Chapter- 7 DATABASE NORMALIZATION Keys Types of Key
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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.( -
Normalized Form Snowflake Schema
Normalized Form Snowflake Schema Half-pound and unascertainable Wood never rhubarbs confoundedly when Filbert snore his sloop. Vertebrate or leewardtongue-in-cheek, after Hazel Lennie compartmentalized never shreddings transcendentally, any misreckonings! quite Crystalloiddiverted. Euclid grabbles no yorks adhered The star schemas in this does not have all revenue for this When done use When doing table contains less sensible of rows Snowflake Normalizationde-normalization Dimension tables are in normalized form the fact. Difference between Star Schema & Snow Flake Schema. The major difference between the snowflake and star schema models is slot the dimension tables of the snowflake model may want kept in normalized form to. Typically most of carbon fact tables in this star schema are in the third normal form while dimensional tables are de-normalized second normal. A relation is danger to pause in First Normal Form should each attribute increase the. The model is lazy in single third normal form 1141 Options to Normalize Assume that too are 500000 product dimension rows These products fall under 500. Hottest 'snowflake-schema' Answers Stack Overflow. Learn together is Star Schema Snowflake Schema And the Difference. For step three within the warehouses we tested Redshift Snowflake and Bigquery. On whose other hand snowflake schema is in normalized form. The CWM repository schema is a standalone product that other products can shareeach product owns only. The main difference between in two is normalization. Families of normalized form snowflake schema snowflake. Star and Snowflake Schema in Data line with Examples. Is spread the dimension tables in the snowflake schema are normalized. Like price weight speed and quantitiesie data execute a numerical format. -
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. -
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. -
Boyce-Codd Normal Forms Lecture 10 Sections 15.1 - 15.4
Boyce-Codd Normal Forms Lecture 10 Sections 15.1 - 15.4 Robb T. Koether Hampden-Sydney College Wed, Feb 6, 2013 Robb T. Koether (Hampden-Sydney College) Boyce-Codd Normal Forms Wed, Feb 6, 2013 1 / 15 1 Third Normal Form 2 Boyce-Codd Normal Form 3 Assignment Robb T. Koether (Hampden-Sydney College) Boyce-Codd Normal Forms Wed, Feb 6, 2013 2 / 15 Outline 1 Third Normal Form 2 Boyce-Codd Normal Form 3 Assignment Robb T. Koether (Hampden-Sydney College) Boyce-Codd Normal Forms Wed, Feb 6, 2013 3 / 15 Third Normal Form Definition (Transitive Dependence) A set of attributes Z is transitively dependent on a set of attributes X if there exists a set of attributes Y such that X ! Y and Y ! Z. Definition (Third Normal Form) A relation R is in third normal form (3NF) if it is in 2NF and there is no nonprime attribute of R that is transitively dependent on any key of R. 3NF is violated if there is a nonprime attribute A that depends on something less than a key. Robb T. Koether (Hampden-Sydney College) Boyce-Codd Normal Forms Wed, Feb 6, 2013 4 / 15 Example Example order_no cust_no cust_name 222-1 3333 Joe Smith 444-2 4444 Sue Taylor 555-1 3333 Joe Smith 777-2 7777 Bob Sponge 888-3 4444 Sue Taylor Table 3 Table 3 is in 2NF, but it is not in 3NF because [order_no] ! [cust_no] ! [cust_name]: Robb T. Koether (Hampden-Sydney College) Boyce-Codd Normal Forms Wed, Feb 6, 2013 5 / 15 3NF Normalization To put a relation into 3NF, for each set of transitive function dependencies X ! Y ! Z , make two tables, one for X ! Y and another for Y ! Z . -
Database Design Solutions
spine=1.10" Wrox Programmer to ProgrammerTM Wrox Programmer to ProgrammerTM Beginning Stephens Database Design Solutions Databases play a critical role in the business operations of most organizations; they’re the central repository for critical information on products, customers, Beginning suppliers, sales, and a host of other essential information. It’s no wonder that Solutions Database Design the majority of all business computing involves database applications. With so much at stake, you’d expect most IT professionals would have a firm understanding of good database design. But in fact most learn through a painful process of trial and error, with predictably poor results. This book provides readers with proven methods and tools for designing