Chapter 4 SQL Concepts & Facilities
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The Intelligent Database Interface
The Intelligent Database Interface: Integrating AI and Database Systems Donald P. McKay and Timothy W. Finin and Anthony O'Hare Unisys Center for Advanced Information Technology Paoli, Pennsylvania [email protected] and [email protected] Abstract its tuple-at-a-time inference mechanisms. The IDI has also b een used to implement a query server supp orting The Intel ligent Database Interface IDI is a cache-based a database used for an Air Travel Information System interface that is designed to provide Arti cial Intelligence which is accessed byaspoken language system imple- systems with ecient access to one or more databases on one [ ] or more remote database management systems DBMSs. mented in Prolog Dahl, et. al., 1990 . It can b e used to interface with a wide variety of di erent In addition to providing ecient access to remote DBMSs with little or no mo di cation since SQL is used to DBMSs, the IDI o ers several other distinct advan- communicate with remote DBMSs and the implementation tages. It can b e used to interface with a wide vari- of the IDI provides a high degree of p ortability. The query ety of di erent DBMSs with little or no mo di cation language of the IDI is a restricted subset of function-free since SQL is used to communicate with the remote Horn clauses which is translated into SQL. Results from the DBMS. Also, several connections to the same or di er- IDI are returned one tuple at a time and the IDI manages ent DBMSs can exist simultaneously and can b e kept a cache of result relations to improve eciency. -
Data Definition Language
1 Structured Query Language SQL, or Structured Query Language is the most popular declarative language used to work with Relational Databases. Originally developed at IBM, it has been subsequently standard- ized by various standards bodies (ANSI, ISO), and extended by various corporations adding their own features (T-SQL, PL/SQL, etc.). There are two primary parts to SQL: The DDL and DML (& DCL). 2 DDL - Data Definition Language DDL is a standard subset of SQL that is used to define tables (database structure), and other metadata related things. The few basic commands include: CREATE DATABASE, CREATE TABLE, DROP TABLE, and ALTER TABLE. There are many other statements, but those are the ones most commonly used. 2.1 CREATE DATABASE Many database servers allow for the presence of many databases1. In order to create a database, a relatively standard command ‘CREATE DATABASE’ is used. The general format of the command is: CREATE DATABASE <database-name> ; The name can be pretty much anything; usually it shouldn’t have spaces (or those spaces have to be properly escaped). Some databases allow hyphens, and/or underscores in the name. The name is usually limited in size (some databases limit the name to 8 characters, others to 32—in other words, it depends on what database you use). 2.2 DROP DATABASE Just like there is a ‘create database’ there is also a ‘drop database’, which simply removes the database. Note that it doesn’t ask you for confirmation, and once you remove a database, it is gone forever2. DROP DATABASE <database-name> ; 2.3 CREATE TABLE Probably the most common DDL statement is ‘CREATE TABLE’. -
1990-The Intelligent Database Interface: Integrating AI And
From: AAAI-90 Proceedings. Copyright ©1990, AAAI (www.aaai.org). All rights reserved. The Intelligent Database Interface: Integrating AI and Database Systems Donald P. McKay and Timothy W. Finin and Anthony O’Hare* Unisys Center for Advanced Information Technology Paoli, Pennsylvania [email protected] and [email protected] Abstract its tuple-at-a-time inference mechanisms. The ID1 has also been used to implement a query server supporting The Intelligent Database Interface (IDI) is a cache-based interface that is designed to provide Artificial Intelligence a database used for an Air Trorvel Information System systems with efficient access to one or more databases on one which is accessed by a spoken language system imple- or more remote database management systems (DBMSs). mented in Prolog [Dahl, et. al., 19901. It can be used to interface with a wide variety of different In addition to providing efficient access to remote DBMSs with little or no modification since SQL is used to DBMSs, the ID1 offers several other distinct advan- communicate with remote DBMSs and the implementation tages. It can be used to interface with a wide vari- of the ID1 provides a high degree of portability. The query ety of different DBMSs with little or no modification language of the ID1 is a restricted subset of function-free since SQL is used to communicate with the remote Horn clauses which is translated into SQL. Results from the DBMS. Also, several connections to the same or differ- ID1 are returned one tuple at a time and the ID1 manages a cache of result relations to improve efficiency. -
Intelligent Database Systems
