Database Systems Relational Algebra SL02 ◮ Attribute, Domain, Tuple, Relation, Database

Total Page:16

File Type:pdf, Size:1020Kb

Database Systems Relational Algebra SL02 ◮ Attribute, Domain, Tuple, Relation, Database Informatik f¨ur Okonomen¨ II Fall 2010 The Relational Model Database Systems Relational Algebra SL02 ◮ Attribute, domain, tuple, relation, database ◮ Instance, schema ◮ ◮ The Relational Model Key constraints, entity constraints, foreign key ◮ Basic Relational Algebra Operators: σ,π, , , ,ρ ∪ × − ◮ Additional Relational Algebra Operators: , 1, ∩ ← Inf4Oec10, SL02 1/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 2/48 M. B¨ohlen, ifi@uzh The Relational Model Relation Schema ◮ The relational model is based on the concept of a relation. ◮ A relation is a mathematical concept based on the ideas of sets. ◮ The relational model was proposed by Codd from IBM Research in ◮ R(A1, A2,..., An) is a relation schema the paper: ◮ A Relational Model for Large Shared Data Banks, Communications of ◮ R is the name of the relation. the ACM, June 1970 ◮ The above paper caused a major revolution in the field of database ◮ A1, A2,..., An are attributes management and earned Codd the coveted ACM Turing Award. ◮ Example: ◮ The strength of the relational approach comes from the formal Customer(CustName, CustStreet, CustCity) foundation provided by the theory of relations. ◮ In practice, there is a standard model based on SQL. There are several important differences between the formal model and the practical model, as we shall see. Inf4Oec10, SL02 3/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 4/48 M. B¨ohlen, ifi@uzh The Customer Relation Attribute customer CustName CustStreet CustCity ◮ Each attribute of a relation has a name Adams Spring Pittsfield ◮ The set of allowed values for each attribute is called the domain of Brooks Senator Brooklyn the attribute Curry North Rye ◮ Attribute values are required to be atomic; that is, indivisible Glenn Sad Hill Woodside ◮ The value of an attribute can be an account number, but cannot be a Green Walnut Stamford set of account numbers Hayes Main Harrison ◮ The attribute name designates the role played by a domain in a Johnson Alma Palo Alto relation: Jones Main Harrison ◮ Used to interpret the meaning of the data elements corresponding to Lindsay Park Pittsfield that attribute Smith North Rye ◮ Example: The domain Date may be used to define two attributes named “Invoice-date” and “Payment-date” with different meanings Turner Putnam Stamford Williams Nassau Princeton Inf4Oec10, SL02 5/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 6/48 M. B¨ohlen, ifi@uzh Domain Tuple ◮ A domain has a logical definition: ◮ Example: USA phone numbers are the set of 10 digit phone numbers valid in the U.S. ◮ A tuple is an ordered set (list) of values ◮ Angled brackets ... are used as notation; sometimes regular ◮ A domain also has a data-type or a format defined for it. parentheses (...) are used as well ◮ The USA phone numbers may have a format: (ddd)ddd-dddd where each d is a decimal digit. ◮ Each value is derived from an appropriate domain ◮ Dates have various formats such as year, month, date formatted as ◮ A customer tuple is a 3-tuple and would consist of three values, for yyyy-mm-dd, or as dd mm,yyyy etc. example: ◮ The special value null is a member of every domain ◮ Adams, Spring, Pittsfield ◮ The null value causes complications in the definition of many operations Inf4Oec10, SL02 7/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 8/48 M. B¨ohlen, ifi@uzh Relational Instance Example of a Relation ◮ r(R) denotes a relation r on the relation schema R ◮ Example: customer(Customer) relation name attributes ◮ A relation instance is a subset of the Cartesian product of the domains of its attributes. Thus, a relation is a set of n-tuples account (a1, a2,..., an) where each ai Di AccNr BrName Balance ∈ ◮ Formally, given sets D1, D2,..., Dn a relation r is a subset of A-101 Downtown 500 D1 D2 ... Dn A-215 Mianus 700 × × × ◮ Example: tuples A-102 Perryridge 400 A-305 Round Hill 350 D = CustName = Jones, Smith, Curry, Lindsay,... 