Chapter 3 Relational Model

Size: px
Start display at page:

Download "Chapter 3 Relational Model"

Transcription

1 Chapter 3 Relational Model Table of Contents 1. Structure of Relational Databases 2. Relational Algebra 3. Tuple Relational Calculus 4. Domain Relational Calculus Chapter 3-1 1

2 1. Structure of Relational Databases z Basic Structure z Database Schema z Query Language Chapter 3-2 Basic Structure z Relational Database ii aq1 9aÑI Y ée: Entity- Relationshipa = 9aI Iñ z Table (Relation) Schema: Set of Attribute (Column, Field) Instance: Set of Record (Row, Tuple) z Domain î Attribute½ µ ÿñe ¾V õ: Customer(aq - %} 20, a - } 3, ) A table T of n attributes and D i : domain of i th attributes T D 1 D 2 D n-1 D n Chapter 3-3 2

3 Database Schema - ER Diagram account-number branch-city balance branch-name assets Account Account- Branch Branch Depositor Loan- Branch Customer Borrower Loan customer-name customer-city account-number street balance Chapter 3-4 Database Schema - Sample z Four Sample Schema - Entity Customer = (customer-name, street, customer-city) Branch = (branch-name, branch-city, assets) Account = (branch-name, account-number, balance) Loan = (branch-name, loan-number, amount) z Two Sample Schema - Relationship Depositor = (customer-name, account-number) Borrower = (customer-name, loan-number) Chapter 3-5 3

4 Database Schema - Design Issue z Single Relation Deposit + Customer Account-Info Account-Info = (branch-name, account-number, balance, customer-name, street, customer-city) z Problem Repetition of Information Incomplete Tuples z Advantage? Chapter 3-6 Formal Query Languages z Query Language Language in which a user requests information from DB Higher than programming languages z Two Categories of Query Language Procedural: éi ñi Ý Example: Relational Algebra Nonprocedural: Relational Calculus i z Types of Query Languages Relational Algebra, Tuple Calculus, Domain Calculus Chapter 3-7 4

5 2. Relational Algebra z  Procedural Query Language E a E Relation1 r)i EÙ µi é Relation1 Ê z Fundamental Operations Unary Operation: Select, Project, Rename Binary Operations: Cartesian Product, Union, Set Difference z Additional Operations Set Intersection, Join, Division, Assignment Chapter 3-8 Select z Notation: σ P (r) P: Predicate (Sequence of Comparison/Logical Operators) Operators:,, =,, <,, >, r: Relation Loan 9a½ Perryridge ýe á? σ branch-name = Perryridge (Loan) Perryridge ý½ $1200 a í I? σ branch-name = Perryridge amount > 1200 (Loan) Chapter 3-9 5

6 Project z Notation: Π A1, A2,, Ar (r) Ai: Attribute of Relation r s Loan 9a½ ±y u%- í õn? Π loan-number, amount (Loan) Loan 9a½ í õna $3000 a e ±ye u%- í õn? Π loan-number, amount (σ amount > 3000 (Loan)) Composition of Relational Operations Chapter 3-10 Union z Notation: r s r and s are compatible relations. Attribute Æi Attribute type Æi (Domain: Equal) -vé ] E Í ÍÑE aq? Π customer-name (borrower) Π customer-name (depositor) Chapter

7 Set Difference z Notation: r - s r and s are compatible relations. Attribute Æi Attribute type Æi (Domain: Equal) -v½ õõ- Ea í - 7- Í Í ÑE aq? Π customer-name (borrower) - Π customer-name (depositor) Chapter 3-12 Cartesian Product z Notation: r s é relatione É Attribute : re attribute + se attribute õaé : re õaé se õaé Perryridge ý½ í - ÍÑE aq? Loan = (branch-name, loan-number, amount) Borrower = (customer-name, loan-number) Π customer-name (σ loan.loan-number = borrower.loan-number ( σ branch-name = Perryridge (Loan Borrower))) Chapter

8 Rename z Notation: ρ x(a1, A2,, An) (E) Expression EE éi x½ Mæ (Ai: Attribute list of x) Find the largest account balance in the bank. Π balance (account) - Π account.balance (σ account.balance < d.balance (account ρ d (account))) Smith- ÆiI ±É ü ] ½ ]ée Í Í? Π customer.customer-name (σ customer. street = smith-addr.street customer.customer-city = smith-addr.city (customer ρ smith-addr(street, city) (Π street, customer-city (σ customer-name = Smith (customer))))) Chapter 3-14 Formal Definition of Relational Algebra z Basic Expression A relation in the database A constant relation z General Relational Algebra Expression E 1 E 2 (E 1 and E 2 : Relational algebra expressions) E 1 - E 2 E 1 E 2 σ P (E 1 ), P: a predicate on attribute in E 1 Π S (E 1 ), S: a list consisting of some attributes in E 1 ρ x (E 1 ), x: a new name for the result of E 1 Chapter

9 Additional Operations z Set Intersection Operation z Natural Join Operation z Division Operation z Assignment Operation Chapter 3-16 Set Intersection z Notation: r s r and s are compatible relations. Attribute Æi Attribute type Æi (Domain: Equal) r s = r - (r - s) Find all customers who have both a loan and an account Π customer-name (borrower) Π customer-name (depositor) Chapter

10 Natural Join z Notation r s = Π R S (σ r.a1 = s.a1 r.a2 = s.a2 r.an = s.an (r s)) If R S =, then r s = r s Theta Join: r θ s = σ θ (r s) Harrison ½ Í u Ía õõe -v? Π branch-name (σ customer-city= Harrison (customer account depositor)) Find all customers who have both a loan and an account Π customer-name (borrower depositor) Chapter 3-18 Division z Notation: r ø s For All ½ í µe½ r(a, B) ø s(b) Brooklyn ½ ñei Í -v½ ±yi í± Í Π customer-name, branch-name (depositor account) ø Π branch-name (σ branch-city= Brooklyn (branch)) z Note r ø s = Π R-S (r) - Π R-S ((Π R-S (r) s) - Π R-S,S (r)) Chapter

