Relational Database Management Systems And
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Database Concepts 7Th Edition
Database Concepts 7th Edition David M. Kroenke • David J. Auer Online Appendix E SQL Views, SQL/PSM and Importing Data Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Appendix E — 10 9 8 7 6 5 4 3 2 1 E-2 Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E Appendix Objectives • To understand the reasons for using SQL views • To use SQL statements to create and query SQL views • To understand SQL/Persistent Stored Modules (SQL/PSM) • To create and use SQL user-defined functions • To import Microsoft Excel worksheet data into a database What is the Purpose of this Appendix? In Chapter 3, we discussed SQL in depth. We discussed two basic categories of SQL statements: data definition language (DDL) statements, which are used for creating tables, relationships, and other structures, and data manipulation language (DML) statements, which are used for querying and modifying data. In this appendix, which should be studied immediately after Chapter 3, we: • Describe and illustrate SQL views, which extend the DML capabilities of SQL. • Describe and illustrate SQL Persistent Stored Modules (SQL/PSM), and create user-defined functions. • Describe and use DBMS data import techniques to import Microsoft Excel worksheet data into a database. E-3 Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E Creating SQL Views An SQL view is a virtual table that is constructed from other tables or views. -
Database Systems Administrator FLSA: Exempt
CLOVIS UNIFIED SCHOOL DISTRICT POSITION DESCRIPTION Position: Database Systems Administrator FLSA: Exempt Department/Site: Technology Services Salary Grade: 127 Reports to/Evaluated by: Chief Technology Officer Salary Schedule: Classified Management SUMMARY Gathers requirements and provisions servers to meet the district’s need for database storage. Installs and configures SQL Server according to the specifications of outside software vendors and/or the development group. Designs and executes a security scheme to assure safety of confidential data. Implements and manages a backup and disaster recovery plan. Monitors the health and performance of database servers and database applications. Troubleshoots database application performance issues. Automates monitoring and maintenance tasks. Maintains service pack deployment and upgrades servers in consultation with the developer group and outside vendors. Deploys and schedules SQL Server Agent tasks. Implements and manages replication topologies. Designs and deploys datamarts under the supervision of the developer group. Deploys and manages cubes for SSAS implementations. DISTINGUISHING CAREER FEATURES The Database Systems Administrator is a senior level analyst position requiring specialized education and training in the field of study typically resulting in a degree. Advancement to this position would require competency in the design and administration of relational databases designated for business, enterprise, and student information. Advancement from this position is limited to supervisory management positions. ESSENTIAL DUTIES AND RESPONSIBILITIES Implements, maintains and administers all district supported versions of Microsoft SQL as well as other DBMS as needed. Responsible for database capacity planning and involvement in server capacity planning. Responsible for verification of backups and restoration of production and test databases. Designs, implements and maintains a disaster recovery plan for critical data resources. -
The Relational Data Model and Relational Database Constraints
chapter 33 The Relational Data Model and Relational Database Constraints his chapter opens Part 2 of the book, which covers Trelational databases. The relational data model was first introduced by Ted Codd of IBM Research in 1970 in a classic paper (Codd 1970), and it attracted immediate attention due to its simplicity and mathematical foundation. The model uses the concept of a mathematical relation—which looks somewhat like a table of values—as its basic building block, and has its theoretical basis in set theory and first-order predicate logic. In this chapter we discuss the basic characteristics of the model and its constraints. The first commercial implementations of the relational model became available in the early 1980s, such as the SQL/DS system on the MVS operating system by IBM and the Oracle DBMS. Since then, the model has been implemented in a large num- ber of commercial systems. Current popular relational DBMSs (RDBMSs) include DB2 and Informix Dynamic Server (from IBM), Oracle and Rdb (from Oracle), Sybase DBMS (from Sybase) and SQLServer and Access (from Microsoft). In addi- tion, several open source systems, such as MySQL and PostgreSQL, are available. Because of the importance of the relational model, all of Part 2 is devoted to this model and some of the languages associated with it. In Chapters 4 and 5, we describe the SQL query language, which is the standard for commercial relational DBMSs. Chapter 6 covers the operations of the relational algebra and introduces the relational calculus—these are two formal languages associated with the relational model. -
