A Universal Relation Approach For Natural Query In Logic Database System

1992 ◽  
pp. 46-64
Author(s):  
Harihodin Selamat
Keyword(s):  
Query Language ◽  
Database Systems ◽  
Optimization Techniques ◽  
Deductive Database ◽  
Universal Relation ◽  
Data Types ◽  
Natural Language Query ◽  
Query System ◽  
Relational Database Systems ◽  
Relation Approach

Recent advances in Artificial Intelligence and Relational Database systems have contributed to the development of Logic Database systems. A lot of research in logic database have been encompassed on the query evaluation and optimization techniques. Very litde effort has been put to the development of the user's query system to facilitate the naive users interacting with the database. Currently, the form of query is based on the primitive logic form. Therefore, this project aims at developing a prototype natural query system to the logic database as a compromise between the primitive logic query and the natural language query systems. This paper describes a conceptual framework of the natural query system. The concept of predicate universal relation is introduced as an interface to bridge the natural query and the corresponding primitive logic query. The concept of data types is employed as a tool towards the construction of the predicate universal relation. We believe this is the first attempt towards a natural query system for logic database via a universal relation approach. Keywords: query interface, logic database, deductive database, universal relation, query processing, query language, natural query, first order logic, data types

Object-Relational Spatial Indexing

2011 ◽  
pp. 49-80
Author(s):  
Hans-Peter Kriegel ◽  
Martin Pfeifle ◽  
Marco Potke ◽  
Thomas Seidl ◽  
Jost Enderle
Keyword(s):  
Spatial Data ◽  
Concurrency Control ◽  
Buffer Management ◽  
Database Systems ◽  
Data Types ◽  
Spatial Access ◽  
Access Methods ◽  
Object Relational ◽  
Relational Database Systems ◽  
Spatial Access Methods

In order to generate efficient execution plans for queries comprising spatial data types and predicates, the database system has to be equipped with appropriate index structures, query processing methods and optimization rules. Although available extensible indexing frameworks provide a gateway for seamless integration of spatial access methods into the standard process of query optimization and execution, they do not facilitate the actual implementation of the spatial access method. An internal enhancement of the database kernel is usually not an option for database developers. The embedding of a custom, block-oriented index structure into concurrency control, recovery services and buffer management would cause extensive implementation efforts and maintenance cost, at the risk of weakening the reliability of the entire system. The server stability can be preserved by delegating index operations to an external process, but this approach induces severe performance bottlenecks due to context switches and inter-process communication. Therefore, we present the paradigm of object-relational spatial access methods that perfectly fits to the common relational data model, and is highly compatible with the extensible indexing frameworks of existing object-relational database systems, allowing the user to define application-specific access methods.

scholarly journals Analysis of the possibilities of optimizing SQL queries

2021 ◽  
Vol 19 ◽  
pp. 151-158
Author(s):  
Piotr Rymarski ◽  
Grzegorz Kozieł
Keyword(s):  
Relational Database ◽  
Web Applications ◽  
Query Language ◽  
Database Systems ◽  
Sql Server ◽  
Management Systems ◽  
Relational Database Systems ◽  
The Impact ◽  
Relational Database Management ◽  
Test Scenarios

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.

scholarly journals Hindi Language Interface to Database

2020 ◽  
Vol 32 ◽  
pp. 01007
Author(s):  
Rachana Dubey ◽  
Tejal Kawale ◽  
Twisha Choudhary ◽  
Vaibhav Narawade
Keyword(s):  
Natural Language ◽  
Data Storage ◽  
Query Language ◽  
Database Systems ◽  
Sources Of Information ◽  
Common People ◽  
Storage And Retrieval ◽  
Natural Language Query ◽  
Sql Query ◽  
Information Database

In our everyday lives we require information to accomplish daily tasks. Database is one of the most important sources of information. Database systems have been widely used in data storage and retrieval. However, to extract information from databases, we need to have some knowledge of database languages like SQL. But SQL has predefined structures and format, so it is hard for the non-expert users to formulate the desired query. To override this complexity, we have turned to natural language to retrieve information from database, which can be an ideal channel between a non-technical user and the application. But the application cannot understand natural language so an interface is required. This interface is capable of converting the user’s natural language query to an equivalent database language query. In this paper, we address the system architecture for translating a Hindi sentence in the form of an audio to an equivalent SQL query. The users don’t need to learn any formal query language; hence it’s easy to use for common people.

scholarly journals Evaluation of Optimization Strategies for Incremental Graph Queries

2017 ◽  
Vol 61 (2) ◽  
pp. 175 ◽  
Author(s):  
Gábor Szárnyas ◽  
János Maginecz ◽  
Dániel Varró
Keyword(s):  
Response Times ◽  
Distributed Storage ◽  
Large Data ◽  
Database Systems ◽  
Optimization Techniques ◽  
Large Data Sets ◽  
Data Sets ◽  
Multiple Datasets ◽  
Graph Queries ◽  
Relational Database Systems

The last decade brought considerable improvements in distributed storage and query technologies, known as NoSQL systems. These systems provide quick evaluation of simple retrieval operations and are able to answer certain complex queries in a scalable way, albeit not instantly. Providing scalability and quick response times at the same time for querying large data sets is still a challenging task. Evaluating complex graph queries is particularly difficult, as it requires lots of join, antijoin and filtering operations. This paper presents optimization techniques used in relational database systems and applies them on graph queries. We evaluate various query plans on multiple datasets and discuss the effect of different optimization techniques.