11 Assignment z Notation: r E Relational algebra expression EE éi õae r ½ Mæ âži Ê1 ÙÙ E Ê)I qmm 9 : r ø s temp1 Π R-S (r) temp2 Π R-S ((temp1 s) - Π R-S,S (r)) result = temp1 - temp2 Chapter Tuple Relational Calculus z Tuple Calculus½ QueryE Iñ Ê: {t P(t)} t: tuple variable, P: predicate Eå: Pi %)I E Í tupleñe ¾V t[a] or t[1]: Component of a tuple variable $1200a í I ±ye -v, ±yu%, í õn? {t t loan t[amount] > 1200} Chapter

12 Existential Quantifier: z Notation: t r (Q(t)) Relation r½ ]a Qi ¹^E tuple tí a? s $1200a í I ±ye ±yu%? {t s loan(t[loan-number] = s[loan-number] s[amount] > 1200} Perryridge ý½ í I ÍE aq? {t s borrower(t[customer-name] = s[customer-name] u loan(u[loan-number] = s[loan-number] u[branch-name] = Perryridge ))} Chapter 3-22 Universal Quantifier: z Notation: t r (Q(t)) Relation re Í tupleña ]a Qi ¹^? Brooklyn ½ ñei Í ý½ õõi Í? {t u branch(u[branch-city] = Brooklyn s depositor(t[customer-name] = s[customer-name] w account(w[account-no] = s[account-no] w[branch-name] = u[branch-name])))} Chapter

13 Formal Definition z Expression Form {t P(t)}, P: formula A formula is built up out of atoms. z Atom s r (s: tuple variable, r: relation) s[x] Θ u[y] (s, u: tuple variable, x: attribute, Θ: <,, =,, >, ) s[x] Θ c (s: tuple variable, x: attribute, c: constant) Chapter 3-24 Formal Definition - ±z z Formulai ~E ÉF An atom is a formula. P 1 : formula, then so are P 1 and (P 1 ). P 1, P 2 : formulae, then so are P 1 P 2, P 1 P 2, P 1 P 2 P 1 (s): formula and r: relation, then s r (P 1 (s)) and s r (P 1 (s)) are formulae. z Equivalence Rule P 1 P 2 ( P 1 P 2 ) t r (P 1 (t)) t r ( P 1 (t)) P 1 P 2 P 1 P 2 Chapter

14 Safety of Expression z Problem of Tuple Relational Calculus Infinite Relation Example: {t (t loan)} z Concept of Domain: dom(p) Set of all values that appear explicitly in P, or Set of all values that appear in one or more relations whose names appear in P. Example: dom(t loan t[amount] > 1200) {1200} loan Chapter 3-26 Concept of Safe Expression z {t P(t)}í safei ]a All values that appear in the result are values from dom(p) s {t t loan t[amount] > 1200} safe {t (t loan)} safe z Expressive Power of Languages The tuple relational calculus restricted to safe expression is equivalent in expressive power to the relational algebra. Chapter

15 4. Domain Relational Calculus z Notation: {<x 1, x 2,, x n > P(x 1, x 2,, x n )} x i : domain variable P: formula composed of atoms z Formal Definition of Domain Relational Calculus Tuple relational calculus- ]E Æi aý Atom: domain variable½ ía E Constant: domain constant Notational Shorthand a, b, c (P(a, b, c)) = a ( b ( c (P(a, b, c)))) Chapter 3-28 Example Queries z $1200a í I ±ye -v, ±yu%, õn? {< b, l, a > < b, l, a > loan a > 1200} z $1200a í I ±ye ±yu%? {< l > a, b (< b, l, a > loan a > 1200)} z Perryridge ý½ í I Í ü í õn? {< c, a > l (< c, l > borrower b (< b, l, a > loan b = Perryridge ))} z Brooklyn E Í ý½ õõi Í? {< c > x, y, z (< x, y, z > branch y = Brooklyn a, b (< x, a, b > account < c, a > depositor ))} Chapter

16 Expressive Power of Languages All three of the following are equivalent: z The relational algebra z The tuple relational calculus restricted to safe expressions z The domain relational calculus restricted to safe expressions Chapter

Relational Algebra 2. Week 5

Relational Algebra 2. Week 5 Relational Algebra 2 Week 5 Relational Algebra (So far) Basic operations: Selection ( σ ) Selects a subset of rows from relation. Projection ( π ) Deletes unwanted columns from relation. Cross-product

More information

CS54100: Database Systems

CS54100: Database Systems CS54100: Database Systems Relational Algebra 3 February 2012 Prof. Walid Aref Core Relational Algebra A small set of operators that allow us to manipulate relations in limited but useful ways. The operators

More information

RELATIONAL MODEL.