Scalable Computation of Acyclic Joins
Scalable Computation of Acyclic Joins (Extended Abstract) Anna Pagh Rasmus Pagh [email protected] [email protected] IT University of Copenhagen Rued Langgaards Vej 7, 2300 København S Denmark ABSTRACT 1. INTRODUCTION The join operation of relational algebra is a cornerstone of The relational model and relational algebra, due to Edgar relational database systems. Computing the join of several F. Codd [3] underlies the majority of today’s database man- relations is NP-hard in general, whereas special (and typi- agement systems. Essential to the ability to express queries cal) cases are tractable. This paper considers joins having in relational algebra is the natural join operation, and its an acyclic join graph, for which current methods initially variants. In a typical relational algebra expression there will apply a full reducer to efficiently eliminate tuples that will be a number of joins. Determining how to compute these not contribute to the result of the join. From a worst-case joins in a database management system is at the heart of perspective, previous algorithms for computing an acyclic query optimization, a long-standing and active field of de- join of k fully reduced relations, occupying a total of n ≥ k velopment in academic and industrial database research. A blocks on disk, use Ω((n + z)k) I/Os, where z is the size of very challenging case, and the topic of most database re- the join result in blocks. search, is when data is so large that it needs to reside on In this paper we show how to compute the join in a time secondary memory. -
SQL Vs Nosql: a Performance Comparison
SQL vs NoSQL: A Performance Comparison Ruihan Wang Zongyan Yang University of Rochester University of Rochester [email protected] [email protected] Abstract 2. ACID Properties and CAP Theorem We always hear some statements like ‘SQL is outdated’, 2.1. ACID Properties ‘This is the world of NoSQL’, ‘SQL is still used a lot by We need to refer the ACID properties[12]: most of companies.’ Which one is accurate? Has NoSQL completely replace SQL? Or is NoSQL just a hype? SQL Atomicity (Structured Query Language) is a standard query language A transaction is an atomic unit of processing; it should for relational database management system. The most popu- either be performed in its entirety or not performed at lar types of RDBMS(Relational Database Management Sys- all. tems) like Oracle, MySQL, SQL Server, uses SQL as their Consistency preservation standard database query language.[3] NoSQL means Not A transaction should be consistency preserving, meaning Only SQL, which is a collection of non-relational data stor- that if it is completely executed from beginning to end age systems. The important character of NoSQL is that it re- without interference from other transactions, it should laxes one or more of the ACID properties for a better perfor- take the database from one consistent state to another. mance in desired fields. Some of the NOSQL databases most Isolation companies using are Cassandra, CouchDB, Hadoop Hbase, A transaction should appear as though it is being exe- MongoDB. In this paper, we’ll outline the general differences cuted in iso- lation from other transactions, even though between the SQL and NoSQL, discuss if Relational Database many transactions are execut- ing concurrently. -
Applying the ETL Process to Blockchain Data. Prospect and Findings
information Article Applying the ETL Process to Blockchain Data. Prospect and Findings Roberta Galici 1, Laura Ordile 1, Michele Marchesi 1 , Andrea Pinna 2,* and Roberto Tonelli 1 1 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy; [email protected] (R.G.); [email protected] (L.O.); [email protected] (M.M.); [email protected] (R.T.) 2 Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Piazza D’Armi, 09100 Cagliari, Italy * Correspondence: [email protected] Received: 7 March 2020; Accepted: 7 April 2020; Published: 10 April 2020 Abstract: We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. -
“A Relational Model of Data for Large Shared Data Banks”
