skip to content
Database systems : the complete book. Preview this item
ClosePreview this item
Checking...

Database systems : the complete book.

Author: Hector Garcia-Molina; Jeffrey D Ullman; Jennifer Widom
Publisher: Upper Saddle River : Pearson/Prentice Hall, 2009.
Edition/Format:   Book : English : 2nd edView all editions and formats
Database:WorldCat
Rating:

(not yet rated) 0 with reviews - Be the first.

 

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Document Type: Book
All Authors / Contributors: Hector Garcia-Molina; Jeffrey D Ullman; Jennifer Widom
ISBN: 0131873253 9780131873254
OCLC Number: 244097685
Description: 1203 blz. ; .. cm.
Contents: PRIOR EDITION TOC 1 The Worlds of Database Systems 1.1 The Evolution of Database Systems 1.1.1 Early Database Management Systems 1.1.2 Relational Database Systems 1.1.3 Smaller and Smaller Systems 1.1.4 Bigger and Bigger Systems 1.1.5 Client-Server and Multi-Tier Architectures 1.1.6 Multimedia Data 1.1.7 Information Integration 1.2 Overview of a Database Management System 1.2.1 Data-Definition Language Commands 1.2.2 Overview of Query Processing 1.2.3 Storage and Buffer Management 1.2.4 Transaction Processing 1.2.5 The Query Processor 1.3 Outline of Database-System Studies 1.3.1 Database Design 1.3.2 Database Programming 1.3.3 Database System Implementation 1.3.4 Information Integration Overview 1.4 Summary of Chapter 1 1.5 References for Chapter 1 2 The Entity-Relationship Data Model 2.1 Elements of the E/R Model 2.1.1 Entity Sets 2.1.2 Attributes 2.1.3 Relationships 2.1.4 Entity-Relationship Diagrams 2.1.5 Instances of an E/R Diagram 2.1.6 Multiplicity of Binary E/R Relationships 2.1.7 Multiway Relationships 2.1.8 Roles in Relationships 2.1.9 Attributes on Relationships 2.1.10 Converting Multiway Relationships to Binary 2.1.11 Subclasses in the E/R Model 2.1.12 Exercises for Section 2.1 2.2 Design Principles 2.2.1 Faithfulness 2.2.2 Avoiding Redundancy 2.2.3 Simplicity Counts 2.2.4 Choosing the Right Relationships 2.2.5 Picking the Right Kind of Element 2.2.6 Exercises for Section 2.2 2.3 The Modeling of Constraints 2.3.1 Classification of Constraints 2.3.2 Keys in the E/R Model 2.3.3 Representing Keys in the E/R Model 2.3.4 Single-Value Constraints 2.3.5 Referential Integrity 2.3.6 Referential Integrity in E/R Diagrams 2.3.7 Other Kinds of Constraints 2.3.8 Exercises for Section 2.3 2.4 Weak Entity Sets 2.4.1 Causes of Weak Entity Sets 2.4.2 Requirements for Weak Entity Sets 2.4.3 Weak Entity Set Notation 2.4.4 Exercises for Section 2.4 2.5 Summary of Chapter 2 2.6 References for Chapter 2 3 The Relational Data Model 3.1 Basics of the Relational Model 3.1.1 Attributes 3.1.2 Schemas 3.1.3 Tuples 3.1.4 Domains 3.1.5 Equivalent Representations of a Relation 3.1.6 Relation Instances 3.1.7 Exercises for Section 3.1 3.2 From E/R Diagrams to Relational Designs 3.2.1 From Entity Sets to Relations 3.2.2 From E/R Relationships to Relations 3.2.3 Combining Relations 3.2.4 Handling Weak Entity Sets 3.2.5 Exercises for Section 3.2 3.3 Converting Subclass Structures to Relations 3.3.1 E/R-Style Conversion 3.3.2 An Object-Oriented Approach 3.3.3 Using Null Values to Combine Relations 3.3.4 Comparison of Approaches 3.3.5 Exercises for Section 3.3 3.4 Functional Dependencies 3.4.1 Definition of Functional Dependency 3.4.2 