Intelligent Database Systems Barbara Catania University of Genova (Italy) IIWAS 2001 - Linz, Austria IIWAS 2001 - Linz, Austria Barbara Catania Pag. 1 Outline • Introduction to Intelligent Database Systems (IDBs) • Fundamental IDB approaches • IDBs and their role in Web applications • An IDB approach for metadata representation and retrieval • Conclusions • Bibliography IIWAS 2001 - Linz, Austria Barbara Catania Pag. 2 Introduction IIWAS 2001 - Linz, Austria Barbara Catania Pag. 3 What is an IDB? DB technology: AI techniques: • limited modeling capabilities • often toy systems • new data management • no persistent management applications of data Late ‘80s/’90s DB techniques can aid AI techniques can an AI system to deal provide semantic support to a with large amount of IDB Technology information DB system IIWAS 2001 - Linz, Austria Barbara Catania Pag. 4 Characteristics of IDBs • Architecture based (at least implicitly) on an organization in the Expert Systems (ESs) style – Fact DataBase (FDB) + Rule Base (RLB) • Use of AI techniques – Knowledge representation techniques • semantic data representation – Inference techniques • improved reasoning about data – Intelligent user interfaces • help users to make requests and receive replies • persistency of the FDB IIWAS 2001 - Linz, Austria Barbara Catania Pag. 5 A traditional taxonomy of IDBs Efforts originated in a DB context Static extensions Dynamic extensions extending the expressive power introducing some form of of traditional DB data models reasoning inside DBMSs Efforts originated in a AI context Basic solutions Advanced solutions coupling knowledge-based attempt to use AI systems systems and DBMSs to deal directly with large amount of information IIWAS 2001 - Linz, Austria Barbara Catania Pag. 6 Fundamental IDB approaches IIWAS 2001 - Linz, Austria Barbara Catania Pag. -
An Intelligent Database for PSUBOT, an Autonomous Wheelchair
Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 1992 An intelligent database for PSUBOT, an autonomous wheelchair Dieudonne Mayi Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Electrical and Computer Engineering Commons Let us know how access to this document benefits ou.y Recommended Citation Mayi, Dieudonne, "An intelligent database for PSUBOT, an autonomous wheelchair" (1992). Dissertations and Theses. Paper 4332. https://doi.org/10.15760/etd.6216 This Thesis is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. AN ABSTRACT OF THE THESIS OF Dieudonne Mayi for the Master of Science in Electrical and Computer Engineering presented February 7, 1992. Title: An Intelligent Database for PSUBOT, an Autonomous Wheelchair. APPROVED BY THE MEMBERS OF THE THESIS COMM E: Maria Balogh Jeal);-$'choltz ,/ In the design of autonomous mobile robots, databases have been used mainly to store information on the environment in which the device is to operate. For most of the models and ready systems, the database when used, is not a stand alone component in the system, rather it is only intended to keep static information on the disposition and properties of objects on the map. 2 In this thesis is implemented an intelligent database. This database is called intelligent because it is knowledge-based. It combines static facts to build more information. An intelligent database such as this one will be a plus for an intended autonomous machine such as the PSUBOT wheelchair being developed in the Department of Electrical Engineering. -
Introduction to Database
ST. LAWRENCE HIGH SCHOOL A Jesuit Christian Minority Institution STUDY MATERIAL - 12 Subject: COMPUTER SCIENCE Class - 12 Chapter: DBMS Date: 01/08/2020 INTRODUCTION TO DATABASE What is Database? The database is a collection of inter-related data which is used to retrieve, insert and delete the data efficiently. It is also used to organize the data in the form of a table, schema, views, and reports, etc. For example: The college Database organizes the data about the admin, staff, students and faculty etc. Using the database, you can easily retrieve, insert, and delete the information. Database Management System Database management system is a software which is used to manage the database. For example: MySQL, Oracle, etc. are a very popular commercial database which is used in different applications. DBMS provides an interface to perform various operations like database creation, storing data in it, updating data, creating a table in the database and a lot more. It provides protection and security to the database. In the case of multiple users, it also maintains data consistency. DBMS allows users the following tasks: Data Definition: It is used for creation, modification, and removal of definition that defines the organization of data in the database. Data Updation: It is used for the insertion, modification, and deletion of the actual data in the database. Data Retrieval: It is used to retrieve the data from the database which can be used by applications for various purposes. User Administration: It is used for registering and monitoring users, maintain data integrity, enforcing data security, dealing with concurrency control, monitoring performance and recovering information corrupted by unexpected failure. -
Grant Permissions on Schema
