretranslator uses it to build queries that meet the regular plan.

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Skaruz, Jarosław. "Database security: combining neural networks and classification approach." Studia Informatica, no. 23 (December 22, 2020): 95–115. http://dx.doi.org/10.34739/si.2019.23.06.

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In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take the advantage of using SQL statements to be performed. The problem of detection of this class of attacks is transformed to time series prediction problem. SQL queries are used as a source of events in a protected environment. To differentiate between normal SQL queries and those sent by an attacker, we divide SQL statements into tokens and pass them to our detection system, which predicts the next token, taking into account previously seen tokens. In the learning phase tokens are passed to a recurrent neural network (RNN) trained by backpropagation through time (BPTT) algorithm. Then, two coefficients of the rule are evaluated. The rule is used to interpret RNN output. In the testing phase RNN with the rule is examined against attacks and legal data to find out how evaluated rule affects efficiency of detecting attacks. All experiments were conducted on Jordan network. Experimental results show the relationship between the rule and a length of SQL queries.

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Rymarski, Piotr, and Grzegorz Kozieł. "Analysis of the possibilities of optimizing SQL queries." Journal of Computer Sciences Institute 19 (June 30, 2021): 151–58. http://dx.doi.org/10.35784/jcsi.2641.

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Most of today's web applications run on relational database systems. Communication with them is possible through statements written in Structured Query Language (SQL). This paper presents the most popular relational database management systems and describes common ways to optimize SQL queries. Using the research environment based on fragment of the imdb.com database, implementing OracleDb, MySQL, Microsoft SQL Server and PostgreSQL engines, a number of test scenarios were performed. The aim was to check the performance changes of SQL queries resulting from syntax modication while maintaining the result, the impact of database organization, indexing and advanced mechanisms aimed at increasing the eciency of operations performed, delivered in the systems used. The tests were carried out using a proprietary application written in Java using the Hibernate framework.

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Lambert, Sherwood Lane, Jon Holladay, and Dawna M. Drum. "International AC: An Education Case on Continuous Monitoring SQL Server Data with ODBC-Linked Tables in Microsoft Access." Journal of Emerging Technologies in Accounting 13, no. 2 (September 1, 2016): 195–213. http://dx.doi.org/10.2308/jeta-51597.

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ABSTRACT This education case teaches students Continuous Auditing/Continuous Monitoring (CA/CM) using Open Database Connectivity (ODBC) connections from students' Microsoft Access (Access) to tables in Microsoft SQL Server (SQL Server). First, the institution's database administrator (DBA) imports the student tables provided with the Teaching Notes into the institution's SQL Server with read-only access. In Access, students create ODBC connections to the SQL Server student tables. Then, students create Access queries using the ODBC-linked tables to monitor for anomalies. During a scheduled week, the DBA, in coordination with the faculty member, enters anomalies in the SQL Server student tables at random times, and students run their Access queries to identify the anomalies.

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Reye, James D. "Providing Insight into SQL." Journal of Educational Technology Systems 24, no. 4 (June 1996): 321–33. http://dx.doi.org/10.2190/x9h9-cl62-d31b-jmq1.

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SQL is the well-known, industry-standard language for accessing relational databases. Although users often have no trouble writing simple queries in SQL, most people experience difficulties in correctly formulating and understanding more complex queries. To help users gain a greater insight into SQL, a special interface has been developed. This is intended as a support tool for introductory database courses. This system provides two special facilities: 1) a progressive execution option, which allows the user to receive immediate feedback on an SQL query as it is being entered on a word-by-word basis; and 2) additional windows which allow the user to view an illustration of what is occurring inside an SQL query, as well as the final results.

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Hudec, Miroslav. "Fuzzy improvement of the SQL." Yugoslav Journal of Operations Research 21, no. 2 (2011): 239–51. http://dx.doi.org/10.2298/yjor1102239h.