Keys of Relations 3.4.3 Superkeys 3.4.4 Discovering Keys for Relations 3.4.5 Exercises for Section 3.4 3.5 Rules About Functional Dependencies 3.5.1 The Splitting/Combining Rule 3.5.2 Trivial Functional Dependencies 3.5.3 Computing the Closure of Attributes 3.5.4 Why the Closure Algorithm Works 3.5.5 The Transitive Rule 3.5.6 Closing Sets of Functional Dependencies 3.5.7 Projecting Functional Dependencies 3.5.8 Exercises for Section 3.5 3.6 Design of Relational Database Schemas 3.6.1 Anomalies 3.6.2 Decomposing Relations 3.6.3 Boyce-Codd Normal Form 3.6.4 Decomposition into BCNF 3.6.5 Recovering Information from a Decomposition 3.6.6 Third Normal Form 3.6.7 Exercises for Section 3.6 3.7 Multivalued Dependencies 3.7.1 Attribute Independence and Its Consequent Redundancy 3.7.2 Definition of Multivalued Dependencies 3.7.3 Reasoning About Multivalued Dependencies 3.7.4 Fourth Normal Form 3.7.5 Decomposition into Fourth Normal Form 3.7.6 Relationships Among Normal Forms 3.7.7 Exercises for Section 3.7 3.8 Summary of Chapter 3 3.9 References for Chapter 3 4 Other Data Models 4.1 Review of Object-Oriented Concepts 4.1.1 The Type System 4.1.2 Classes and Objects 4.1.3 Object Identity 4.1.4 Methods 4.1.5 Class Hierarchies 4.2 Introduction to ODL 4.2.1 Object-Oriented Design 4.2.2 Class Declarations 4.2.3 Attributes in ODL 4.2.4 Relationships in ODL 4.2.5 Inverse Relationships 4.2.6 Multiplicity of Relationships 4.2.7 Methods in ODL 4.2.8 Types in ODL 4.2.9 Exercises for Section 4.2 4.3 Additional ODL Concepts 4.3.1 Multiway Relationships in ODL 4.3.2 Subclasses in ODL 4.3.3 Multiple Inheritance in ODL 4.3.4 Extents 4.3.5 Declaring Keys in ODL 4.3.6 Exercises for Section 4.3 4.4 From ODL Designs to Relational Designs 4.4.1 From ODL Attributes to Relational Attributes 4.4.2 Nonatomic Attributes in Classes 4.4.3 Representing Set-Valued Attributes 4.4.4 Representing Other Type Constructors 4.4.5 Representing ODL Relationships 4.4.6 What If There Is No Key? 4.4.7 Exercises for Section 4.4 4.5 The Object-Relational Model 4.5.1 From Relations to Object-Relations 4.5.2 Nested Relations 4.5.3 References 4.5.4 Object-Oriented Versus Object-Relational 4.5.5 From ODL Designs to Object-Relational Designs 4.5.6 Exercises for Section 4.5 4.6 Semistructured Data 4.6.1 Motivation for the Semistructured-Data Model 4.6.2 Semistructured Data Representation 4.6.3 Information Integration Via Semistructured Data 4.6.4 Exercises for Section 4.6 4.7 XML and Its Data Model 4.7.1 Semantic Tags 4.7.2 Well-Formed XML 4.7.3 Document Type Definitions 4.7.4 Using a DTD 4.7.5 Attribute Lists 4.7.6 Exercises for Section 4.7 4.8 Summary of Chapter 4 4.9 References for Chapter 4 5 Relational Algebra 5.1 An Example Database Schema 5.2 An Algebra of Relational Operations 5.2.1 Basics of Relational Algebra 5.2.2 Set Operations on Relations 5.2.3 Projection 5.2.4 Selection 5.2.5 Cartesian Product 5.2.6 Natural Joins 5.2.7 Theta-Joins 5.2.8 Combining Operations to Form Queries 5.2.9 Renaming 5.2.10 Dependent and Independent Operations 5.2.11 A Linear Notation for Algebraic Expressions 5.2.12 Exercises for Section 5.2 5.3 Relational Operations on Bags 5.3.1 Why Bags? 5.3.2 Union, Intersection, and Difference of Bags 5.3.3 Projection of Bags 5.3.4 Selection on Bags 5.3.5 Product of Bags 5.3.6 Joins of Bags 5.3.7 