RELATIONAL MODEL. RELATIONAL MODEL Structure of Reltionl Dtbses Reltionl Algebr Tuple Reltionl Clculus Domin Reltionl Clculus Extended Reltionl-Algebr- Opertions Modifiction of the Dtbse Views EXAMPLE OF A RELATION BASIC

More information

Relational Algebra & Calculus

Relational Algebra & Calculus Relational Algebra & Calculus Yanlei Diao UMass Amherst Slides Courtesy of R. Ramakrishnan and J. Gehrke 1 Outline v Conceptual Design: ER model v Logical Design: ER to relational model v Querying and

More information

Relational Algebra and Calculus

Relational Algebra and Calculus Topics Relational Algebra and Calculus Linda Wu Formal query languages Preliminaries Relational algebra Relational calculus Expressive power of algebra and calculus (CMPT 354 2004-2) Chapter 4 CMPT 354

More information

Query Processing. 3 steps: Parsing & Translation Optimization Evaluation

Query Processing. 3 steps: Parsing & Translation Optimization Evaluation rela%onal algebra Query Processing 3 steps: Parsing & Translation Optimization Evaluation 30 Simple set of algebraic operations on relations Journey of a query SQL select from where Rela%onal algebra π

More information

Advanced DB CHAPTER 5 DATALOG

Advanced DB CHAPTER 5 DATALOG Advanced DB CHAPTER 5 DATALOG Datalog Basic Structure Syntax of Datalog Rules Semantics of Nonrecursive Datalog Safety Relational Operations in Datalog Recursion in Datalog The Power of Recursion A More

More information

Database Applications (15-415)

Database Applications (15-415) Database Applications (15-415) Relational Calculus Lecture 5, January 27, 2014 Mohammad Hammoud Today Last Session: Relational Algebra Today s Session: Relational algebra The division operator and summary

More information

Schedule. Today: Jan. 17 (TH) Jan. 24 (TH) Jan. 29 (T) Jan. 22 (T) Read Sections Assignment 2 due. Read Sections Assignment 3 due.

Schedule. Today: Jan. 17 (TH) Jan. 24 (TH) Jan. 29 (T) Jan. 22 (T) Read Sections Assignment 2 due. Read Sections Assignment 3 due. Schedule Today: Jan. 17 (TH) Relational Algebra. Read Chapter 5. Project Part 1 due. Jan. 22 (T) SQL Queries. Read Sections 6.1-6.2. Assignment 2 due. Jan. 24 (TH) Subqueries, Grouping and Aggregation.

More information

Introduction to Data Management. Lecture #12 (Relational Algebra II)

Introduction to Data Management. Lecture #12 (Relational Algebra II) Introduction to Data Management Lecture #12 (Relational Algebra II) Instructor: Mike Carey mjcarey@ics.uci.edu Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 1 Announcements v HW and exams:

More information

INTRODUCTION TO RELATIONAL DATABASE SYSTEMS

INTRODUCTION TO RELATIONAL DATABASE SYSTEMS INTRODUCTION TO RELATIONAL DATABASE SYSTEMS DATENBANKSYSTEME 1 (INF 3131) Torsten Grust Universität Tübingen Winter 2017/18 1 THE RELATIONAL ALGEBRA The Relational Algebra (RA) is a query language for

More information

Databases 2011 The Relational Algebra

Databases 2011 The Relational Algebra Databases 2011 Christian S. Jensen Computer Science, Aarhus University What is an Algebra? An algebra consists of values operators rules Closure: operations yield values Examples integers with +,, sets

More information

Relational Calculus. Dr Paolo Guagliardo. University of Edinburgh. Fall 2016

Relational Calculus. Dr Paolo Guagliardo. University of Edinburgh. Fall 2016 Relational Calculus Dr Paolo Guagliardo University of Edinburgh Fall 2016 First-order logic term t := x (variable) c (constant) f(t 1,..., t n ) (function application) formula ϕ := P (t 1,..., t n ) t

More information

Database Applications (15-415)

Database Applications (15-415) Database Applications (15-415) Relational Calculus Lecture 6, January 26, 2016 Mohammad Hammoud Today Last Session: Relational Algebra Today s Session: Relational calculus Relational tuple calculus Announcements:

More information

! " # $! % & '! , ) ( + - (. ) ( ) * + / 0 1 2 3 0 / 4 5 / 6 0 ; 8 7 < = 7 > 8 7 8 9 : Œ Š ž P P h ˆ Š ˆ Œ ˆ Š ˆ Ž Ž Ý Ü Ý Ü Ý Ž Ý ê ç è ± ¹ ¼ ¹ ä ± ¹ w ç ¹ è ¼ è Œ ¹ ± ¹ è ¹ è ä ç w ¹ ã ¼ ¹ ä ¹ ¼ ¹ ±

More information

General Overview - rel. model. Carnegie Mellon Univ. Dept. of Computer Science /615 DB Applications. Motivation. Overview - detailed

General Overview - rel. model. Carnegie Mellon Univ. Dept. of Computer Science /615 DB Applications. Motivation. Overview - detailed Carnegie Mellon Univ. Dep of Computer Science 15-415/615 DB Applications C. Faloutsos & A. Pavlo Lecture#5: Relational calculus General Overview - rel. model history concepts Formal query languages relational

More information

7 RC Simulates RA. Lemma: For every RA expression E(A 1... A k ) there exists a DRC formula F with F V (F ) = {A 1,..., A k } and

7 RC Simulates RA. Lemma: For every RA expression E(A 1... A k ) there exists a DRC formula F with F V (F ) = {A 1,..., A k } and 7 RC Simulates RA. We now show that DRC (and hence TRC) is at least as expressive as RA. That is, given an RA expression E that mentions at most C, there is an equivalent DRC expression E that mentions

More information

Relational Algebra Part 1. Definitions.

