Chapter 3 Relational Model
|
|
- Oswin Woods
- 5 years ago
- Views:
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 (So far) Basic operations: Selection ( σ ) Selects a subset of rows from relation. Projection ( π ) Deletes unwanted columns from relation. Cross-product
More informationCS54100: 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 informationRELATIONAL 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 informationRelational 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 informationRelational 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 informationQuery 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 informationAdvanced 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 informationDatabase 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 informationSchedule. 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 informationIntroduction 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 informationINTRODUCTION 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 informationDatabases 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 informationRelational 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 informationDatabase 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 informationGeneral 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 information7 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 informationRelational 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 informationUVA 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 informationA 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 informationRelational 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 informationDatabase 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 informationCS156: 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 informationRelational 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 informationCS632 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 informationER 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 informationAutomata 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 informationCS5300 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 informationPlan 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 informationETIKA 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 informationAn 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 informationcse303 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 informationBİL 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 informationCMPS 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 informationMovies 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 informationSets 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 informationWith 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 informationFoundations 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 informationGAV-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 informationT 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.
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 informationSets 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 informationThis 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 informationRelational 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 informationChapter 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 informationComputational 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 information03 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 informationFirst 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 informationNotes. 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 informationChapter 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 informationâ, 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 informationThe 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 informationOn 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 informationhal , 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 informationQuery 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 informationCOSC 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 informationChapter 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 informationQuerying 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 informationDefinite 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 informationChapter 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 informationFrom 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 informationSubrings 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 informationCS 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 informationComp 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 informationarxiv: 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 informationhp 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 informationLecture 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 information6 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 informationInformation 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 informationF 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 informationB 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 informationApplications 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 informationExercise 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 informationCS 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 informationDATABASE 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 informationI 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 informationApproximate 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 informationDATABASTEKNIK - 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 informationBOOLEAN 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 informationHomomorphism 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 informationBut 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 informationInstructor: 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 informationFuzzy 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 informationDatabases. 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 informationProvenance 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 informationarxiv: 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 informationEECS-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 informationChapter 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 informationP 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 informationLanguages. 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 informationPacket #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 informationKnowledge 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 informationFirst-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 informationSets, 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 information1 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 informationFundamentos 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 informationA 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 informationCSE 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 informationToday 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 information07 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