Exercises for Section 5.3 5.4 Extended Operators of Relational Algebra 5.4.1 Duplicate Elimination 5.4.2 Aggregation Operators 5.4.3 Grouping 5.4.4 The Grouping Operator 5.4.5 Extending the Projection Operator 5.4.6 The Sorting Operator 5.4.7 Outerjoins 5.4.8 Exercises for Section 5.4 5.5 Constraints on Relations 5.5.1 Relational Algebra as a Constraint Language 5.5.2 Referential Integrity Constraints 5.5.3 Additional Constraint Examples 5.5.4 Exercises for Section 5.5 5.6 Summary of Chapter 5 5.7 References for Chapter 5 6 The Database Language SQL 6.1 Simple Queries in SQL 6.1.1 Projection in SQL 6.1.2 Selection in SQL 6.1.3 Comparison of Strings 6.1.4 Dates and Times 6.1.5 Null Values and Comparisons Involving NULL 6.1.6 The Truth-Value UNKNOWN 6.1.7 Ordering the Output 6.1.8 Exercises for Section 6.1 6.2 Queries Involving More Than One Relation 6.2.1 Products and Joins in SQL 6.2.2 Disambiguating Attributes 6.2.3 Tuple Variables 6.2.4 Interpreting Multirelation Queries 6.2.5 Union, Intersection, and Difference of Queries 6.2.6 Exercises for Section 6.2 6.3 Subqueries 6.3.1 Subqueries that Produce Scalar Values 6.3.2 Conditions Involving Relations 6.3.3 Conditions Involving Tuples 6.3.4 Correlated Subqueries 6.3.5 Subqueries in FROM Clauses 6.3.6 SQL Join Expressions 6.3.7 Natural Joins 6.3.8 Outerjoins 6.3.9 Exercises for Section 6.3 6.4 Full-Relation Operations 6.4.1 Eliminating Duplicates 6.4.2 Duplicates in Unions, Intersections, and Differences 6.4.3 Grouping and Aggregation in SQL 6.4.4 Aggregation Operators 6.4.5 Grouping 6.4.6 HAVING Clauses 6.4.7 Exercises for Section 6.4 6.5 Database Modifications 6.5.1 Insertion 6.5.2 Deletion 6.5.3 Updates 6.5.4 Exercises for Section 6.5 6.6 Defining a Relation Schema in SQL 6.6.1 Data Types 6.6.2 Simple Table Declarations 6.6.3 Modifying Relation Schemas 6.6.4 Default Values 6.6.5 Indexes 6.6.6 Introduction to Selection of Indexes 6.6.7 Exercises for Section 6.6 6.7 View Definitions 6.7.1 Declaring Views 6.7.2 Querying Views 6.7.3 Renaming Attributes 6.7.4 Modifying Views 6.7.5 Interpreting Queries Involving Views 6.7.6 Exercises for Section 6.7 6.8 Summary of Chapter 6 6.9 References for Chapter 6 7 Constraints and Triggers 7.1 Keys and Foreign Keys 7.1.1 Declaring Primary Keys 7.1.2 Keys Declared With UNIQUE 7.1.3 Enforcing Key Constraints 7.1.4 Declaring Foreign-Key Constraints 7.1.5 Maintaining Referential Integrity 7.1.6 Deferring the Checking of Constraints 7.1.7 Exercises for Section 7.1 7.2 Constraints on Attributes and Tuples 7.2.1 Not-Null Constraints 7.2.2 Attribute-Based CHECK Constraints 7.2.3 Tuple-Based CHECK Constraints 7.2.4 Exercises for Section 7.2 7.3 Modification of Constraints 7.3.1 Giving Names to Constraints 7.3.2 Altering Constraints on Tables 7.3.3 Exercises for Section 7.3 7.4 Schema-Level Constraints and Triggers 7.4.1 Assertions 7.4.2 Event-Condition-Action Rules 7.4.3 Triggers in SQL 7.4.4 Instead-Of Triggers 7.4.5 Exercises for Section 7.4 7.5 Summary of Chapter 7 7.6 References for Chapter 7 8 System Aspects of SQL 8.1 SQL in a Programming Environment 8.1.1 The Impedance Mismatch Problem 8.1.2 The SQL/Host Language Interface 8.1.3 The DECLARE Section 8.1.4 Using Shared Variables 8.1.5 Single-Row Select Statements 8.1.6 Cursors 8.1.7 Modifications by Cursor 8.1.8 Protecting Against Concurrent