1 { } A-201 Brighton 900 D = CustStreet = Main, North, Park,... 2 { } A-222 Redwood 700 D = CustCity = Harrison, Rye, Pittsfield,... 3 { } A-217 Brighton 750 r = (Jones, Main, Harrison), (Smith, North, Rye), { (Curry, North, Rye), (Lindsay, Park, Pittsfield) } CustName CustStreet CustCity ⊆ × × Inf4Oec10, SL02 9/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 10/48 M. B¨ohlen, ifi@uzh Characteristics of Relations Database ◮ Relations are unordered, i.e., the order of tuples is irrelevant (tuples may be stored and retrieved in an arbitrary order) ◮ A database consists of a set of relations ◮ The attributes in R(A ,..., A ) and the values in t = v ,..., v are 1 n 1 n ordered. ◮ Example: Information about an enterprise is broken up into parts, with each relation storing one part of the information account ◮ account: stores information about accounts AccNr BrName Balance ◮ customer: stores information about customers A-101 Downtown 500 ◮ depositor: information about which customer owns which account A-215 Mianus 700 ◮ Storing all information as a single relation such as A-102 Perryridge 400 ◮ bank(AccNr, Balance, CustName,...) A-305 Round Hill 350 results in A-201 Brighton 900 ◮ repetition of information: e.g.,if two customers own the same account A-222 Redwood 700 ◮ the need for null values: e.g., to represent a customer without an A-217 Brighton 750 account ◮ There exist alternative definitions of a relation where attributes in a schema and values in a tuple are not ordered. Inf4Oec10, SL02 11/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 12/48 M. B¨ohlen, ifi@uzh The Depositor Relation Checking... depositor 1. What kind of object is X = (3) in the relational model? {{ }} CuName AccNr X is a database. Hayes A-102 2. Is r = (Tom, 27, ZH), (Bob, 33, Rome, IT ) a relation? Johnson A-101 { } No. Tuples have different schemas. Johnson A-201 Jones A-217 3. Are DB1 and DB2 identical databases? Lindsay A-222 DB1= (1, 5), (2, 3) , (4, 4) {{ } { }} Smith A-215 DB2= (4, 4) , (2, 3), (1, 5) {{ } { }} Turner A-305 Yes. Relations are sets of tuples and not ordered Inf4Oec10, SL02 13/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 14/48 M. B¨ohlen, ifi@uzh Checking... Checking... 4. Illustrate the following relations graphically: r(X , Y )= (1, a), (2, b), (3, c) { } s(A, B, C)= (1, 2, 3) { } r 6. What is the difference between a set and a relation? Illustrate with X Y s an example. 1 a A B C set: elements can be anything. 2 b 1 2 3 relation: all tuples must have the same schema. S = (1, r), (2, c , ), is a set but not a relation. 3 c { {⋆} •} 5. Determine the following objects: ◮ the 2nd attribute of relation r? X ◮ the 3rd tuple of relation r? there is no ordering ◮ the tuple in relation r with the smallest value for attribute X ? (1,a) Inf4Oec10, SL02 15/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 16/48 M. B¨ohlen, ifi@uzh Summary of the Relational Data Model Constraints ◮ A domain D is a set of atomic data values. ◮ phone numbers, names, grades, birthdates, departments ◮ each domain includes the special value null ◮ With each domain a data type or format is specified. ◮ 5 digit integers, yyyy-mm-dd, characters ◮ Constraints are conditions that must be satisfied by all valid relation ◮ An attribute Ai describes the role of a domain in a relation schema. instances ◮ PhoneNr, Age, DeptName ◮ There are four main types of constraints in the relational model: ◮ A relation schema R(A1,..., An) is made up of a relation