Fuzzy Classification on Relational Databases

2011 ◽  
pp. 586-614 ◽  
Author(s):  
Andreas Meier ◽  
Günter Schindler ◽  
Nicolas Werro
Keyword(s):  
Relational Databases ◽  
Information Overload ◽  
Query Language ◽  
Large Data ◽  
Database Systems ◽  
Fuzzy Classification ◽  
Linguistic Variables ◽  
Context Model ◽  
Relational Database Systems ◽  
Data Collections

In practice, information systems are based on very large data collections mostly stored in relational databases. As a result of information overload, it has become increasingly difficult to analyze huge amounts of data and to generate appropriate management decisions. Furthermore, data are often imprecise because they do not accurately represent the world or because they are themselves imperfect. For these reasons, a context model with fuzzy classes is proposed to extend relational database systems. More precisely, fuzzy classes and linguistic variables and terms, together with appropriate membership functions, are added to the database schema. The fuzzy classification query language (fCQL) allows the user to formulate unsharp queries that are then transformed into appropriate SQL statements using the fCQL toolkit so that no migration of the raw data is needed. In addition to the context model with fuzzy classes, fCQL and its implementation are presented here, illustrated by concrete examples.

Access path query language for relational database systems

1983 ◽  
Vol 13 (8) ◽  
pp. 661-670
Author(s):  
L. M. Patnaik ◽  
Phule Shailendra ◽  
K. Venkateswara Rao
Keyword(s):  
Relational Database ◽  
Query Language ◽  
Database Systems ◽  
Access Path ◽  
Relational Database Systems

scholarly journals A Simpler and Semantic Multidimensional Database Query Language to Facilitate Access to Information in Decision-making

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Fredi Edgardo Palominos ◽  
Felisa Córdova ◽  
Claudia Durán ◽  
Bryan Nuñez
Keyword(s):  
Decision Making ◽  
Query Language ◽  
Database Systems ◽  
Relational Algebra ◽  
Multidimensional Database ◽  
Management Indicators ◽  
Relational Calculus ◽  
Database Technology ◽  
Sql Language ◽  
Relational Database Systems

OLAP and multidimensional database technology have contributed significantly to speed up and build confidence in the effectiveness of methodologies based on the use of management indicators in decision-making, industry, production, and services. Although there are a wide variety of tools related to the OLAP approach, many implementations are performed in relational database systems (R-OLAP). So, all interrogation actions are performed through queries that must be reinterpreted in the SQL language. This translation has several consequences because SQL language is based on a mixture of relational algebra and tuple relational calculus, which conceptually responds to the logic of the relational data model, very different from the needs of the multidimensional databases. This paper presents a multidimensional query language that allows expressing multidimensional queries directly over ROLAP databases. The implementation of the multidimensional query language will be done through a middleware that is responsible for mapping the queries, hiding the translation to a layer of software not noticeable to the end-user. Currently, progress has been made in the definition of a language where through a key statement, called aggregate, it is possible to execute the typical multidimensional operators which represent an important part of the most frequent operations in this type of database.

Database Queries, Data Mining, and OLAP

2011 ◽  
pp. 598-603
Author(s):  
Lutz Hamel
Keyword(s):  
Data Mining ◽  
Relational Database ◽  
Query Language ◽  
Data Retrieval ◽  
Database Systems ◽  
Database Queries ◽  
On Line ◽  
Analytical Processing ◽  
Relational Database Systems ◽  
Complementary Value

Modern, commercially available relational database systems now routinely include a cadre of data retrieval and analysis tools. Here we shed some light on the interrelationships between the most common tools and components included in today’s database systems: query language engines, data mining components, and on-line analytical processing (OLAP) tools. We do so by pair-wise juxtaposition which will underscore their differences and highlight their complementary value.

Database Queries, Data Mining, and OLAP

2011 ◽  
pp. 339-343
Author(s):  
Lutz Hamel
Keyword(s):  
Data Mining ◽  
Relational Database ◽  
Query Language ◽  
Data Retrieval ◽  
Database Systems ◽  
Database Queries ◽  
Analytical Processing ◽  
Relational Database Systems ◽  
Complementary Value ◽  
Do So

Modern, commercially available relational database systems now routinely include a cadre of data retrieval and analysis tools. Here we shed some light on the interrelationships between the most common tools and components included in today’s database systems: query language engines, data mining components, and online analytical processing (OLAP) tools. We do so by pair-wise juxtaposition, which will underscore their differences and highlight their complementary value.

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