Relational Database: Definitions Ex: Instance of Students Relation • Relational Database: a Set of Relations
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Foreign(Key(Constraints(
Foreign(Key(Constraints( ! Foreign(key:(a(rule(that(a(value(appearing(in(one(rela3on(must( appear(in(the(key(component(of(another(rela3on.( – aka(values(for(certain(a9ributes(must("make(sense."( – Po9er(example:(Every(professor(who(is(listed(as(teaching(a(course(in(the( Courses(rela3on(must(have(an(entry(in(the(Profs(rela3on.( ! How(do(we(express(such(constraints(in(rela3onal(algebra?( ! Consider(the(rela3ons(Courses(crn,(year,(name,(proflast,(…)(and( Profs(last,(first).( ! We(want(to(require(that(every(nonLNULL(value(of(proflast(in( Courses(must(be(a(valid(professor(last(name(in(Profs.( ! RA((πProfLast(Courses)((((((((⊆ π"last(Profs)( 23( Foreign(Key(Constraints(in(SQL( ! We(want(to(require(that(every(nonLNULL(value(of(proflast(in( Courses(must(be(a(valid(professor(last(name(in(Profs.( ! In(Courses,(declare(proflast(to(be(a(foreign(key.( ! CREATE&TABLE&Courses&(& &&&proflast&VARCHAR(8)&REFERENCES&Profs(last),...);& ! CREATE&TABLE&Courses&(& &&&proflast&VARCHAR(8),&...,&& &&&FOREIGN&KEY&proflast&REFERENCES&Profs(last));& 24( Requirements(for(FOREIGN(KEYs( ! If(a(rela3on(R(declares(that(some(of(its(a9ributes(refer( to(foreign(keys(in(another(rela3on(S,(then(these( a9ributes(must(be(declared(UNIQUE(or(PRIMARY(KEY(in( S.( ! Values(of(the(foreign(key(in(R(must(appear(in(the( referenced(a9ributes(of(some(tuple(in(S.( 25( Enforcing(Referen>al(Integrity( ! Three(policies(for(maintaining(referen3al(integrity.( ! Default(policy:(reject(viola3ng(modifica3ons.( ! Cascade(policy:(mimic(changes(to(the(referenced( a9ributes(at(the(foreign(key.( ! SetLNULL(policy:(set(appropriate(a9ributes(to(NULL.( -
ACS-3902 Ron Mcfadyen Slides Are Based on Chapter 5 (7Th Edition)
ACS-3902 Ron McFadyen Slides are based on chapter 5 (7th edition) (chapter 3 in 6th edition) ACS-3902 1 The Relational Data Model and Relational Database Constraints • Relational model – Ted Codd (IBM) 1970 – First commercial implementations available in early 1980s – Widely used ACS-3902 2 Relational Model Concepts • Database is a collection of relations • Implementation of relation: table comprising rows and columns • In practice a table/relation represents an entity type or relationship type (entity-relationship model … later) • At intersection of a row and column in a table there is a simple value • Row • Represents a collection of related data values • Formally called a tuple • Column names • Columns may be referred to as fields, or, formally as attributes • Values in a column are drawn from a domain of values associated with the column/field/attribute ACS-3902 3 Relational Model Concepts 7th edition Figure 5.1 ACS-3902 4 Domains • Domain – Atomic • A domain is a collection of values where each value is indivisible • Not meaningful to decompose further – Specifying a domain • Name, data type, rules – Examples • domain of department codes for UW is a list: {“ACS”, “MATH”, “ENGL”, “HIST”, etc} • domain of gender values for UW is the list (“male”, “female”) – Cardinality: number of values in a domain – Database implementation & support vary ACS-3902 5 Domain example - PostgreSQL CREATE DOMAIN posint AS integer CHECK (VALUE > 0); CREATE TABLE mytable (id posint); INSERT INTO mytable VALUES(1); -- works INSERT INTO mytable VALUES(-1); -- fails https://www.postgresql.org/docs/current/domains.html ACS-3902 6 Domain example - PostgreSQL CREATE DOMAIN domain_code_type AS character varying NOT NULL CONSTRAINT domain_code_type_check CHECK (VALUE IN ('ApprovedByAdmin', 'Unapproved', 'ApprovedByEmail')); CREATE TABLE codes__domain ( code_id integer NOT NULL, code_type domain_code_type NOT NULL, CONSTRAINT codes_domain_pk PRIMARY KEY (code_id) ) ACS-3902 7 Relation • Relation schema R – Name R and a list of attributes: • Denoted by R (A1, A2, ...,An) • E.g. -
Referential Integrity in Sqlite
CS 564: Database Management Systems University of Wisconsin - Madison, Fall 2017 Referential Integrity in SQLite Declaring Referential Integrity (Foreign Key) Constraints Foreign key constraints are used to check referential integrity between tables in a database. Consider, for example, the following two tables: create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR ); We can enforce the constraint that a Student’s residence actually exists by making Student.residence a foreign key that refers to Residence.name. SQLite lets you specify this relationship in several different ways: create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR, FOREIGNKEY(residence) REFERENCES Residence(name) ); or create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR REFERENCES Residence(name) ); or create table Residence ( nameVARCHARPRIMARY KEY, 1 capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR REFERENCES Residence-- Implicitly references the primary key of the Residence table. ); All three forms are valid syntax for specifying the same constraint. Constraint Enforcement There are a number of important things about how referential integrity and foreign keys are handled in SQLite: • The attribute(s) referenced by a foreign key constraint (i.e. Residence.name in the example above) must be declared UNIQUE or as the PRIMARY KEY within their table, but this requirement is checked at run-time, not when constraints are declared. For example, if Residence.name had not been declared as the PRIMARY KEY of its table (or as UNIQUE), the FOREIGN KEY declarations above would still be permitted, but inserting into the Student table would always yield an error. -
Not ACID, Not BASE, but SALT a Transaction Processing Perspective on Blockchains