name R and a list of attributes. ◮ Domain constraints: each value in a tuple must be from the domain ◮ employee(Name, Dept, Salary), department(DName, Manager, Address) of its attribute ◮ Key constraints ◮ A tuple t is an ordered list of values t =(v1,..., vn) with vi dom(Ai ). ∈ ◮ Entity constraints ◮ t =(Tom, SE, 23K) ◮ Referential integrity constraints ◮ A relation r D1 ... Dn over schema R(A1,..., An) is a set of n-ary tuples. ⊆ × × ◮ r = (Tom, SE, 23K), (Lene, DB, 33K) Names Departments Integer { }⊆ × × ◮ A database DB is a set of relations. ◮ DB = r, s { } ◮ r = (Tom, SE, 23K), (Lene, DB, 33K) { } ◮ s = (SE, Tom, Boston), (DB, Lena, Tucson) { } Inf4Oec10, SL02 17/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 18/48 M. B¨ohlen, ifi@uzh Key Constraints/1 Key Constraints/2 ◮ Let K R ⊆ ◮ K is a superkey of R if values for K are sufficient to identify a unique tuple of each possible relation r ◮ By “possible” we mean a relation r that could exist in the enterprise ◮ K is a candidate key if K is minimal we are modeling. Example: CustName is a candidate key for Customer, since it is a ◮ Example: CustName, CustStreet and CustName are both { } superkeys{ of Customer, if no two} customers{ can possibly} have the superkey and no subset of it is a superkey. same name. ◮ Primary key: a candidate key chosen as the principal means of ◮ In real life, an attribute such as CustID would be used instead of identifying tuples within a relation CustName to uniquely identify customers, but we omit it to keep our examples small, and instead assume customer names are unique. ◮ Should choose an attribute whose value never, or very rarely, changes. ◮ E.g. email address is unique, but may change CustName CustStreet ID CustName CustStreet N. Jeff Binzm¨uhlestr 1 N. Jeff Binzm¨uhlestr N. Jeff Hochstr 2 N. Jeff Hochstr bad good Inf4Oec10, SL02 19/48 M. B¨ohlen, ifi@uzh Inf4Oec10, SL02 20/48 M. B¨ohlen, ifi@uzh Entity Constraints Referential Integrity Constraint ◮ A relation schema may have an attribute that corresponds to the ◮ The entity constraint requires that the primary key attributes of primary key of another relation.
Recommended publications
  • Relational Algebra
    Relational Algebra Instructor: Shel Finkelstein Reference: A First Course in Database Systems, 3rd edition, Chapter 2.4 – 2.6, plus Query Execution Plans Important Notices • Midterm with Answers has been posted on Piazza. – Midterm will be/was reviewed briefly in class on Wednesday, Nov 8. – Grades were posted on Canvas on Monday, Nov 13. • Median was 83; no curve. – Exam will be returned in class on Nov 13 and Nov 15. • Please send email if you want “cheat sheet” back. • Lab3 assignment was posted on Sunday, Nov 5, and is due by Sunday, Nov 19, 11:59pm. – Lab3 has lots of parts (some hard), and is worth 13 points. – Please attend Labs to get help with Lab3. What is a Data Model? • A data model is a mathematical formalism that consists of three parts: 1. A notation for describing and representing data (structure of the data) 2. A set of operations for manipulating data. 3. A set of constraints on the data. • What is the associated query language for the relational data model? Two Query Languages • Codd proposed two different query languages for the relational data model. – Relational Algebra • Queries are expressed as a sequence of operations on relations. • Procedural language. – Relational Calculus • Queries are expressed as formulas of first-order logic. • Declarative language. • Codd’s Theorem: The Relational Algebra query language has the same expressive power as the Relational Calculus query language. Procedural vs. Declarative Languages • Procedural program – The program is specified as a sequence of operations to obtain the desired the outcome. I.e., how the outcome is to be obtained.