“A RELATIONAL MODEL OF DATA FOR LARGE SHARED DATA BANKS” Through the internet, I find more information about Edgar F. Codd. He is a mathematician and computer scientist who laid the theoretical foundation for relational databases--the standard method by which information is organized in and retrieved from computers. In 1981, he received the A. M. Turing Award, the highest honor in the computer science field for his fundamental and continuing contributions to the theory and practice of database management systems. This paper is concerned with the application of elementary relation theory to systems which provide shared access to large banks of formatted data. It is divided into two sections. In section 1, a relational model of data is proposed as a basis for protecting users of formatted data systems from the potentially disruptive changes in data representation caused by growth in the data bank and changes in traffic. A normal form for the time-varying collection of relationships is introduced. In Section 2, certain operations on relations are discussed and applied to the problems of redundancy and consistency in the user's model. Relational model provides a means of describing data with its natural structure only--that is, without superimposing any additional structure for machine representation purposes. Accordingly, it provides a basis for a high level data language which will yield maximal independence between programs on the one hand and machine representation and organization of data on the other. A further advantage of the relational view is that it forms a sound basis for treating derivability, redundancy, and consistency of relations. -
Reactive Relational Database Connectivity
R2DBC - Reactive Relational Database Connectivity Ben Hale<[email protected]>, Mark Paluch <[email protected]>, Greg Turnquist <[email protected]>, Jay Bryant <[email protected]> Version 0.8.0.RC1, 2019-09-26 © 2017-2019 The original authors. Copies of this document may be made for your own use and for distribution to others, provided that you do not charge any fee for such copies and further provided that each copy contains this Copyright Notice, whether distributed in print or electronically. 1 Preface License Specification: R2DBC - Reactive Relational Database Connectivity Version: 0.8.0.RC1 Status: Draft Specification Lead: Pivotal Software, Inc. Release: 2019-09-26 Copyright 2017-2019 the original author or authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Foreword R2DBC brings a reactive programming API to relational data stores. The Introduction contains more details about its origins and explains its goals. This document describes the first and initial generation of R2DBC. Organization of this document This document is organized into the following parts: • Introduction • Goals • Compliance • Overview • Connections • Transactions 2 • Statements • Batches • Results • Column and Row Metadata • Exceptions • Data Types • Extensions 3 Chapter 1. -
Join , Sub Queries and Set Operators Obtaining Data from Multiple Tables
Join , Sub queries and set operators Obtaining Data from Multiple Tables EMPLOYEES DEPARTMENTS … … Cartesian Products – A Cartesian product is formed when: • A join condition is omitted • A join condition is invalid • All rows in the first table are joined to all rows in the second table – To avoid a Cartesian product, always include a valid join condition in a WHERE clause. Generating a Cartesian Product EMPLOYEES (20 rows) DEPARTMENTS (8 rows) … Cartesian product: 20 x 8 = 160 rows … Types of Oracle-Proprietary Joins – Equijoin – Nonequijoin – Outer join – Self-join Joining Tables Using Oracle Syntax • Use a join to query data from more than one table: SELECT table1.column, table2.column FROM table1, table2 WHERE table1.column1 = table2.column2; – Write the join condition in the WHERE clause. – Prefix the column name with the table name when the same column name appears in more than one table. Qualifying Ambiguous Column Names – Use table prefixes to qualify column names that are in multiple tables. – Use table prefixes to improve performance. – Instead of full table name prefixes, use table aliases. – Table aliases give a table a shorter name. • Keeps SQL code smaller, uses less memory – Use column aliases to distinguish columns that have identical names, but reside in different tables. Equijoins EMPLOYEES DEPARTMENTS Primary key … Foreign key Retrieving Records with Equijoins SELECT e.employee_id, e.last_name, e.department_id, d.department_id, d.location_id FROM employees e, departments d WHERE e.department_id = d.department_id; … Retrieving Records with Equijoins: Example SELECT d.department_id, d.department_name, d.location_id, l.city FROM departments d, locations l WHERE d.location_id = l.location_id; Additional Search Conditions Using the AND Operator SELECT d.department_id, d.department_name, l.city FROM departments d, locations l WHERE d.location_id = l.location_id AND d.department_id IN (20, 50); Joining More than Two Tables EMPLOYEES DEPARTMENTS LOCATIONS … • To join n tables together, you need a minimum of n–1 • join conditions. -
SQL: Programming Introduction to Databases Compsci 316 Fall 2019 2 Announcements (Mon., Sep