Not ACID, not BASE, but SALT A Transaction Processing Perspective on Blockchains Stefan Tai, Jacob Eberhardt and Markus Klems Information Systems Engineering, Technische Universitat¨ Berlin fst, je, [email protected] Keywords: SALT, blockchain, decentralized, ACID, BASE, transaction processing Abstract: Traditional ACID transactions, typically supported by relational database management systems, emphasize database consistency. BASE provides a model that trades some consistency for availability, and is typically favored by cloud systems and NoSQL data stores. With the increasing popularity of blockchain technology, another alternative to both ACID and BASE is introduced: SALT. In this keynote paper, we present SALT as a model to explain blockchains and their use in application architecture. We take both, a transaction and a transaction processing systems perspective on the SALT model. From a transactions perspective, SALT is about Sequential, Agreed-on, Ledgered, and Tamper-resistant transaction processing. From a systems perspec- tive, SALT is about decentralized transaction processing systems being Symmetric, Admin-free, Ledgered and Time-consensual. We discuss the importance of these dual perspectives, both, when comparing SALT with ACID and BASE, and when engineering blockchain-based applications. We expect the next-generation of decentralized transactional applications to leverage combinations of all three transaction models. 1 INTRODUCTION against. Using the admittedly contrived acronym of SALT, we characterize blockchain-based transactions There is a common belief that blockchains have the – from a transactions perspective – as Sequential, potential to fundamentally disrupt entire industries. Agreed, Ledgered, and Tamper-resistant, and – from Whether we are talking about financial services, the a systems perspective – as Symmetric, Admin-free, sharing economy, the Internet of Things, or future en- Ledgered, and Time-consensual. -
(DDL) Reference Manual
Data Definition Language (DDL) Reference Manual Abstract This publication describes the DDL language syntax and the DDL dictionary database. The audience includes application programmers and database administrators. Product Version DDL D40 DDL H01 Supported Release Version Updates (RVUs) This publication supports J06.03 and all subsequent J-series RVUs, H06.03 and all subsequent H-series RVUs, and G06.26 and all subsequent G-series RVUs, until otherwise indicated by its replacement publications. Part Number Published 529431-003 May 2010 Document History Part Number Product Version Published 529431-002 DDL D40, DDL H01 July 2005 529431-003 DDL D40, DDL H01 May 2010 Legal Notices Copyright 2010 Hewlett-Packard Development Company L.P. Confidential computer software. Valid license from HP required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein. Export of the information contained in this publication may require authorization from the U.S. Department of Commerce. Microsoft, Windows, and Windows NT are U.S. registered trademarks of Microsoft Corporation. Intel, Itanium, Pentium, and Celeron are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. -
The Unconstrained Primary Key
IBM Systems Lab Services and Training The Unconstrained Primary Key Dan Cruikshank www.ibm.com/systems/services/labservices © 2009 IBM Corporation In this presentation I build upon the concepts that were presented in my article “The Keys to the Kingdom”. I will discuss how primary and unique keys can be utilized for something other than just RI. In essence, it is about laying the foundation for data centric programming. I hope to convey that by establishing some basic rules the database developer can obtain reasonable performance. The title is an oxymoron, in essence a Primary Key is a constraint, but it is a constraint that gives the database developer more freedom to utilize an extremely powerful relational database management system, what we call DB2 for i. 1 IBM Systems Lab Services and Training Agenda Keys to the Kingdom Exploiting the Primary Key Pagination with ROW_NUMBER Column Ordering Summary 2 www.ibm.com/systems/services/labservices © 2009 IBM Corporation I will review the concepts I introduced in the article “The Keys to the Kingdom” published in the Centerfield. I think this was the inspiration for the picture. I offered a picture of me sitting on the throne, but that was rejected. I will follow this with a discussion on using the primary key as a means for creating peer or subset tables for the purpose of including or excluding rows in a result set. The ROW_NUMBER function is part of the OLAP support functions introduced in 5.4. Here I provide some examples of using ROW_NUMBER with the BETWEEN predicate in order paginate a result set. -
Keys Are, As Their Name Suggests, a Key Part of a Relational Database
The key is defined as the column or attribute of the database table. For example if a table has id, name and address as the column names then each one is known as the key for that table. We can also say that the table has 3 keys as id, name and address. The keys are also used to identify each record in the database table . Primary Key:- • Every database table should have one or more columns designated as the primary key . The value this key holds should be unique for each record in the database. For example, assume we have a table called Employees (SSN- social security No) that contains personnel information for every employee in our firm. We’ need to select an appropriate primary key that would uniquely identify each employee. Primary Key • The primary key must contain unique values, must never be null and uniquely identify each record in the table. • As an example, a student id might be a primary key in a student table, a department code in a table of all departments in an organisation. Unique Key • The UNIQUE constraint uniquely identifies each record in a database table. • Allows Null value. But only one Null value. • A table can have more than one UNIQUE Key Column[s] • A table can have multiple unique keys Differences between Primary Key and Unique Key: • Primary Key 1. A primary key cannot allow null (a primary key cannot be defined on columns that allow nulls). 2. Each table can have only one primary key. • Unique Key 1. A unique key can allow null (a unique key can be defined on columns that allow nulls.) 2. -