    [Show full text]
  • Relational Algebra and SQL Relational Query Languages
    Relational Algebra and SQL Chapter 5 1 Relational Query Languages • Languages for describing queries on a relational database • Structured Query Language (SQL) – Predominant application-level query language – Declarative • Relational Algebra – Intermediate language used within DBMS – Procedural 2 1 What is an Algebra? · A language based on operators and a domain of values · Operators map values taken from the domain into other domain values · Hence, an expression involving operators and arguments produces a value in the domain · When the domain is a set of all relations (and the operators are as described later), we get the relational algebra · We refer to the expression as a query and the value produced as the query result 3 Relational Algebra · Domain: set of relations · Basic operators: select, project, union, set difference, Cartesian product · Derived operators: set intersection, division, join · Procedural: Relational expression specifies query by describing an algorithm (the sequence in which operators are applied) for determining the result of an expression 4 2 The Role of Relational Algebra in a DBMS 5 Select Operator • Produce table containing subset of rows of argument table satisfying condition σ condition (relation) • Example: σ Person Hobby=‘stamps’(Person) Id Name Address Hobby Id Name Address Hobby 1123 John 123 Main stamps 1123 John 123 Main stamps 1123 John 123 Main coins 9876 Bart 5 Pine St stamps 5556 Mary 7 Lake Dr hiking 9876 Bart 5 Pine St stamps 6 3 Selection Condition • Operators: <, ≤, ≥, >, =, ≠ • Simple selection
    [Show full text]
  • Session 5 – Main Theme
    Database Systems Session 5 – Main Theme Relational Algebra, Relational Calculus, and SQL Dr. Jean-Claude Franchitti New York University Computer Science Department Courant Institute of Mathematical Sciences Presentation material partially based on textbook slides Fundamentals of Database Systems (6th Edition) by Ramez Elmasri and Shamkant Navathe Slides copyright © 2011 and on slides produced by Zvi Kedem copyight © 2014 1 Agenda 1 Session Overview 2 Relational Algebra and Relational Calculus 3 Relational Algebra Using SQL Syntax 5 Summary and Conclusion 2 Session Agenda . Session Overview . Relational Algebra and Relational Calculus . Relational Algebra Using SQL Syntax . Summary & Conclusion 3 What is the class about? . Course description and syllabus: » http://www.nyu.edu/classes/jcf/CSCI-GA.2433-001 » http://cs.nyu.edu/courses/fall11/CSCI-GA.2433-001/ . Textbooks: » Fundamentals of Database Systems (6th Edition) Ramez Elmasri and Shamkant Navathe Addition Wesley ISBN-10: 0-1360-8620-9, ISBN-13: 978-0136086208 6th Edition (04/10) 4 Icons / Metaphors Information Common Realization Knowledge/Competency Pattern Governance Alignment Solution Approach 55 Agenda 1 Session Overview 2 Relational Algebra and Relational Calculus 3 Relational Algebra Using SQL Syntax 5 Summary and Conclusion 6 Agenda . Unary Relational Operations: SELECT and PROJECT . Relational Algebra Operations from Set Theory . Binary Relational Operations: JOIN and DIVISION . Additional Relational Operations . Examples of Queries in Relational Algebra . The Tuple Relational Calculus . The Domain Relational Calculus 7 The Relational Algebra and Relational Calculus . Relational algebra . Basic set of operations for the relational model . Relational algebra expression . Sequence of relational algebra operations . Relational calculus . Higher-level declarative language for specifying relational queries 8 Unary Relational Operations: SELECT and PROJECT (1/3) .