Updates 8.1.9 Scrolling Cursors 8.1.10 Dynamic SQL 8.1.11 Exercises for Section 8.1 8.2 Procedures Stored in the Schema 8.2.1 Creating PSM Functions and Procedures 8.2.2 Some Simple Statement Forms in PSM 8.2.3 Branching Statements 8.2.4 Queries in PSM 8.2.5 Loops in PSM 8.2.6 For-Loops 8.2.7 Exceptions in PSM 8.2.8 Using PSM Functions and Procedures 8.2.9 Exercises for Section 8.2 8.3 The SQL Environment 8.3.1 Environments 8.3.2 Schemas 8.3.3 Catalogs 8.3.4 Clients and Servers in the SQL Environment 8.3.5 Connections 8.3.6 Sessions 8.3.7 Modules 8.4 Using a Call-Level Interface 8.4.1 Introduction to SQL/CLI 8.4.2 Processing Statements 8.4.3 Fetching Data From a Query Result 8.4.4 Passing Parameters to Queries 8.4.5 Exercises for Section 8.4 8.5 Java Database Connectivity 8.5.1 Introduction to JDBC 8.5.2 Creating Statements in JDBC 8.5.3 Cursor Operations in JDBC 8.5.4 Parameter Passing 8.5.5 Exercises for Section 8.5 8.6 Transactions in SQL 8.6.1 Serializability 8.6.2 Atomicity 8.6.3 Transactions 8.6.4 Read-Only Transactions 8.6.5 Dirty Reads 8.6.6 Other Isolation Levels 8.6.7 Exercises for Section 8.6 8.7 Security and User Authorization in SQL 8.7.1 Privileges 8.7.2 Creating Privileges 8.7.3 The Privilege-Checking Process 8.7.4 Granting Privileges 8.7.5 Grant Diagrams 8.7.6 Revoking Privileges 8.7.7 Exercises for Section 8.7 8.8 Summary of Chapter 8 8.9 References for Chapter 8 9 Object-Orientation in Query Languages 9.1 Introduction to OQL 9.1.1 An Object-Oriented Movie Example 9.1.2 Path Expressions 9.1.3 Select-From-Where Expressions in OQL 9.1.4 Modifying the Type of the Result 9.1.5 Complex Output Types 9.1.6 Subqueries 9.1.7 Exercises for Section 9.1 9.2 Additional Forms of OQL Expressions 9.2.1 Quantifier Expressions 9.2.2 Aggregation Expressions 9.2.3 Group-By Expressions 9.2.4 HAVING Clauses 9.2.5 Union, Intersection, and Difference 9.2.6 Exercises for Section 9.2 9.3 Object Assignment and Creation in OQL 9.3.1 Assigning Values to Host-Language Variables 9.3.2 Extracting Elements of Collections 9.3.3 Obtaining Each Member of a Collection 9.3.4 Constants in OQL 9.3.5 Creating New Objects 9.3.6 Exercises for Section 9.3 9.4 User-Defined Types in SQL 9.4.1 Defining Types in SQL 9.4.2 Methods in User-Defined Types 9.4.3 Declaring Relations with a UDT 9.4.4 References 9.4.5 Exercises for Section 9.4 9.5 Operations on Object-Relational Data 9.5.1 Following References 9.5.2 Accessing Attributes of Tuples with a UDT 9.5.3 Generator and Mutator Functions 9.5.4 Ordering Relationships on UDT's 9.5.5 Exercises for Section 9.5 9.6 Summary of Chapter 9 9.7 References for Chapter 9 10 Logical Query Languages 10.1 A Logic for Relations 10.1.1 Predicates and Atoms 10.1.2 Arithmetic Atoms 10.1.3 Datalog Rules and Queries 10.1.4 Meaning of Datalog Rules 10.1.5 Extensional and Intensional Predicates 10.1.6 Datalog Rules Applied to Bags 10.1.7 Exercises for Section 10.1 10.2 From Relational Algebra to Datalog 10.2.1 Intersection 10.2.2 Union 10.2.3 Difference 10.2.4 Projection 10.2.5 Selection 10.2.6 Product 10.2.7 Joins 10.2.8 Simulating Multiple Operations with Datalog 10.2.9 Exercises for Section 10.2 10.3 Recursive Programming in Datalog 10.3.1 Recursive Rules 10.3.2 Evaluating Recursive Datalog Rules 10.3.3 Negation in Recursive Rules 10.3.4 Exercises for Section 10.3 10.4 Recursion in SQL 10.4.1 Defining IDB Relations in SQL 10.4.2 Stratified Negation 10.4.3 Problematic Expressions in Recursive SQL 10.4.4 Exercises for Section 10.4 10.5 Summary of Chapter 10 10.6 References for Chapter 10 11 Data Storage 11.1 The "Megatron 2002" Database System 11.1.1 Megatron 2002 Implementation Details 11.1.2 How Megatron 2002 Executes Queries 11.1.3 What's Wrong With Megatron 2002? 