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Structured Query Language (SQL) is used to obtain data from relational databases. Fuzzy improvement of SQL queries has advantages in cases when the user cannot unambiguously define selection criteria or when the user wants to examine data that almost meet the given criteria. In this paper we examine a realization of the fuzzy querying concept. For this purposes the fuzzy generalized logical condition for the WHERE part of the SQL is created. It allows users to create queries by linguistic terms. The proposed model is an extension of the SQL so that no modification inside databases has to be undertaken.

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Goel, Piyush, and Bala Iyer. "SQL query optimization." ACM SIGMOD Record 25, no. 2 (June 1996): 47–56. http://dx.doi.org/10.1145/235968.233318.

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Chukhray, Andrey, and Olena Havrylenko. "The method of student's query analysis while intelligent computer tutoring in SQL." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 2 (June 2, 2021): 78–86. http://dx.doi.org/10.32620/reks.2021.2.07.

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Recently, IT specialties have become one of the most demanded specialties in the world labor market. Simultaneously the traditional teaching in conditions of mass production, even with a professional teacher, has a significant drawback – the fundamental impossibility of adapting to each student. Since the 60s of the twentieth century, researchers worldwide have been developing various computer-tutoring tools that have, less or more, adaptive functions. Nevertheless, the task of the perfect computer tutor development is still far from being solved. The article's research subject is the process of student requests analyzing during intelligent computer tutoring in SQL. The main goal is to develop a method for analyzing the student's SQL queries. The purposes: to form a general scheme and features of the method for analyzing student’s SQL queries based on the principles of technical diagnostics and methods of lexical, syntactic analysis of computer programs; to develop methods for parse tree construction; to create methods for comparing reference and real SQL queries according to their similarity rate; to demonstrate the function ability of the developed methods on specific examples. The methods used computer programs the automatic testing method, the computer programs lexical and syntactic analysis methods, the computer programs parsing trees construction methods, the objects diagnosing method based on comparison with a reference, the strings analysis methods, the method of q-grams. The following results were obtained: the student’s SQL queries analysis method was formed based on a system approach including automatic testing on real data, building query-parsing trees, comparison with a reference, and comprehensive determination of the queries similarity rate. The scientific novelty is the improvement of the method for the student's SQL query analysis during intelligent computer training in SQL query composition.

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Das, A. K., and M. A. Musen. "A Temporal Query System for Protocol-Directed Decision Support." Methods of Information in Medicine 33, no. 04 (1994): 358–70. http://dx.doi.org/10.1055/s-0038-1635036.

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Abstract:Chronus is a query system that supports temporal extensions to the Structured Query Language (SQL) for relational databases. Although the relational data model can store time-stamped data and can permit simple temporal-comparison operations, it does not provide either a closed or a sufficient algebra for manipulating temporal data. In this paper, we outline an algebra that maintains a consistent relational representation of temporal data and that allows the type of temporal queries needed for protocol-directed decision support. We also discuss how Chronus can translate between our temporal algebra and the relational algebra used for SQL queries. We have applied our system to the task of screening patients for clinical trials. Our results demonstrate that Chronus can express sufficiently all required temporal queries, and that the search time of such queries is similar to that of standard SQL.

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J. Santhosh Kumar, B., and P. P. Anaswara. "Vulnerability detection and prevention of SQL injection." International Journal of Engineering & Technology 7, no. 2.31 (May 29, 2018): 16. http://dx.doi.org/10.14419/ijet.v7i2.31.13388.

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SQL injection attack is the most serious security vulnerabilities on databases are connected with web or within an intranet, most of these vulnerabilities are affected by lack of input validation and SQL parameters are use. The attackers are trying to steal the data which was hidden and by attacking the database using the attacking technique that is called SQL injection attacks. The SQL injection attack detection and prevention technologies are experimented in this paper. There are different defence methods are used to prevent such as, parameterized statement, stored procedures and white list input validation. The comparative results of these methods are highlighted in the table with SQL injection query, prepared statement insertion and selection queries, stored procedures and modify queries. The comparison of these methods used for detection and prevention vulnerability in web server.

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Johnson, Noah, Joseph P. Near, and Dawn Song. "Towards practical differential privacy for SQL queries." Proceedings of the VLDB Endowment 11, no. 5 (January 1, 2018): 526–39. http://dx.doi.org/10.1145/3187009.3177733.