Relational Algebra Part 1. Definitions. .. Cal Poly pring 2016 CPE/CC 365 Introduction to Database ystems Alexander Dekhtyar Eriq Augustine.. elational Algebra Notation, T,,... relations. t, t 1, t 2,... tuples of relations. t (n tuple with

More information

UVA UVA UVA UVA. Database Design. Relational Database Design. Functional Dependency. Loss of Information

UVA UVA UVA UVA. Database Design. Relational Database Design. Functional Dependency. Loss of Information Relational Database Design Database Design To generate a set of relation schemas that allows - to store information without unnecessary redundancy - to retrieve desired information easily Approach - design

More information

A Dichotomy. in in Probabilistic Databases. Joint work with Robert Fink. for Non-Repeating Queries with Negation Queries with Negation

A Dichotomy. in in Probabilistic Databases. Joint work with Robert Fink. for Non-Repeating Queries with Negation Queries with Negation Dichotomy for Non-Repeating Queries with Negation Queries with Negation in in Probabilistic Databases Robert Dan Olteanu Fink and Dan Olteanu Joint work with Robert Fink Uncertainty in Computation Simons

More information

Relational Algebra on Bags. Why Bags? Operations on Bags. Example: Bag Selection. σ A+B < 5 (R) = A B

Relational Algebra on Bags. Why Bags? Operations on Bags. Example: Bag Selection. σ A+B < 5 (R) = A B Relational Algebra on Bags Why Bags? 13 14 A bag (or multiset ) is like a set, but an element may appear more than once. Example: {1,2,1,3} is a bag. Example: {1,2,3} is also a bag that happens to be a

More information

Database Systems Relational Algebra. A.R. Hurson 323 CS Building

Database Systems Relational Algebra. A.R. Hurson 323 CS Building Relational Algebra A.R. Hurson 323 CS Building Relational Algebra Relational model is based on set theory. A relation is simply a set. The relational algebra is a set of high level operators that operate

More information

CS156: The Calculus of Computation Zohar Manna Winter 2010

CS156: The Calculus of Computation Zohar Manna Winter 2010 Page 3 of 35 Page 4 of 35 quantifiers CS156: The Calculus of Computation Zohar Manna Winter 2010 Chapter 2: First-Order Logic (FOL) existential quantifier x. F [x] there exists an x such that F [x] Note:

More information

Relational completeness of query languages for annotated databases

Relational completeness of query languages for annotated databases Relational completeness of query languages for annotated databases Floris Geerts 1,2 and Jan Van den Bussche 1 1 Hasselt University/Transnational University Limburg 2 University of Edinburgh Abstract.

More information

CS632 Notes on Relational Query Languages I

CS632 Notes on Relational Query Languages I CS632 Notes on Relational Query Languages I A. Demers 6 Feb 2003 1 Introduction Here we define relations, and introduce our notational conventions, which are taken almost directly from [AD93]. We begin

More information

ER Modelling: Summary

ER Modelling: Summary ER Modelling: Summary ER describes the world (the set of possible worlds) what it is and the laws of this world ER is static: it does not describe (legal) transitions Useful for two purposes build software

More information

Automata and Languages

Automata and Languages Automata and Languages Prof. Mohamed Hamada Software Engineering Lab. The University of Aizu Japan Mathematical Background Mathematical Background Sets Relations Functions Graphs Proof techniques Sets

More information

CS5300 Database Systems

CS5300 Database Systems CS5300 Database Systems Relational Algebra A.R. Hurson 323 CS Building hurson@mst.edu This module is intended to introduce: relational algebra as the backbone of relational model, and set of operations

More information

Plan of the lecture. G53RDB: Theory of Relational Databases Lecture 2. More operations: renaming. Previous lecture. Renaming.

Plan of the lecture. G53RDB: Theory of Relational Databases Lecture 2. More operations: renaming. Previous lecture. Renaming. Plan of the lecture G53RDB: Theory of Relational Lecture 2 Natasha Alechina chool of Computer cience & IT nza@cs.nott.ac.uk Renaming Joins Definability of intersection Division ome properties of relational

More information

ETIKA V PROFESII PSYCHOLÓGA

ETIKA V PROFESII PSYCHOLÓGA P r a ž s k á v y s o k á š k o l a p s y c h o s o c i á l n í c h s t u d i í ETIKA V PROFESII PSYCHOLÓGA N a t á l i a S l o b o d n í k o v á v e d ú c i p r á c e : P h D r. M a r t i n S t r o u

More information

An Example file... log.txt

An Example file... log.txt # ' ' Start of fie & %$ " 1 - : 5? ;., B - ( * * B - ( * * F I / 0. )- +, * ( ) 8 8 7 /. 6 )- +, 5 5 3 2( 7 7 +, 6 6 9( 3 5( ) 7-0 +, => - +< ( ) )- +, 7 / +, 5 9 (. 6 )- 0 * D>. C )- +, (A :, C 0 )- +,

More information

cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska

cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska LECTURE 1 Course Web Page www3.cs.stonybrook.edu/ cse303 The webpage contains: lectures notes slides; very detailed solutions to

More information

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir)

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir) BİL 354 Veritnı Sistemleri Reltionl lger (İlişkisel Ceir) Reltionl Queries Query lnguges: llow mnipultion nd retrievl of dt from dtse. Reltionl model supports simple, powerful QLs: Strong forml foundtion

More information

CMPS 277 Principles of Database Systems. Lecture #9

CMPS 277 Principles of Database Systems.  Lecture #9 CMPS 277 Principles of Database Systems http://www.soe.classes.edu/cmps277/winter10 Lecture #9 1 Summary The Query Evaluation Problem for Relational Calculus is PSPACEcomplete. The Query Equivalence Problem

More information

Movies Title Director Actor

Movies Title Director Actor Movies Title Director Actor The Trouble with Harry Hitchcock Gwenn The Trouble with Harry Hitchcock Forsythe The Trouble with Harry Hitchcock MacLaine The Trouble with Harry Hitchcock Hitchcock Cries and

More information

Sets are one of the basic building blocks for the types of objects considered in discrete mathematics.