    [Show full text]
  • Relational Algebra & Relational Calculus
    Relational Algebra & Relational Calculus Lecture 4 Kathleen Durant Northeastern University 1 Relational Query Languages • Query languages: Allow manipulation and retrieval of data from a database. • Relational model supports simple, powerful QLs: • Strong formal foundation based on logic. • Allows for optimization. • Query Languages != programming languages • QLs not expected to be “Turing complete”. • QLs not intended to be used for complex calculations. • QLs support easy, efficient access to large data sets. 2 Relational Query Languages • Two mathematical Query Languages form the basis for “real” query languages (e.g. SQL), and for implementation: • Relational Algebra: More operational, very useful for representing execution plans. • Basis for SEQUEL • Relational Calculus: Let’s users describe WHAT they want, rather than HOW to compute it. (Non-operational, declarative.) • Basis for QUEL 3 4 Cartesian Product Example • A = {small, medium, large} • B = {shirt, pants} A X B Shirt Pants Small (Small, Shirt) (Small, Pants) Medium (Medium, Shirt) (Medium, Pants) Large (Large, Shirt) (Large, Pants) • A x B = {(small, shirt), (small, pants), (medium, shirt), (medium, pants), (large, shirt), (large, pants)} • Set notation 5 Example: Cartesian Product • What is the Cartesian Product of AxB ? • A = {perl, ruby, java} • B = {necklace, ring, bracelet} • What is BxA? A x B Necklace Ring Bracelet Perl (Perl,Necklace) (Perl, Ring) (Perl,Bracelet) Ruby (Ruby, Necklace) (Ruby,Ring) (Ruby,Bracelet) Java (Java, Necklace) (Java, Ring) (Java, Bracelet) 6 Mathematical Foundations: Relations • The domain of a variable is the set of its possible values • A relation on a set of variables is a subset of the Cartesian product of the domains of the variables. • Example: let x and y be variables that both have the set of non- negative integers as their domain • {(2,5),(3,10),(13,2),(6,10)} is one relation on (x, y) • A table is a subset of the Cartesian product of the domains of the attributes.
    [Show full text]
  • Relational Algebra Expression Evaluation
    Faculty of Informatics, Masaryk University Relational Algebra Expression Evaluation Bachelor's Thesis Lucie Molkov´a Brno, spring 2009 Declaration Thereby I declare that this thesis is my original work, which I have created on my own. All sources and literature used in writing the thesis, as well as any quoted material, are properly cited, including full reference to its source. Advisor: RNDr. Vlastislav Dohnal, Ph.D. Acknowledgements I would like to thank my advisor RNDr. Vlastislav Dohnal, Ph.D. for the help and motivation he provided throughout my work on this thesis and to Loren K. Rhodes, Ph.D. for valuable inputs. Special thanks go to Tom´aˇsJanouˇsekand Bc. Petr Roˇckai for support and ideas that saved me a lot of time. Abstract Relational algebra is a query language that is being used to explain basic relational operations and their principles. Many books and articles are concerned with the theory of relational algebra, however there is no practical use for it. One of the reasons is that no software exists that would allow a real use of relational alge- bra. Most of the currently used relational database management systems work with SQL queries. This work therefore describes and implemets a tool that transforms a relational algebra expressions into SQL queries, allowing the expressions to be evaluated in standard databases. This work also defines a new, applicable syntax for relational algebra and describes its grammar in order to ensure the correctness of the expressions. Keywords Relationa Algebra, SQL, Transformation, Perl, Parsing, Parse::Yapp, Syntax Anal- ysis, Semantic Analysis Contents 1 Introduction 7 1.1 Objectives .