11.2 The Memory Hierarchy 11.2.1 Cache 11.2.2 Main Memory 11.2.3 Virtual Memory 11.2.4 Secondary Storage 11.2.5 Tertiary Storage 11.2.6 Volatile and Nonvolatile Storage 11.2.7 Exercises for Section 11.2 11.3 Disks 11.3.1 Mechanics of Disks 11.3.2 The Disk Controller 11.3.3 Disk Storage Characteristics 11.3.4 Disk Access Characteristics 11.3.5 Writing Blocks 11.3.6 Modifying Blocks 11.3.7 Exercises for Section 11.3 11.4 Using Secondary Storage Effectively 11.4.1 The I/O Model of Computation 11.4.2 Sorting Data in Secondary Storage 11.4.3 Merge-Sort 11.4.4 Two-Phase, Multiway Merge-Sort 11.4.5 Multiway Merging of Larger Relations 11.4.6 Exercises for Section 11.4 11.5 Accelerating Access to Secondary Storage 11.5.1 Organizing Data by Cylinders 11.5.2 Using Multiple Disks 11.5.3 Mirroring Disks 11.5.4 Disk Scheduling and the Elevator Algorithm 11.5.5 Prefetching and Large-Scale Buffering 11.5.6 Summary of Strategies and Tradeoffs 11.5.7 Exercises for Section 11.5 11.6 Disk Failures 11.6.1 Intermittent Failures 11.6.2 Checksums 11.6.3 Stable Storage 11.6.4 Error-Handling Capabilities of Stable Storage 11.6.5 Exercises for Section 11.6 11.7 Recovery from Disk Crashes 11.7.1 The Failure Model for Disks 11.7.2 Mirroring as a Redundancy Technique 11.7.3 Parity Blocks 11.7.4 An Improvement: RAID 5 11.7.5 Coping With Multiple Disk Crashes 11.7.6 Exercises for Section 11.7 11.8 Summary of Chapter 11 11.9 References for Chapter 11 12 Representing Data Elements 12.1 Data Elements and Fields 12.1.1 Representing Relational Database Elements 12.1.2 Representing Objects 12.1.3 Representing Data Elements 12.2 Records 12.2.1 Building Fixed-Length Records 12.2.2 Record Headers 12.2.3 Packing Fixed-Length Records into Blocks 12.2.4 Exercises for Section 12.2 12.3 Representing Block and Record Addresses 12.3.1 Client-Server Systems 12.3.2 Logical and Structured Addresses 12.3.3 Pointer Swizzling 12.3.4 Returning Blocks to Disk 12.3.5 Pinned Records and Blocks 12.3.6 Exercises for Section 12.3 12.4 Variable-Length Data and Records 12.4.1 Records With Variable-Length Fields 12.4.2 Records With Repeating Fields 12.4.3 Variable-Format Records 12.4.4 Records That Do Not Fit in a Block 12.4.5 BLOBS 12.4.6 Exercises for Section 12.4 12.5 Record Modifications 12.5.1 Insertion 12.5.2 Deletion 12.5.3 Update 12.5.4 Exercises for Section 12.5 12.6 Summary of Chapter 12 12.7 References for Chapter 12 13 Index Structures 13.1 Indexes on Sequential Files 13.1.1 Sequential Files 13.1.2 Dense Indexes 13.1.3 Sparse Indexes 13.1.4 Multiple Levels of Index 13.1.5 Indexes With Duplicate Search Keys 13.1.6 Managing Indexes During Data Modifications 13.1.7 Exercises for Section 13.1 13.2 Secondary Indexes 13.2.1 Design of Secondary Indexes 13.2.2 Applications of Secondary Indexes 13.2.3 Indirection in Secondary Indexes 13.2.4 Document Retrieval and Inverted Indexes 13.2.5 Exercises for Section 13.2 13.3 B-Trees 