Sets are one of the basic building blocks for the types of objects considered in discrete mathematics. Section 2.1 Introduction Sets are one of the basic building blocks for the types of objects considered in discrete mathematics. Important for counting. Programming languages have set operations. Set theory

More information

With Question/Answer Animations. Chapter 2

With Question/Answer Animations. Chapter 2 With Question/Answer Animations Chapter 2 Chapter Summary Sets The Language of Sets Set Operations Set Identities Functions Types of Functions Operations on Functions Sequences and Summations Types of

More information

Foundations of Databases

Foundations of Databases Foundations of Databases (Slides adapted from Thomas Eiter, Leonid Libkin and Werner Nutt) Foundations of Databases 1 Quer optimization: finding a good wa to evaluate a quer Queries are declarative, and

More information

GAV-sound with conjunctive queries

GAV-sound with conjunctive queries GAV-sound with conjunctive queries Source and global schema as before: source R 1 (A, B),R 2 (B,C) Global schema: T 1 (A, C), T 2 (B,C) GAV mappings become sound: T 1 {x, y, z R 1 (x,y) R 2 (y,z)} T 2

More information

T i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a. A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r )

T i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a. A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r ) v e r. E N G O u t l i n e T i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r ) C o n t e n t s : T h i s w o

More information

. ffflffluary 7, 1855.

. ffflffluary 7, 1855. x B B - Y 8 B > ) - ( vv B ( v v v (B/ x< / Y 8 8 > [ x v 6 ) > ( - ) - x ( < v x { > v v q < 8 - - - 4 B ( v - / v x [ - - B v B --------- v v ( v < v v v q B v B B v?8 Y X $ v x B ( B B B B ) ( - v -

More information

Sets McGraw-Hill Education

Sets McGraw-Hill Education Sets A set is an unordered collection of objects. The objects in a set are called the elements, or members of the set. A set is said to contain its elements. The notation a A denotes that a is an element

More information

This document has been prepared by Sunder Kidambi with the blessings of

This document has been prepared by Sunder Kidambi with the blessings of Ö À Ö Ñ Ø Ò Ñ ÒØ Ñ Ý Ò Ñ À Ö Ñ Ò Ú º Ò Ì ÝÊ À Å Ú Ø Å Ê ý Ú ÒØ º ÝÊ Ú Ý Ê Ñ º Å º ² ºÅ ý ý ý ý Ö Ð º Ñ ÒÜ Æ Å Ò Ñ Ú «Ä À ý ý This document has been prepared by Sunder Kidambi with the blessings of Ö º

More information

Relational Algebra SPJRUD

Relational Algebra SPJRUD Relational Algebra SPJRUD Jef Wijsen Université de Mons (UMONS) May 14, 2018 Jef Wijsen (Université de Mons (UMONS)) SPJRUD May 14, 2018 1 / 1 Tabular Representation The table A B C 1 3 2 1 4 1 2 4 2 2

More information

Chapter 7: Relational Database Design

Chapter 7: Relational Database Design 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

More information

Computational Logic. Relational Query Languages with Negation. Free University of Bozen-Bolzano, Werner Nutt

Computational Logic. Relational Query Languages with Negation. Free University of Bozen-Bolzano, Werner Nutt Computational Logic Free University of Bozen-Bolzano, 2010 Werner Nutt (Slides adapted from Thomas Eiter and Leonid Libkin) Computational Logic 1 Queries with All Who are the directors whose movies are

More information

03 Review of First-Order Logic

03 Review of First-Order Logic CAS 734 Winter 2014 03 Review of First-Order Logic William M. Farmer Department of Computing and Software McMaster University 18 January 2014 What is First-Order Logic? First-order logic is the study of

More information

First Steps in Relational Lattice

First Steps in Relational Lattice First Steps in Relational Lattice MARSHALL SPIGHT Marshall.Spight@gmai1.com VADIM TROPASHKO Vadim.Tropashko@orcl.com Relational lattice reduces the set of si classic relational algebra operators to two

More information

Notes. Corneliu Popeea. May 3, 2013

Notes. Corneliu Popeea. May 3, 2013 Notes Corneliu Popeea May 3, 2013 1 Propositional logic Syntax We rely on a set of atomic propositions, AP, containing atoms like p, q. A propositional logic formula φ Formula is then defined by the following

More information

Chapter 7: Relational Database Design. Chapter 7: Relational Database Design

Chapter 7: Relational Database Design. Chapter 7: Relational Database Design 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

More information

â, Đ (Very Long Baseline Interferometry, VLBI)

â, Đ (Very Long Baseline Interferometry, VLBI) ½ 55 ½ 5 Í Vol.55 No.5 2014 9 ACTA ASTRONOMICA SINICA Sep., 2014» Á Çý è 1,2 1,2 å 1,2 Ü ô 1,2 ï 1,2 ï 1,2 à 1,3 Æ Ö 3 ý (1 Á Í 200030) (2 Á Í û À 210008) (3 541004) ÇÅè 1.5 GHz Á è, î Í, û ÓÆ Å ò ½Ò ¼ï.

More information

The Structure of Inverses in Schema Mappings

The Structure of Inverses in Schema Mappings To appear: J. ACM The Structure of Inverses in Schema Mappings Ronald Fagin and Alan Nash IBM Almaden Research Center 650 Harry Road San Jose, CA 95120 Contact email: fagin@almaden.ibm.com Abstract A schema

More information

On Monoids over which All Strongly Flat Right S-Acts Are Regular

On Monoids over which All Strongly Flat Right S-Acts Are Regular Æ26 Æ4 ² Vol.26, No.4 2006µ11Â JOURNAL OF MATHEMATICAL RESEARCH AND EXPOSITION Nov., 2006 Article ID: 1000-341X(2006)04-0720-05 Document code: A On Monoids over which All Strongly Flat Right S-Acts Are