SQL: Programming Introduction to Databases CompSci 316 Fall 2019 2 Announcements (Mon., Sep. 30) • Please fill out the RATest survey (1 free pt on midterm) • Gradiance SQL Recursion exercise assigned • Homework 2 + Gradiance SQL Constraints due tonight! • Wednesday • Midterm in class • Open-book, open-notes • Same format as sample midterm (posted in Sakai) • Gradiance SQL Triggers/Views due • After fall break • Project milestone 1 due; remember members.txt • Gradiance SQL Recursion due 3 Motivation • Pros and cons of SQL • Very high-level, possible to optimize • Not intended for general-purpose computation • Solutions • Augment SQL with constructs from general-purpose programming languages • E.g.: SQL/PSM • Use SQL together with general-purpose programming languages: many possibilities • Through an API, e.g., Python psycopg2 • Embedded SQL, e.g., in C • Automatic obJect-relational mapping, e.g.: Python SQLAlchemy • Extending programming languages with SQL-like constructs, e.g.: LINQ 4 An “impedance mismatch” • SQL operates on a set of records at a time • Typical low-level general-purpose programming languages operate on one record at a time • Less of an issue for functional programming languages FSolution: cursor • Open (a result table): position the cursor before the first row • Get next: move the cursor to the next row and return that row; raise a flag if there is no such row • Close: clean up and release DBMS resources FFound in virtually every database language/API • With slightly different syntaxes FSome support more positioning and movement options, modification at the current position, etc. 5 Augmenting SQL: SQL/PSM • PSM = Persistent Stored Modules • CREATE PROCEDURE proc_name(param_decls) local_decls proc_body; • CREATE FUNCTION func_name(param_decls) RETURNS return_type local_decls func_body; • CALL proc_name(params); • Inside procedure body: SET variable = CALL func_name(params); 6 SQL/PSM example CREATE FUNCTION SetMaxPop(IN newMaxPop FLOAT) RETURNS INT -- Enforce newMaxPop; return # rows modified. -
Examples of Relational Database Model
Examples Of Relational Database Model Discerning Ajai never dally so hardheadedly or die-cast any macaronics warily. Flutiest Noble necessitating: he syllabicating his magnificoes inexplicably and deprecatorily. Taliped Ram zeroes, his decerebration revving strangle verbally. Several products exist to support such databases. Simply click the image would make changes online. Note that a constraint implies an index on the same label and property. So why should we use a database? Gain new system that data typing sql programs operate, documents can write business logic in relational database examples of organization might like i have all elements which is. In sql and domains like spreadsheet, difference and gathering data? DRDA enables network connected relational databases to cooperate to fulfill SQL requests. So what is our use case? And because these databases are expensive, you tend to put everything in there. Individual tables to? It will take us a couple of weeks going over these skills and concepts. When there is a one to one relationship, one of two actions typically occur. In database examples of relational model was one. Graph models and graph queries are two sides of pain same coin. Some research data stores replicate a given blob across multiple server nodes, which enables fast parallel reads. Why relational structure of relational schema? Each model database model? But what if item prices were negotiated on each order or there were special promotions? Other data on database relational databases went from. The domain is better user not relational model support multiple bills in other. There is called relation which columns? In english as a model developed procedures for example, music collection of models are generic visual basic skill every tuple, it natural join. -
Relational Database Fundamentals
05_04652x ch01.qxp 7/10/06 1:45 PM Page 7 Chapter 1 Relational Database Fundamentals In This Chapter ᮣ Organizing information ᮣ Defining database ᮣ Defining DBMS ᮣ Comparing database models ᮣ Defining relational database ᮣ Considering the challenges of database design QL (pronounced ess-que-ell, not see’qwl) is an industry-standard language Sspecifically designed to enable people to create databases, add new data to databases, maintain the data, and retrieve selected parts of the data. Various kinds of databases exist, each adhering to a different conceptual model. SQL was originally developed to operate on data in databases that follow the relational model. Recently, the international SQL standard has incorporated part of the object model, resulting in hybrid structures called object-relational databases. In this chapter, I discuss data storage, devote a section to how the relational model compares with other major models, and provide a look at the important features of relational databases. Before I talk about SQL, however, I need to nail down what I mean by the term database. Its meaning has changed as computers have changed the way people record and maintain information. COPYRIGHTED MATERIAL Keeping Track of Things Today, people use computers to perform many tasks formerly done with other tools. Computers have replaced typewriters for creating and modifying documents. They’ve surpassed electromechanical calculators as the best way to do math. They’ve also replaced millions of pieces of paper, file folders, and file cabinets as the principal storage medium for important information. Compared to those old tools, of course, computers do much more, much faster — and with greater accuracy.