efficient, reliable, and secure databases. Author Rod Stephens explains how a database should be organized to ensure data integrity without sacrificing performance. He shares procedures for designing robust, flexible, and secure databases that provide a solid foundation for all of your database applications. The methods and techniques in this book can be applied to any database environment, including Oracle®, Microsoft Access®, SQL Server®, and MySQL®. You’ll learn the basics of good database design and ultimately discover how to design a real-world database. What you will learn from this book ● How to identify database requirements that meet users’ needs ● Ways to build data models using a variety of modeling techniques, including Beginning entity-relational models, user-interface models, and -
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. -
Adequacy of Decompositions of Relational Databases*9+
JOURNAL OF COMPUTER AND SYSTEM SCIENCES 21, 368-379 (1980) Adequacy of Decompositions of Relational Databases*9+ DAVID MAIER State University of New York, Stony Brook, New York 11794 0. MENDELZON IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 FEREIDOON SADRI Princeton University, Princeton, New Jersey 08540 AND JEFFREY D. ULLMAN Stanford University, Stanford, California 94305 Received August 6, 1979; revised July 16, 1980 We consider conditions that have appeared in the literature with the purpose of defining a “good” decomposition of a relation scheme. We show that these notions are equivalent in the case that all constraints in the database are functional dependencies. This result solves an open problem of Rissanen. However, for arbitrary constraints the notions are shown to differ. I. BASIC DEFINITIONS We assume the reader is familiar with the relational model of data as expounded by Codd [ 111, in which data are represented by tables called relations. Rows of the tables are tuples, and the columns are named by attributes. The notation used in this paper is that found in Ullman [23]. A frequent viewpoint is that the “real world” is modeled by a universal set of attributes R and constraints on the set of relations that can be the “current” relation for scheme R (see Beeri et al. [4], Aho et al. [ 11, and Beeri et al. [7]). The database scheme representing the real world is a collection of (nondisjoint) subsets of the * Work partially supported by NSF Grant MCS-76-15255. D. Maier and A. 0. Mendelzon were also supported by IBM fellowships while at Princeton University, and F. -
Fundamentals of Database Systems [Normalization – II]
Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form Fundamentals of Database Systems [Normalization { II] Malay Bhattacharyya Assistant Professor Machine Intelligence Unit Indian Statistical Institute, Kolkata October, 2019 Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form 1 First Normal Form 2 Second Normal Form 3 Third Normal Form 4 Boyce-Codd Normal Form Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form First normal form The domain (or value set) of an attribute defines the set of values it might contain. A domain is atomic if elements of the domain are considered to be indivisible units. Company Make Company Make Maruti WagonR, Ertiga Maruti WagonR, Ertiga Honda City Honda City Tesla RAV4 Tesla, Toyota RAV4 Toyota RAV4 BMW X1 BMW X1 Only Company has atomic domain None of the attributes have atomic domains Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form First normal form Definition (First normal form (1NF)) A relational schema R is in 1NF iff the domains of all attributes in R are atomic. The advantages of 1NF are as follows: It eliminates redundancy It eliminates repeating groups. Note: In practice, 1NF includes a few more practical constraints like each attribute must be unique, no tuples are duplicated, and no columns are duplicated. Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form First normal form The following relation is not in 1NF because the attribute Model is not atomic. Company Country Make Model Distributor Maruti India WagonR LXI, VXI Carwala Maruti India WagonR LXI Bhalla Maruti India Ertiga VXI Bhalla Honda Japan City SV Bhalla Tesla USA RAV4 EV CarTrade Toyota Japan RAV4 EV CarTrade BMW Germany X1 Expedition CarTrade We can convert this relation into 1NF in two ways!!! Outline First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form First normal form Approach 1: Break the tuples containing non-atomic values into multiple tuples.