More information

hal , version 1-21 Oct 2009

hal , version 1-21 Oct 2009 ON SKOLEMISING ZERMELO S SET THEORY ALEXANDRE MIQUEL Abstract. We give a Skolemised presentation of Zermelo s set theory (with notations for comprehension, powerset, etc.) and show that this presentation

More information

Query answering using views

Query answering using views Query answering using views General setting: database relations R 1,...,R n. Several views V 1,...,V k are defined as results of queries over the R i s. We have a query Q over R 1,...,R n. Question: Can

More information

COSC 430 Advanced Database Topics. Lecture 2: Relational Theory Haibo Zhang Computer Science, University of Otago

COSC 430 Advanced Database Topics. Lecture 2: Relational Theory Haibo Zhang Computer Science, University of Otago COSC 430 Advanced Database Topics Lecture 2: Relational Theory Haibo Zhang Computer Science, University of Otago Learning objectives and references You should be able to: define the elements of the relational

More information

Chapter 2 Sets, Relations and Functions

Chapter 2 Sets, Relations and Functions Chapter 2 Sets, Relations and Functions Key Topics Sets Set Operations Russell s Paradox Relations Composition of Relations Reflexive, Symmetric and Transitive Relations Functions Partial and Total Functions

More information

Querying Fuzzy Relational Databases Through Fuzzy Domain Calculus

Querying Fuzzy Relational Databases Through Fuzzy Domain Calculus Querying Fuzzy Relational Databases Through Fuzzy Domain Calculus 1, 2 a 3 Jose Galindo, * Juan Miguel Medina, M Carmen Aranda 1 Departamento Lenguajes y Ciencias de la Computacion, Universidad de Malaga,

More information

Definite Logic Programs

Definite Logic Programs Chapter 2 Definite Logic Programs 2.1 Definite Clauses The idea of logic programming is to use a computer for drawing conclusions from declarative descriptions. Such descriptions called logic programs

More information

Chapter Summary. Sets The Language of Sets Set Operations Set Identities Functions Types of Functions Operations on Functions Computability

Chapter Summary. Sets The Language of Sets Set Operations Set Identities Functions Types of Functions Operations on Functions Computability Chapter 2 1 Chapter Summary Sets The Language of Sets Set Operations Set Identities Functions Types of Functions Operations on Functions Computability Sequences and Summations Types of Sequences Summation

More information

From Constructibility and Absoluteness to Computability and Domain Independence

From Constructibility and Absoluteness to Computability and Domain Independence From Constructibility and Absoluteness to Computability and Domain Independence Arnon Avron School of Computer Science Tel Aviv University, Tel Aviv 69978, Israel aa@math.tau.ac.il Abstract. Gödel s main

More information

Subrings and Ideals 2.1 INTRODUCTION 2.2 SUBRING

Subrings and Ideals 2.1 INTRODUCTION 2.2 SUBRING Subrings and Ideals Chapter 2 2.1 INTRODUCTION In this chapter, we discuss, subrings, sub fields. Ideals and quotient ring. We begin our study by defining a subring. If (R, +, ) is a ring and S is a non-empty

More information

CS 347 Distributed Databases and Transaction Processing Notes03: Query Processing

CS 347 Distributed Databases and Transaction Processing Notes03: Query Processing CS 347 Distributed Databases and Transaction Processing Notes03: Query Processing Hector Garcia-Molina Zoltan Gyongyi CS 347 Notes 03 1 Query Processing! Decomposition! Localization! Optimization CS 347

More information

Comp 5311 Database Management Systems. 5. Functional Dependencies Exercises

Comp 5311 Database Management Systems. 5. Functional Dependencies Exercises Comp 5311 Database Management Systems 5. Functional Dependencies Exercises 1 Assume the following table contains the only set of tuples that may appear in a table R. Which of the following FDs hold in

More information

arxiv: v1 [cs.db] 1 Sep 2015

arxiv: v1 [cs.db] 1 Sep 2015 Decidability of Equivalence of Aggregate Count-Distinct Queries Babak Bagheri Harari Val Tannen Computer & Information Science Department University of Pennsylvania arxiv:1509.00100v1 [cs.db] 1 Sep 2015

More information

hp calculators HP 35s Solving for roots Roots of an equation Using the SOLVE function Practice solving problems involving roots

hp calculators HP 35s Solving for roots Roots of an equation Using the SOLVE function Practice solving problems involving roots Roots of an equation Using the SOLVE function Practice solving problems involving roots Roots of an equation The roots of an equation are values of X where the value of Y is equal to zero. For example,

More information

Lecture 2: Syntax. January 24, 2018

Lecture 2: Syntax. January 24, 2018 Lecture 2: Syntax January 24, 2018 We now review the basic definitions of first-order logic in more detail. Recall that a language consists of a collection of symbols {P i }, each of which has some specified

More information

6 The Relational Data Model: Algebraic operations on tabular data

6 The Relational Data Model: Algebraic operations on tabular data 6 The Relational Data Model: Algebraic operations on tabular data 6.1 Basic idea of relational languages 6.2 Relational Algebra operations 6.3 Relational Algebra: Syntax and Semantics 6.4. More Operators

More information

Information Systems for Engineers. Exercise 5. ETH Zurich, Fall Semester Hand-out Due

Information Systems for Engineers. Exercise 5. ETH Zurich, Fall Semester Hand-out Due Information Systems for Engineers Exercise 5 ETH Zurich, Fall Semester 2017 Hand-out 27.10.2017 Due 03.11.2017 Reading material: Chapter 2.4 in [1]. Lecture slides 4. 1. Given the two tables below, write

More information

F O R SOCI AL WORK RESE ARCH

F O R SOCI AL WORK RESE ARCH 7 TH EUROPE AN CONFERENCE F O R SOCI AL WORK RESE ARCH C h a l l e n g e s i n s o c i a l w o r k r e s e a r c h c o n f l i c t s, b a r r i e r s a n d p o s s i b i l i t i e s i n r e l a t i o n