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Grust, Torsten, and Jan Rittinger. "Observing SQL queries in their natural habitat." ACM Transactions on Database Systems 38, no. 1 (April 2013): 1–33. http://dx.doi.org/10.1145/2445583.2445586.

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Huang, Bo, and Hui Lin. "Restructuring the SQL Framework for Spatial Queries." Annals of GIS 3, no. 1-2 (December 1997): 42–50. http://dx.doi.org/10.1080/10824009709480492.

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Buchatskiy, R. A., E. Y. Sharygin, L. V. Skvortsov, R. A. Zhuykov, D. M. Melnik, and R. V. Baev. "Dynamic compilation of SQL queries for PostgreSQL." Proceedings of the Institute for System Programming of the RAS 28, no. 6 (2016): 37–48. http://dx.doi.org/10.15514/ispras-2016-28(6)-3.

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Suarez-Cabal, M. J., C. de la Riva, and J. Tuya. "Populating Test Databases for Testing SQL Queries." IEEE Latin America Transactions 8, no. 2 (April 2010): 164–71. http://dx.doi.org/10.1109/tla.2010.5514443.

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Cao, Bin, and Antonio Badia. "Exploiting maximal redundancy to optimize SQL queries." Knowledge and Information Systems 20, no. 2 (August 26, 2008): 187–220. http://dx.doi.org/10.1007/s10115-008-0156-0.

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Buitendijk, R. B. "Logical errors in database SQL retrieval queries." Computer Science in Economics and Management 1, no. 2 (1988): 79–96. http://dx.doi.org/10.1007/bf00427157.

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SÁENZ-PÉREZ, FERNANDO. "Applying Constraint Logic Programming to SQL Semantic Analysis." Theory and Practice of Logic Programming 19, no. 5-6 (September 2019): 808–25. http://dx.doi.org/10.1017/s1471068419000206.

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AbstractThis paper proposes the use of Constraint Logic Programming (CLP) to model SQL queries in a data-independent abstract layer by focusing on some semantic properties for signalling possible errors in such queries. First, we define a translation from SQL to Datalog, and from Datalog to CLP, so that solving this CLP program will give information about inconsistency, tautology, and possible simplifications. We use different constraint domains which are mapped to SQL types, and propose them to cooperate for improving accuracy. Our approach leverages a deductive system that includes SQL and Datalog, and we present an implementation in this system which is currently being tested in classroom, showing its advantages and differences with respect to other approaches, as well as some performance data.

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Harvey, Valerie J., Jeanne M. Baugh, Bruce A. Johnston, Constance M. Ruzich, and Arthur J. Grant. "The Challenge Of Negation In Searches And Queries." Review of Business Information Systems (RBIS) 7, no. 4 (October 1, 2003): 63–76. http://dx.doi.org/10.19030/rbis.v7i4.4514.

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Negation poses certain challenges for queries and searches. This paper deals with exclusionary queries implemented using the ISO database language SQL and a dialog-based interface and with retrieval searches involving negation. This research arose because instructors in database courses noticed a large proportion of students making mistakes on certain queries. The paper explores underlying comprehension issues and makes practical recommendations on identifying potential sources of error and avoiding incorrect or misleading results. Proposed actions include changes in general education and database training and encouraging implementation of the new SQL:1999 standard.

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Munot, Priyanka R., Dipali R. Patil, and Kajal P. Pathak. "SQL Query Optimization Techniques." IJARCCE 8, no. 5 (May 30, 2019): 87–90. http://dx.doi.org/10.17148/ijarcce.2019.8518.

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MURAKAWA, Takehiko, Junichi ENDO, Kazunori MATSUO, and Masaru NAKAGAWA. "Automatic Conversion of SQL statements into NoSQL queries." Joho Chishiki Gakkaishi 22, no. 2 (2012): 126–31. http://dx.doi.org/10.2964/jsik.22_126.

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Journal articles on the topic 'Optimization of SQL queries'

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