13.3.1 The Structure of B-trees 13.3.2 Applications of B-trees 13.3.3 Lookup in B-Trees 13.3.4 Range Queries 13.3.5 Insertion Into B-Trees 13.3.6 Deletion From B-Trees 13.3.7 Efficiency of B-Trees 13.3.8 Exercises for Section 13.3 13.4 Hash Tables 13.4.1 Secondary-Storage Hash Tables 13.4.2 Insertion Into a Hash Table 13.4.3 Hash-Table Deletion 13.4.4 Efficiency of Hash Table Indexes 13.4.5 Extensible Hash Tables 13.4.6 Insertion Into Extensible Hash Tables 13.4.7 Linear Hash Tables 13.4.8 Insertion Into Linear Hash Tables 13.4.9 Exercises for Section 13.4 13.5 Summary of Chapter 13 13.6 References for Chapter 13 14 Multidimensional and Bitmap Indexes 14.1 Applications Needing Multiple Dimensions 14.1.1 Geographic Information Systems 14.1.2 Data Cubes 14.1.3 Multidimensional Queries in SQL 14.1.4 Executing Range Queries Using Conventional Indexes 14.1.5 Executing Nearest-Neighbor Queries Using Conventional Indexes 14.1.6 Other Limitations of Conventional Indexes 14.1.7 Overview of Multidimensional Index Structures 14.1.8 Exercises for Section 14.1 14.2 Hash-Like Structures for Multidimensional Data 14.2.1 Grid Files 14.2.2 Lookup in a Grid File 14.2.3 Insertion Into Grid Files 14.2.4 Performance of Grid Files 14.2.5 Partitioned Hash Functions 14.2.6 Comparison of Grid Files and Partitioned Hashing 14.2.7 Exercises for Section 14.2 14.3 Tree-Like Structures for Multidimensional Data 14.3.1 Multiple-Key Indexes 14.3.2 Performance of Multiple-Key Indexes 14.3.3 $kd$-Trees 14.3.4 Operations on $kd$-Trees 14.3.5 Adapting $kd$-Trees to Secondary Storage 14.3.6 Quad Trees 14.3.7 R-Trees 14.3.8 Operations on R-trees 14.3.9 Exercises for Section 14.3 14.4 Bitmap Indexes 14.4.1 Motivation for Bitmap Indexes 14.4.2 Compressed Bitmaps 14.4.3 Operating on Run-Length-Encoded Bit-Vectors 14.4.4 Managing Bitmap Indexes 14.4.5 Exercises for Section 14.4 14.5 Summary of Chapter 14 14.6 References for Chapter 14 15 Query Execution 15.1 Introduction to Physical-Query-Plan Operators 15.1.1 Scanning Tables 15.1.2 Sorting While Scanning Tables 15.1.3 The Model of Computation for Physical Operators 15.1.4 Parameters for Measuring Costs 15.1.5 I/O Cost for Scan Operators 15.1.6 Iterators for Implementation of Physical Operators 15.2 One-Pass Algorithms for Database Operations 15.2.1 One-Pass Algorithms for Tuple-at-a-Time Operations 15.2.2 One-Pass Algorithms for Unary, Full-Relation Operations 15.2.3 One-Pass Algorithms for Binary Operations 15.2.4 Exercises for Section 15.2 15.3 Nested-Loop Joins 15.3.1 Tuple-Based Nested-Loop Join 15.3.2 An Iterator for Tuple-Based Nested-Loop Join 15.3.3 A Block-Based Nested-Loop Join Algorithm 15.3.4 Analysis of Nested-Loop Join 15.3.5 Summary of Algorithms so Far 15.3.6 Exercises for Section 15.3 15.4 Two-Pass Algorithms Based on Sorting 15.4.1 Duplicate Elimination Using Sorting 15.4.2 Grouping and Aggregation Using Sorting 15.4.3 A Sort-Based Union Algorithm 15.4.4 Sort-Based Intersection and Difference 15.4.5 A Simple Sort-Based Join Algorithm 15.4.6 Analysis of Simple Sort-Join 15.4.7 A More Efficient Sort-Based Join 15.4.8 Summary of Sort-Based Algorithms 15.4.9 Exercises for Section 15.4 15.5 Two-Pass Algorithms Based on Hashing 15.5.1 Partitioning Relations by Hashing 15.5.2 A Hash-Based Algorithm for Duplicate Elimination 15.5.3 Hash-Based Grouping