More information

B œ c " " ã B œ c 8 8. such that substituting these values for the B 3 's will make all the equations true

B œ c   ã B œ c 8 8. such that substituting these values for the B 3 's will make all the equations true System of Linear Equations variables Ð unknowns Ñ B" ß B# ß ÞÞÞ ß B8 Æ Æ Æ + B + B ÞÞÞ + B œ, "" " "# # "8 8 " + B + B ÞÞÞ + B œ, #" " ## # #8 8 # ã + B + B ÞÞÞ + B œ, 3" " 3# # 38 8 3 ã + 7" B" + 7# B#

More information

Applications of Discrete Mathematics to the Analysis of Algorithms

Applications of Discrete Mathematics to the Analysis of Algorithms Applications of Discrete Mathematics to the Analysis of Algorithms Conrado Martínez Univ. Politècnica de Catalunya, Spain May 2007 Goal Given some algorithm taking inputs from some set Á, we would like

More information

Exercise Sheet 1: Relational Algebra David Carral, Markus Krötzsch Database Theory, 17 April, Summer Term 2018

Exercise Sheet 1: Relational Algebra David Carral, Markus Krötzsch Database Theory, 17 April, Summer Term 2018 Exercise Sheet 1: Relational Algebra David Carral, Markus Krötzsch Database Theory, 17 April, Summer Term 2018 Exercise 1.1. Consider a cinema database with tables of the following form (adapted from a

More information

CS 4604: Introduc0on to Database Management Systems. B. Aditya Prakash Lecture #3: SQL---Part 1

CS 4604: Introduc0on to Database Management Systems. B. Aditya Prakash Lecture #3: SQL---Part 1 CS 4604: Introduc0on to Database Management Systems B. Aditya Prakash Lecture #3: SQL---Part 1 Announcements---Project Goal: design a database system applica=on with a web front-end Project Assignment

More information

DATABASE DESIGN I - 1DL300

DATABASE DESIGN I - 1DL300 DATABASE DESIGN I - DL300 Fll 00 An introductory course on dtse systems http://www.it.uu.se/edu/course/homepge/dstekn/ht0/ Mnivskn Sesn Uppsl Dtse Lortory Deprtment of Informtion Technology, Uppsl University,

More information

I N A C O M P L E X W O R L D

I N A C O M P L E X W O R L D IS L A M I C E C O N O M I C S I N A C O M P L E X W O R L D E x p l o r a t i o n s i n A g-b eanste d S i m u l a t i o n S a m i A l-s u w a i l e m 1 4 2 9 H 2 0 0 8 I s l a m i c D e v e l o p m e

More information

Approximate Rewriting of Queries Using Views

Approximate Rewriting of Queries Using Views Approximate Rewriting of Queries Using Views Foto Afrati 1, Manik Chandrachud 2, Rada Chirkova 2, and Prasenjit Mitra 3 1 School of Electrical and Computer Engineering National Technical University of

More information

DATABASTEKNIK - 1DL116

DATABASTEKNIK - 1DL116 DATABASTEKNIK - DL6 Spring 004 An introductury course on dtse systems http://user.it.uu.se/~udl/dt-vt004/ Kjell Orsorn Uppsl Dtse Lortory Deprtment of Informtion Technology, Uppsl University, Uppsl, Sweden

More information

BOOLEAN ALGEBRA INTRODUCTION SUBSETS

BOOLEAN ALGEBRA INTRODUCTION SUBSETS BOOLEAN ALGEBRA M. Ragheb 1/294/2018 INTRODUCTION Modern algebra is centered around the concept of an algebraic system: A, consisting of a set of elements: ai, i=1, 2,, which are combined by a set of operations

More information

Homomorphism Preservation Theorem. Albert Atserias Universitat Politècnica de Catalunya Barcelona, Spain

Homomorphism Preservation Theorem. Albert Atserias Universitat Politècnica de Catalunya Barcelona, Spain Homomorphism Preservation Theorem Albert Atserias Universitat Politècnica de Catalunya Barcelona, Spain Structure of the talk 1. Classical preservation theorems 2. Preservation theorems in finite model

More information

But RECAP. Why is losslessness important? An Instance of Relation NEWS. Suppose we decompose NEWS into: R1(S#, Sname) R2(City, Status)

But RECAP. Why is losslessness important? An Instance of Relation NEWS. Suppose we decompose NEWS into: R1(S#, Sname) R2(City, Status) So far we have seen: RECAP How to use functional dependencies to guide the design of relations How to modify/decompose relations to achieve 1NF, 2NF and 3NF relations But How do we make sure the decompositions

More information

Instructor: Amol Deshpande

Instructor: Amol Deshpande Instructor: Amol Deshpande amol@cs.umd.edu } New topics to discuss More constructs in E/R modeling Conver@ng from E/R to rela@onal schema Crea@ng some E/R models Ruby on Rails } Other things Grading of

More information

Fuzzy and Rough Sets Part I

Fuzzy and Rough Sets Part I Fuzzy and Rough Sets Part I Decision Systems Group Brigham and Women s Hospital, Harvard Medical School Harvard-MIT Division of Health Sciences and Technology Aim Present aspects of fuzzy and rough sets.