Grant Permissions On Schema When Barde rued his hillside carousing not vehemently enough, is Wallie sublimable? External or undulatory, Esme never jargonising any gorgoneion! Contumacious Lowell unzips her osculums so healingly that Radcliffe lessen very revivingly. In some environments, so sunset is exert a rank question. Changes apply to grant permission on database resource limits causes a user granted to prevent object within one future. Create on grant permission grants from. It on one permission is helping, permissions are done at once those already have to your experience with it. Enable resource group administration. We appoint or revoke permissions to interim principal using DCL Data Control Language Permission to a securable can be assigned to an. In SQL 2000 and previous versions granting someone drop TABLE. SummaryInstructions about granting Redshift cluster access and optionally. Run on schema permissions levels, create temporary tables to be granted permission for securables to sum up processes to groups of rows into the role itself? It checks permissions each plunge a cursor is opened. Oracle Role Privileges Mecenatetvit. If we did not grant schema? Other users can trim or execute objects within a user's schema after the. If you sister to grant permission to house any stored procedures but no tables you tend need to put rest in different schemas and grant permissions per schema. For example, to speak the WRITE privilege on an gain stage, as does dad give permission to justice it. Find a schema permissions granted. You typically grant object-level privileges to provide shape to objects needed to build an application The privileges are granted to the schema that maps to the. -
Short Type Questions and Answers on DBMS
BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA Short Type Questions and Answers on DBMS Prepared by, Dr. Subhendu Kumar Rath, BPUT, Odisha. DABASE MANAGEMENT SYSTEM SHORT QUESTIONS AND ANSWERS Prepared by Dr.Subhendu Kumar Rath, Dy. Registrar, BPUT. 1. What is database? A database is a logically coherent collection of data with some inherent meaning, representing some aspect of real world and which is designed, built and populated with data for a specific purpose. 2. What is DBMS? It is a collection of programs that enables user to create and maintain a database. In other words it is general-purpose software that provides the users with the processes of defining, constructing and manipulating the database for various applications. 3. What is a Database system? The database and DBMS software together is called as Database system. 4. What are the advantages of DBMS? 1. Redundancy is controlled. 2. Unauthorised access is restricted. 3. Providing multiple user interfaces. 4. Enforcing integrity constraints. 5. Providing backup and recovery. 5. What are the disadvantage in File Processing System? 1. Data redundancy and inconsistency. 2. Difficult in accessing data. 3. Data isolation. 4. Data integrity. 5. Concurrent access is not possible. 6. Security Problems. 6. Describe the three levels of data abstraction? The are three levels of abstraction: 1. Physical level: The lowest level of abstraction describes how data are stored. 2. Logical level: The next higher level of abstraction, describes what data are stored in database and what relationship among those data. 3. View level: The highest level of abstraction describes only part of entire database. -
DATABASES for ARTIFICIAL INTELLIGENCE Srishty Choudhary, Uday Patkar
Srishty Choudhary et al, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.3, March- 2016, pg. 67-70 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 5.258 IJCSMC, Vol. 5, Issue. 3, March 2016, pg.67 – 70 DATABASES FOR ARTIFICIAL INTELLIGENCE Srishty Choudhary, Uday Patkar BVCOEL, INDIA BVCOEL, INDIA [email protected] [email protected] Abstract- The basic motto behind implementing artificial intelligence is to create expert systems and to implement human intelligence in machines. An intelligent robot is a machine able to extract information from its environment. One can study this to know more about themselves and how data are stored and which system is used here. Keywords: - AI (Artificial intelligence), RDMS (Relational database management system), DBMS (Database management system), IDMS (Intelligent database management system), HIPM (Human information processing model), DPM (Data processing model). I. INTRODUCTION Artificial intelligence is a branch of science or rather advanced science which deals with how intelligence can be implemented. But after implementing next important aspect that should be made confront is how data which is generated will be stored and for that we need databases. Database is basically a pool of data which stores data in both sequential and non-sequential format. II. THEORETICAL BACKGROUND Data is collection of bits and bytes of information and a database is an organised collection of data. On the broader side a Database management system (DBMS) is a computer software application that interacts with the user, other applications, and the database itself to capture and analyse data. -
Nosql and TRADITIONAL DATABASE INTEGRATION: CASE STUDY PROJECT BDIC-DM