and Aggregation 15.5.4 Hash-Based Union, Intersection, and Difference 15.5.5 The Hash-Join Algorithm 15.5.6 Saving Some Disk I/O's 15.5.7 Summary of Hash-Based Algorithms 15.5.8 Exercises for Section 15.5 15.6 Index-Based Algorithms 15.6.1 Clustering and Nonclustering Indexes 15.6.2 Index-Based Selection 15.6.3 Joining by Using an Index 15.6.4 Joins Using a Sorted Index 15.6.5 Exercises for Section 15.6 15.7 Buffer Management 15.7.1 Buffer Management Architecture 15.7.2 Buffer Management Strategies 15.7.3 The Relationship Between Physical Operator Selection and Buffer Management 15.7.4 Exercises for Section 15.7 15.8 Algorithms Using More Than Two Passes 15.8.1 Multipass Sort-Based Algorithms 15.8.2 Performance of Multipass, Sort-Based Algorithms 15.8.3 Multipass Hash-Based Algorithms 15.8.4 Performance of Multipass Hash-Based Algorithms 15.8.5 Exercises for Section 15.8 15.9 Parallel Algorithms for Relational Operations 15.9.1 Models of Parallelism 15.9.2 Tuple-at-a-Time Operations in Parallel 15.9.3 Parallel Algorithms for Full-Relation Operations 15.9.4 Performance of Parallel Algorithms 15.9.5 Exercises for Section 15.9 15.10 Summary of Chapter 15 15.11 References for Chapter 15 16 The Query Compiler 16.1 Parsing 16.1.1 Syntax Analysis and Parse Trees 16.1.2 A Grammar for a Simple Subset of SQL 16.1.3 The Preprocessor 16.1.4 Exercises for Section 16.1 16.2 Algebraic Laws for Improving Query Plans 16.2.1 Commutative and Associative Laws 16.2.2 Laws Involving Selection 16.2.3 Pushing Selections 16.2.4 Laws Involving Projection 16.2.5 Laws About Joins and Products 16.2.6 Laws Involving Duplicate Elimination 16.2.7 Laws Involving Grouping and Aggregation 16.2.8 Exercises for Section 16.2 16.3 From Parse Trees to Logical Query Plans 16.3.1 Conversion to Relational Algebra 16.3.2 Removing Subqueries From Conditions 16.3.3 Improving the Logical Query Plan 16.3.4 Grouping Associative/Commutative Operators 16.3.5 Exercises for Section 16.3 16.4 Estimating the Cost of Operations 16.4.1 Estimating Sizes of Intermediate Relations 16.4.2 Estimating the Size of a Projection 16.4.3 Estimating the Size of a Selection 16.4.4 Estimating the Size of a Join 16.4.5 Natural Joins With Multiple Join Attributes 16.4.6 Joins of Many Relations 16.4.7 Estimating Sizes for Other Operations 16.4.8 Exercises for Section 16.4 16.5 Introduction to Cost-Based Plan Selection 16.5.1 Obtaining Estimates for Size Parameters 16.5.2 Computation of Statistics 16.5.3 Heuristics for Reducing the Cost of Logical Query Plans 16.5.4 Approaches to Enumerating Physical Plans 16.5.5 Exercises for Section 16.5 16.6 Choosing an Order for Joins 16.6.1 Significance of Left and Right Join Arguments 16.6.2 Join Trees 16.6.3 Left-Deep Join Trees 16.6.4 Dynamic Programming to Select a Join Order and Grouping 16.6.5 Dynamic Programming With More Detailed Cost Functions 16.6.6 A Greedy Algorithm for Selecting a Join Order 16.6.7 Exercises for Section 16.6 16.7 Completing the Physical-Query-Plan 16.7.1 Choosing a Selection Method 16.7.2 Choosing a Join Method 16.7.3 Pipelining Versus Materialization 16.7.4 Pipelining Unary Operations 16.7.5 Pipelining Binary Operations 16.7.6 Notation for Physical Query Plans 16.7.7 Ordering of Physical Operations 16.7.8 Exercises for Section 16.7 16.8 Summary of Chapter 16 16.9 