    [Show full text]
  • Algebraic Operations on Tabular Data Context 6.1 Basic Idea of Relational
    Context Database Design: 6 The Relational Data Model: e s - developing a relational a Requirements analysis b database schema Algebraic operations on tabular data a t Design: a d - formal theory 6.1 Basic idea of relational languages Conceptual Design g n i Data handling in a rela- s 6.2 Relational Algebra operations u tional database Schema design d 6.3 Relational Algebra: Syntax and Semantics n - Algebra,-calculus -SQL -logical a (“create tables”) g Extensions 6.4. More Operators n i n g Using Databases 6.5 Special Topics of RA i s from application progs 6.5.1 Relational algebra operators in SQL e D : Special topics, 6.5.2 Relational completeness 1 Schema design t Physical Schema, 6.5.3 What is missing in RA? r a -physical P 6.5.4 RA operator trees Part 2: (“create access path”) Implementation of DBS Loading, administration, Transaction, Kemper / Eickler: 3.4, Elmasri /Navathe: chap. 74-7.6, tuning, maintenance, Concurrency control Garcia-Molina, Ullman, Widom: chap. 5 reorganization Recovery 6.1 Basic idea of relational languages Relational Languages • Data Model: Important concepts Goal of language design Language for definition and Given a relational database like the Video shop DB handling (manipulation ) of data Design a language, which allows to express queries – Languages for handling data: like: • Relational Algebra (RA) as a semantically well defined - Customers who rented videos for more than 100 $ last month applicative language - List of all movies no copy of which have been on loan since 2 month - List the total sales volume of each movie within the last year • Relational tuple calculus (domain calculus): predicate logic - Is there anybody whose rented movies all have category "horror"? interpretation of data and queries y? …….
    [Show full text]
  • Relational Databases, Logic, and Complexity
    Relational Databases, Logic, and Complexity Phokion G. Kolaitis University of California, Santa Cruz & IBM Research-Almaden [email protected] 2009 GII Doctoral School on Advances in Databases 1 What this course is about Goals: Cover a coherent body of basic material in the foundations of relational databases Prepare students for further study and research in relational database systems Overview of Topics: Database query languages: expressive power and complexity Relational Algebra and Relational Calculus Conjunctive queries and homomorphisms Recursive queries and Datalog Selected additional topics: Bag Semantics, Inconsistent Databases Unifying Theme: The interplay between databases, logic, and computational complexity 2 Relational Databases: A Very Brief History The history of relational databases is the history of a scientific and technological revolution. Edgar F. Codd, 1923-2003 The scientific revolution started in 1970 by Edgar (Ted) F. Codd at the IBM San Jose Research Laboratory (now the IBM Almaden Research Center) Codd introduced the relational data model and two database query languages: relational algebra and relational calculus . “A relational model for data for large shared data banks”, CACM, 1970. “Relational completeness of data base sublanguages”, in: Database Systems, ed. by R. Rustin, 1972. 3 Relational Databases: A Very Brief History Researchers at the IBM San Jose Laboratory embark on the System R project, the first implementation of a relational database management system (RDBMS) In 1974-1975, they develop SEQUEL , a query language that eventually became the industry standard SQL . System R evolved to DB2 – released first in 1983. M. Stonebraker and E. Wong embark on the development of the Ingres RDBMS at UC Berkeley in 1973.
    [Show full text]
  • Database Management Systems Solutions Manual Third Edition
    DATABASE MANAGEMENT SYSTEMS SOLUTIONS MANUAL THIRD EDITION Raghu Ramakrishnan University of Wisconsin Madison, WI, USA Johannes Gehrke Cornell University Ithaca, NY, USA Jeff Derstadt, Scott Selikoff, and Lin Zhu Cornell University Ithaca, NY, USA CONTENTS PREFACE iii 1 INTRODUCTION TO DATABASE SYSTEMS 1 2 INTRODUCTION TO DATABASE DESIGN 6 3THERELATIONALMODEL 16 4 RELATIONAL ALGEBRA AND CALCULUS 28 5 SQL: QUERIES, CONSTRAINTS, TRIGGERS 45 6 DATABASE APPLICATION DEVELOPMENT 63 7 INTERNET APPLICATIONS 66 8 OVERVIEW OF STORAGE AND INDEXING 73 9 STORING DATA: DISKS AND FILES 81 10 TREE-STRUCTURED INDEXING 88 11 HASH-BASED INDEXING 100 12 OVERVIEW OF QUERY EVALUATION 119 13 EXTERNAL SORTING 126 14 EVALUATION OF RELATIONAL OPERATORS 131 i iiDatabase Management Systems Solutions Manual Third Edition 15 A TYPICAL QUERY OPTIMIZER 144 16 OVERVIEW OF TRANSACTION MANAGEMENT 159 17 CONCURRENCY CONTROL 167 18 CRASH RECOVERY 179 19 SCHEMA REFINEMENT AND NORMAL FORMS 189 20 PHYSICAL DATABASE DESIGN AND TUNING 204 21 SECURITY 215 PREFACE It is not every question that deserves an answer. Publius Syrus, 42 B.C. I hope that most of the questions in this book deserve an answer. The set of questions is unusually extensive, and is designed to reinforce and deepen students’ understanding of the concepts covered in each chapter. There is a strong emphasis on quantitative and problem-solving type exercises. While I wrote some of the solutions myself, most were written originally by students in the database classes at Wisconsin. I’d like to thank the many students who helped in developing and checking the solutions to the exercises; this manual would not be available without their contributions.
