A query language and interface for integrated media and alphanumeric database systems

1997 ◽  
pp. 508-518
Author(s):  
Jia-Ling Koh ◽  
Arbee L. P. Chen ◽  
Paul C. M. Chang ◽  
James C. C. Chen
Keyword(s):  
Query Language ◽  
Database Systems ◽  
Integrated Media

scholarly journals Array databases: concepts, standards, implementations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peter Baumann ◽  
Dimitar Misev ◽  
Vlad Merticariu ◽  
Bang Pham Huu
Keyword(s):  
Service Quality ◽  
Ad Hoc ◽  
Query Language ◽  
Distributed Processing ◽  
Database Systems ◽  
Database Technology ◽  
Comprehensive Survey ◽  
Spatio Temporal ◽  
And Performance ◽  
Array Databases

AbstractMulti-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacubes”. As classic database technology does not support arrays adequately, such data today are maintained mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for flexible ad-hoc analytics on large n-D arrays, similar to what SQL offers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison differentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the field; for example, subsetting tests were designed in a way that systems cannot be tuned to specifically these queries. It is hoped that this gives a representative overview to all who want to immerse into the field as well as a clear guidance to those who need to choose the best suited datacube tool for their application. This article presents results of the Research Data Alliance (RDA) Array Database Assessment Working Group (ADA:WG), a subgroup of the Big Data Interest Group. It has elicited the state of the art in Array Databases, technically supported by IEEE GRSS and CODATA Germany, to answer the question: how can data scientists and engineers benefit from Array Database technology? As it turns out, Array Databases can offer significant advantages in terms of flexibility, functionality, extensibility, as well as performance and scalability—in total, the database approach of offering “datacubes” analysis-ready heralds a new level of service quality. Investigation shows that there is a lively ecosystem of technology with increasing uptake, and proven array analytics standards are in place. Consequently, such approaches have to be considered a serious option for datacube services in science, engineering and beyond. Tools, though, vary greatly in functionality and performance as it turns out.

scholarly journals Performance Benchmarking of Key-Value Store NoSQL Databases

2018 ◽  
Vol 8 (6) ◽  
pp. 5333
Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Query Language ◽  
Research Work ◽  
Database Systems ◽  
Nosql Databases ◽  
Performance Benchmarking ◽  
Nosql Database ◽  
Structured Query Language ◽  
Web Developers

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

Query Optimization in Crowd-Sourcing Using Multi-Objective Ant Lion Optimizer

2019 ◽  
Vol 14 (4) ◽  
pp. 50-63 ◽  
Author(s):  
Deepak Kumar ◽  
Deepti Mehrotra ◽  
Rohit Bansal
Keyword(s):  
Query Optimization ◽  
Query Language ◽  
Database Systems ◽  
Amazon Mechanical Turk ◽  
Optimization Approach ◽  
Crowd Sourcing ◽  
Market Place ◽  
Multi Objective ◽  
Ant Lion Optimizer ◽  
Ant Lion

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.

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.

The Effects on End-User Query Performance of Incorporating Object-Oriented Abstractions in Database Accounting Systems

2005 ◽  
Vol 19 (1) ◽  
pp. 43-74 ◽  
Author(s):  
Roger S. Debreceny ◽  
Paul L. Bowen
Keyword(s):  
Information Systems ◽  
Query Language ◽  
Accounting Information ◽  
Object Oriented ◽  
Database Systems ◽  
Control Group ◽  
Relational Schema ◽  
Accounting Information Systems ◽  
Query Performance ◽  
User Query

Object-oriented (OO) advocates assert that concepts such as generalization-specialization hierarchies (GSHs) and abstract data types (ADTs) make information systems more usable by increasing the level of abstraction of the data structure. This study analyzes the effects of GSHs and ADTs on the performance of end-users of accounting information systems. Two groups of experimental participants interactively developed Structured Query Language (SQL) queries to answer ten business questions. The control group (n = 28) used data stored in a traditional relational schema. The experimental group (n = 31) used the same data stored in an OO schema that included GSHs and ADTs. Both schemas implemented the same database accounting model of the sales cycle of a hypothetical company. Participants using the higher abstraction (OO) schema with GSHs and ADTs made fewer semantic errors than did participants using the traditional relational schema. The OO participants also required less time to formulate their queries. These results have several important implications. First, relational database vendors should continue, if not accelerate, their efforts to incorporate OO features such as GSHs and ADTs into their database systems. Second, users of accounting information systems need to improve their understanding of the implications of various data structures on their interactive queries. Third, research should investigate the effects of other abstraction mechanisms, including classification/instantiation and aggregation/decomposition, on query performance.

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.

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.

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

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