Relational Database Design Chapter 7
Chapter 7: Relational Database Design Chapter 7: Relational Database Design First Normal Form Pitfalls in Relational Database Design Functional Dependencies Decomposition Boyce-Codd Normal Form Third Normal Form Multivalued Dependencies and Fourth Normal Form Overall Database Design Process Database System Concepts 7.2 ©Silberschatz, Korth and Sudarshan 1 First Normal Form Domain is atomic if its elements are considered to be indivisible units + Examples of non-atomic domains: Set of names, composite attributes Identification numbers like CS101 that can be broken up into parts A relational schema R is in first normal form if the domains of all attributes of R are atomic Non-atomic values complicate storage and encourage redundant (repeated) storage of data + E.g. Set of accounts stored with each customer, and set of owners stored with each account + We assume all relations are in first normal form (revisit this in Chapter 9 on Object Relational Databases) Database System Concepts 7.3 ©Silberschatz, Korth and Sudarshan First Normal Form (Contd.) Atomicity is actually a property of how the elements of the domain are used. + E.g. Strings would normally be considered indivisible + Suppose that students are given roll numbers which are strings of the form CS0012 or EE1127 + If the first two characters are extracted to find the department, the domain of roll numbers is not atomic. + Doing so is a bad idea: leads to encoding of information in application program rather than in the database. Database System Concepts 7.4 ©Silberschatz, Korth and Sudarshan 2 Pitfalls in Relational Database Design Relational database design requires that we find a “good” collection of relation schemas. -
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. -
Pizza Parlor Point-Of-Sales System CMPS 342 Database
1 Pizza Parlor Point-Of-Sales System CMPS 342 Database Systems Chris Perry Ruben Castaneda 2 Table of Contents PHASE 1 1 Pizza Parlor: Point-Of-Sales Database........................................................................3 1.1 Description of Business......................................................................................3 1.2 Conceptual Database.........................................................................................4 2 Conceptual Database Design........................................................................................5 2.1 Entities................................................................................................................5 2.2 Relationships....................................................................................................13 2.3 Related Entities................................................................................................16 PHASE 2 3 ER-Model vs Relational Model..................................................................................17 3.1 Description.......................................................................................................17 3.2 Comparison......................................................................................................17 3.3 Conversion from E-R model to relational model.............................................17 3.4 Constraints........................................................................................................19 4 Relational Model..........................................................................................................19 -
Normalization Exercises
DATABASE DESIGN: NORMALIZATION NOTE & EXERCISES (Up to 3NF) Tables that contain redundant data can suffer from update anomalies, which can introduce inconsistencies into a database. The rules associated with the most commonly used normal forms, namely first (1NF), second (2NF), and third (3NF). The identification of various types of update anomalies such as insertion, deletion, and modification anomalies can be found when tables that break the rules of 1NF, 2NF, and 3NF and they are likely to contain redundant data and suffer from update anomalies. Normalization is a technique for producing a set of tables with desirable properties that support the requirements of a user or company. Major aim of relational database design is to group columns into tables to minimize data redundancy and reduce file storage space required by base tables. Take a look at the following example: StdSSN StdCity StdClass OfferNo OffTerm OffYear EnrGrade CourseNo CrsDesc S1 SEATTLE JUN O1 FALL 2006 3.5 C1 DB S1 SEATTLE JUN O2 FALL 2006 3.3 C2 VB S2 BOTHELL JUN O3 SPRING 2007 3.1 C3 OO S2 BOTHELL JUN O2 FALL 2006 3.4 C2 VB The insertion anomaly: Occurs when extra data beyond the desired data must be added to the database. For example, to insert a course (CourseNo), it is necessary to know a student (StdSSN) and offering (OfferNo) because the combination of StdSSN and OfferNo is the primary key. Remember that a row cannot exist with NULL values for part of its primary key. The update anomaly: Occurs when it is necessary to change multiple rows to modify ONLY a single fact. -
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’.