    [Show full text]
  • Chapter (5) the Relational Data Model, Relational Constraints, and the Relational Algebra
    Chapter (5) The Relational Data Model, Relational Constraints, and the Relational Algebra Objectives • Describe the basic principals of the relational model of data • Define the modeling concepts and notation of the relational model • Learn about the relational constraints • Define the update operations of the relational model • Handling the violations of the integrity constraints • Learn about relational algebra that is used to manipulate relations and specifying queries. The relational model was first introduced by Ted Codd of IBM Research in a 1970 in a classic paper [Codd 1970]. 1 Relational Model Concepts The relational model represents the database as a collection of relations. A relation is often resembles a table of values or to some extent, a “flat” file of records. There are important differences between relations and files. A relation that is thought as a table of values contains rows that represent a collection of related values. In the formal relational model terminology, a row is called a tuple, a column header is called an attribute, and the table is called a relation. The data type describing the types of values that can appear in each column is called a domain. 2 1 Domains A domain D is a set of values that are indivisible as far as the relational model is concerned, i.e., it contains a set of atomic values. Examples: USA_Phone numbers. Which is ….. Local_phone_numbers. Which is … Names: The set of names of persons. Social_security_numbers: The set of valid 9-digit social security numbers. GPA: A real value between 0 and 4. There is a data type of format associated with each domain.
    [Show full text]
  • Relational Algebra
    Cleveland State University CIS611 – Relational Database Systems Lecture Notes Prof. Victor Matos RELATIONAL ALGEBRA V. Matos - CIS611_LECTURE_NOTES_ALGEBRA.docx 1 THE RELATIONAL DATA MODEL (RM) and the Relational Algebra The relational model of data (RM) was introduced by Dr. E. Codd (CACM, June 1970). The RM is simpler and more uniform than the preceding Network and Hierarchical model. S.Todd, (IBM 1976) presented PRTV the first implementation of a relational algebra DBMS. A. Klug added summary functions for statistical computing (ACM SIGMOD 1982). Roth, Oszoyoglu et al. (1987) extended the model to allow nested data structures Clifford, Tansel, Navathe, and others have added time especifications into the model Current research is aimed at extending the model to support complex data objects, multimedia mgnt, hyperdata, geographical, temporal and logical processing. V. Matos - CIS611_LECTURE_NOTES_ALGEBRA.docx 2 THE RELATIONAL DATA MODEL (RM) and the Relational Algebra A relational database is a collection of relations A relation is a 2-dimensional table, in which each row represents a collection of related data values The values in a relation can be interpreted as a fact describing an entity or a relationship Relation name Attributes STUDENT Name SSN Address GPA Mary Poppins 111-22-3333 77 Picadilly St 4.00 Pepe Gonzalez 123-45-6789 123 Bonita Rd. 3.09 Tuples V. Sundarabatharan 999-88-7777 105 Calcara Ave. 3.87 Shi-Wua Yan 881-99-0101 778 Tienamen Sq. 3.88 V. Matos - CIS611_LECTURE_NOTES_ALGEBRA.docx 3 THE RELATIONAL DATA MODEL (RM) and the Relational Algebra Domains, Tuples, Attributes, and Relations A domain D is a set of atomic values.