Ciências Exatas e da Terra - Ciência da Computação - Sistemas de Computação - Arquitetura de Sistemas de Computação (Ciência da Computação) NoSQL AND TRADITIONAL DATABASE INTEGRATION: CASE STUDY PROJECT BDIC-DM Ramiro Tadeu Wisnieski 1 Data de entrega dos originais à redação em: 12/08/2016 e recebido para diagramação em: 20/04/2018 This article describes the procedures involved in integrating a NoSQL database with a traditional one. These procedures were implemented in an academic project context of agile development, entitled Big Data, Internet of Things and Mobile Devices (BDIC-DM in Portuguese). This project was conceived in the first half of 2015 at Aeronautics Institute of Technology (ITA). As a requirement for the effectiveness of the mission, the implementation of an e-commerce system to manage transactions involving large volumes of data (Big Data), a number of different technologies were used. Among these tools the ones that stand out are those involving the generation, storage and consumption of large volumes of data. As a starting point for some features of Real Time Transactional Processing (OLTP - Online Transactional Processing) system, the traditional Database Management System (DBMS) MySQL was used along with the DBMS NoSQL Cassandra to store the portal purchase data. As for the batch data analysis (OLAP - Online Analytical Processing) Apache Hadoop Ecosystem was used. An infrastructure based on the Apache Sqoop tool allowed the export of data from traditional relational database to the HDFS(Hadoop File System). Keywords: Big Data. Cassandra. Iintegration. MySQL. NoSQL. I. INTRODUCTION system makes use of relationships between different With the recent rise of Big Data worldwide, it entities, attributes and records. -
Cs6302 Database Management System Two Marks Unit I Introduction to Dbms
CS6302 DATABASE MANAGEMENT SYSTEM TWO MARKS UNIT I INTRODUCTION TO DBMS 1. Who is a DBA? What are the responsibilities of a DBA? April/May-2011 A database administrator (short form DBA) is a person responsible for the design, implementation, maintenance and repair of an organization's database. They are also known by the titles Database Coordinator or Database Programmer, and is closely related to the Database Analyst, Database Modeller, Programmer Analyst, and Systems Manager. The role includes the development and design of database strategies, monitoring and improving database performance and capacity, and planning for future expansion requirements. They may also plan, co-ordinate and implement security measures to safeguard the database 2. What is a data model? List the types of data model used. April/May-2011 A database model is the theoretical foundation of a database and fundamentally determines in which manner data can be stored, organized, and manipulated in a database system. It thereby defines the infrastructure offered by a particular database system. The most popular example of a database model is the relational model. types of data model used Hierarchical model Network model Relational model Entity-relationship Object-relational model Object model 3.Define database management system. Database management system (DBMS) is a collection of interrelated data and a set of programs to access those data. 4.What is data base management system? A database management system (DBMS) is a software package with computer programs that control the creation, maintenance, and the use of a database. It allows organizations to conveniently develop databases for various applications by database administrators (DBAs) and other specialists. -
444 Difference Between Sql and Nosql Databases
International Journal of Management, IT & Engineering Vol. 8 Issue 6, June 2018, ISSN: 2249-0558 Impact Factor: 7.119 Journal Homepage: http://www.ijmra.us, Email: [email protected] Double-Blind Peer Reviewed Refereed Open Access International Journal - Included in the International Serial Directories Indexed & Listed at: Ulrich's Periodicals Directory ©, U.S.A., Open J-Gage as well as in Cabell’s Directories of Publishing Opportunities, U.S.A Difference between SQL and NoSQL Databases Kalyan Sudhakar* Abstract This article explores the various differences between SQL and NoSQL databases. It begins by giving brief descriptions of both SQL and NoSQL databases and then discussing the various pros and cos of each database type. This article also examines the applicability differences between the two database types. Structured Query Language (SQL) refers to a domain-specific or standardized programming language used by database designers in designing and managing relational SQL databases or controlling data stored in RDSMS (relational database management system). The scope of SQL database encompasses data query, data definition (creation and modification of schema), data manipulation (inserting, deleting, and updating), as well as control of data access. NoSQL databases are non-relational and can exist together with relational databases. NoSQL databases are most suitable for use in applications that involve large amounts of data, and the data can either be unstructured, structured, or semi- structured. SQL databases have been the most widely used databases in the world over the years. However, it is the requirements that drive data models, which in turns, influence the choice between SQL and NoSQL databases.