More information

Databases. Exercises on Relational Algebra

Databases. Exercises on Relational Algebra Databases Exercises on Relational Algebra The Lab Sessions Giacomo Bergami (giacomo.bergami2@unibo.it) bergami.co.nr 2016/10/07 Keys and Superkeys Relational Algebra (I) Negation Minimum 2016/10/14 Relational

More information

Provenance Semirings. Todd Green Grigoris Karvounarakis Val Tannen. presented by Clemens Ley

Provenance Semirings. Todd Green Grigoris Karvounarakis Val Tannen. presented by Clemens Ley Provenance Semirings Todd Green Grigoris Karvounarakis Val Tannen presented by Clemens Ley place of origin Provenance Semirings Todd Green Grigoris Karvounarakis Val Tannen presented by Clemens Ley place

More information

arxiv: v1 [cs.db] 21 Sep 2016

arxiv: v1 [cs.db] 21 Sep 2016 Ladan Golshanara 1, Jan Chomicki 1, and Wang-Chiew Tan 2 1 State University of New York at Buffalo, NY, USA ladangol@buffalo.edu, chomicki@buffalo.edu 2 Recruit Institute of Technology and UC Santa Cruz,

More information

EECS-3421a: Test #2 Electrical Engineering & Computer Science York University

EECS-3421a: Test #2 Electrical Engineering & Computer Science York University 18 November 2015 EECS-3421a: Test #2 1 of 16 EECS-3421a: Test #2 Electrical Engineering & Computer Science York University Family Name: Given Name: Student#: CSE Account: Instructor: Parke Godfrey Exam

More information

Chapter 2. Linear Algebra. rather simple and learning them will eventually allow us to explain the strange results of

Chapter 2. Linear Algebra. rather simple and learning them will eventually allow us to explain the strange results of Chapter 2 Linear Algebra In this chapter, we study the formal structure that provides the background for quantum mechanics. The basic ideas of the mathematical machinery, linear algebra, are rather simple

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Languages. Theory I: Database Foundations. Relational Algebra. Paradigms. Projection. Basic Operators. Jan-Georg Smaus (Georg Lausen)

Languages. Theory I: Database Foundations. Relational Algebra. Paradigms. Projection. Basic Operators. Jan-Georg Smaus (Georg Lausen) Languages Theory I: Database Foundations Jan-Georg Smaus (Georg Lausen) Paradigms 1. Languages: Relational Algebra Projection Union and Difference Summary 26.7.2011 Relational algebra Relational calculus

More information

Packet #2: Set Theory & Predicate Calculus. Applied Discrete Mathematics

Packet #2: Set Theory & Predicate Calculus. Applied Discrete Mathematics CSC 224/226 Notes Packet #2: Set Theory & Predicate Calculus Barnes Packet #2: Set Theory & Predicate Calculus Applied Discrete Mathematics Table of Contents Full Adder Information Page 1 Predicate Calculus

More information

Knowledge Discovery. Zbigniew W. Ras. Polish Academy of Sciences, Dept. of Comp. Science, Warsaw, Poland

Knowledge Discovery. Zbigniew W. Ras. Polish Academy of Sciences, Dept. of Comp. Science, Warsaw, Poland Handling Queries in Incomplete CKBS through Knowledge Discovery Zbigniew W. Ras University of orth Carolina, Dept. of Comp. Science, Charlotte,.C. 28223, USA Polish Academy of Sciences, Dept. of Comp.

More information

First-Order Logic (FOL)

First-Order Logic (FOL) First-Order Logic (FOL) Also called Predicate Logic or Predicate Calculus 2. First-Order Logic (FOL) FOL Syntax variables x, y, z, constants a, b, c, functions f, g, h, terms variables, constants or n-ary

More information

Sets, Logic, Relations, and Functions

Sets, Logic, Relations, and Functions Sets, Logic, Relations, and Functions Andrew Kay September 28, 2014 Abstract This is an introductory text, not a comprehensive study; these notes contain mainly definitions, basic results, and examples.

More information

1 First-order logic. 1 Syntax of first-order logic. 2 Semantics of first-order logic. 3 First-order logic queries. 2 First-order query evaluation

1 First-order logic. 1 Syntax of first-order logic. 2 Semantics of first-order logic. 3 First-order logic queries. 2 First-order query evaluation Knowledge Bases and Databases Part 1: First-Order Queries Diego Calvanese Faculty of Computer Science Master of Science in Computer Science A.Y. 2007/2008 Overview of Part 1: First-order queries 1 First-order

More information

Fundamentos lógicos de bases de datos (Logical foundations of databases)

Fundamentos lógicos de bases de datos (Logical foundations of databases) 20/7/2015 ECI 2015 Buenos Aires Fundamentos lógicos de bases de datos (Logical foundations of databases) Diego Figueira Gabriele Puppis CNRS LaBRI About the speakers Gabriele Puppis PhD from Udine (Italy)

More information

A Language for Task Orchestration and its Semantic Properties

A Language for Task Orchestration and its Semantic Properties DEPARTMENT OF COMPUTER SCIENCES A Language for Task Orchestration and its Semantic Properties David Kitchin, William Cook and Jayadev Misra Department of Computer Science University of Texas at Austin

More information

CSE 562 Database Systems

CSE 562 Database Systems Outline Query Optimization CSE 562 Database Systems Query Processing: Algebraic Optimization Some slides are based or modified from originals by Database Systems: The Complete Book, Pearson Prentice Hall

More information

Today s topics. Introduction to Set Theory ( 1.6) Naïve set theory. Basic notations for sets

Today s topics. Introduction to Set Theory ( 1.6) Naïve set theory. Basic notations for sets Today s topics Introduction to Set Theory ( 1.6) Sets Definitions Operations Proving Set Identities Reading: Sections 1.6-1.7 Upcoming Functions A set is a new type of structure, representing an unordered

More information

07 Equational Logic and Algebraic Reasoning

07 Equational Logic and Algebraic Reasoning CAS 701 Fall 2004 07 Equational Logic and Algebraic Reasoning Instructor: W. M. Farmer Revised: 17 November 2004 1 What is Equational Logic? Equational logic is first-order logic restricted to languages

More information