    [Show full text]
  • Session 7 – Main Theme
    Database Systems Session 7 – Main Theme Functional Dependencies and Normalization Dr. Jean-Claude Franchitti New York University Computer Science Department Courant Institute of Mathematical Sciences Presentation material partially based on textbook slides Fundamentals of Database Systems (6th Edition) by Ramez Elmasri and Shamkant Navathe Slides copyright © 2011 and on slides produced by Zvi Kedem copyight © 2014 1 Agenda 1 Session Overview 2 Logical Database Design - Normalization 3 Normalization Process Detailed 4 Summary and Conclusion 2 Session Agenda . Logical Database Design - Normalization . Normalization Process Detailed . Summary & Conclusion 3 What is the class about? . Course description and syllabus: » http://www.nyu.edu/classes/jcf/CSCI-GA.2433-001 » http://cs.nyu.edu/courses/spring15/CSCI-GA.2433-001/ . Textbooks: » Fundamentals of Database Systems (6th Edition) Ramez Elmasri and Shamkant Navathe Addition Wesley ISBN-10: 0-1360-8620-9, ISBN-13: 978-0136086208 6th Edition (04/10) 4 Icons / Metaphors Information Common Realization Knowledge/Competency Pattern Governance Alignment Solution Approach 55 Agenda 1 Session Overview 2 Logical Database Design - Normalization 3 Normalization Process Detailed 4 Summary and Conclusion 6 Agenda . Informal guidelines for good design . Functional dependency . Basic tool for analyzing relational schemas . Informal Design Guidelines for Relation Schemas . Normalization: . 1NF, 2NF, 3NF, BCNF, 4NF, 5NF • Normal Forms Based on Primary Keys • General Definitions of Second and Third Normal Forms • Boyce-Codd Normal Form • Multivalued Dependency and Fourth Normal Form • Join Dependencies and Fifth Normal Form 7 Logical Database Design . We are given a set of tables specifying the database » The base tables, which probably are the community (conceptual) level . They may have come from some ER diagram or from somewhere else .
    [Show full text]
  • DML, Relational Algebra
    CS3200 – Database Design Spring 2018 Derbinsky SQL: Part 1 DML, Relational Algebra Lecture 3 SQL: Part 1 (DML, Relational Algebra) February 6, 2018 1 CS3200 – Database Design Spring 2018 Derbinsky Relational Algebra • The basic set of operations for the relational model – Note that the relational model assumes sets, so some of the database operations will not map • Allows the user to formally express a retrieval over one or more relations, as a relational algebra expression – Results in a new relation, which could itself be queried (i.e. composable) • Why is RA important? – Formal basis for SQL – Used in query optimization – Common vocabulary in data querying technology – Sometimes easier to understand the flow of complex SQL SQL: Part 1 (DML, Relational Algebra) February 6, 2018 2 CS3200 – Database Design Spring 2018 Derbinsky In the Beginning… Chamberlin, Donald D., and Raymond F. Boyce. "SEQUEL: A structured English query language." Proceedings of the 1974 ACM SIGFIDET (now SIGMOD) workshop on Data description, access and control. ACM, 1974. “In this paper we present the data manipulation facility for a structured English query language (SEQUEL) which can be used for accessing data in an integrated relational data base. Without resorting to the concepts of bound variables and quantifiers SEQUEL identifies a set of simple operations on tabular structures, which can be shown to be of equivalent power to the first order predicate calculus. A SEQUEL user is presented with a consistent set of keyword English templates which reflect how people use tables to obtain information. Moreover, the SEQUEL user is able to compose these basic templates in a structured manner in order to form more complex queries.
    [Show full text]