References for Chapter 16 17 Coping With System Failures 17.1 Issues and Models for Resilient Operation 17.1.1 Failure Modes 17.1.2 More About Transactions 17.1.3 Correct Execution of Transactions 17.1.4 The Primitive Operations of Transactions 17.1.5 Exercises for Section 17.1 17.2 Undo Logging 17.2.1 Log Records 17.2.2 The Undo-Logging Rules 17.2.3 Recovery Using Undo Logging 17.2.4 Checkpointing 17.2.5 Nonquiescent Checkpointing 17.2.6 Exercises for Section 17.2 17.3 Redo Logging 17.3.1 The Redo-Logging Rule 17.3.2 Recovery With Redo Logging 17.3.3 Checkpointing a Redo Log 17.3.4 Recovery With a Checkpointed Redo Log 17.3.5 Exercises for Section 17.3 17.4 Undo/Redo Logging 17.4.1 The Undo/Redo Rules 17.4.2 Recovery With Undo/Redo Logging 17.4.3 Checkpointing an Undo/Redo Log 17.4.4 Exercises for Section 17.4 17.5 Protecting Against Media Failures 17.5.1 The Archive 17.5.2 Nonquiescent Archiving 17.5.3 Recovery Using an Archive and Log 17.5.4 Exercises for Section 17.5 17.6 Summary of Chapter 17 17.7 References for Chapter 17 18 Concurrency Control 18.1 Serial and Serializable Schedules 18.1.1 Schedules 18.1.2 Serial Schedules 18.1.3 Serializable Schedules 18.1.4 The Effect of Transaction Semantics 18.1.5 A Notation for Transactions and Schedules 18.1.6 Exercises for Section 18.1 18.2 Conflict-Serializability 18.2.1 Conflicts 18.2.2 Precedence Graphs and a Test for Conflict-Serializability 18.2.3 Why the Precedence-Graph Test Works 18.2.4 Exercises for Section 18.2 18.3 Enforcing Serializability by Locks 18.3.1 Locks 18.3.2 The Locking Scheduler 18.3.3 Two-Phase Locking 18.3.4 Why Two-Phase Locking Works 18.3.5 Exercises for Section 18.3 18.4 Locking Systems With Several Lock Modes 18.4.1 Shared and Exclusive Locks 18.4.2 Compatibility Matrices 18.4.3 Upgrading Locks 18.4.4 Update Locks 18.4.5 Increment Locks 18.4.6 Exercises for Section 18.4 18.5 An Architecture for a Locking Scheduler 18.5.1 A Scheduler That Inserts Lock Actions 18.5.2 The Lock Table 18.5.3 Exercises for Section 18.5 18.6 Managing Hierarchies of Database Elements 18.6.1 Locks With Multiple Granularity 18.6.2 Warning Locks 18.6.3 Phantoms and Handling Insertions Correctly 18.6.4 Exercises for Section 18.6 18.7 The Tree Protocol 18.7.1 Motivation for Tree-Based Locking 18.7.2 Rules for Access to Tree-Structured Data 18.7.3 Why the Tree Protocol Works 18.7.4 Exercises for Section 18.7 18.8 Concurrency Control by Timestamps 18.8.1 Timestamps 18.8.2 Physically Unrealizable Behaviors 18.8.3 Problems With Dirty Data 18.8.4 The Rules for Timestamp-Based Scheduling 18.8.5 Multiversion Timestamps 18.8.6 Timestamps and Locking 18.8.7 Exercises for Section 18.8 18.9 Concurrency Control by Validation 18.9.1 Architecture of a Validation-Based Scheduler 18.9.2 The Validation Rules 18.9.3 Comparison of Three Concurrency-Control Mechanisms 18.9.4 Exercises for Section 18.9 18.10 Summary of Chapter 18 18.11 References for Chapter 18 19 More About Transaction Management 19.1 Serializability and Recoverability 19.1.1 The Dirty-Data Problem 19.1.2 Cascading Rollback 19.1.3 Recoverable Schedules 19.1.4 Schedules That Avoid Cascading Rollback 19.1.5 Managing Rollbacks Using Locking 19.1.6 Group Commit 19.1.7 Logical Logging 19.1.8 Recovery From Logical Logs 19.1.9 Exercises for Section 19.1 19.2 View Serializability 19.2.1 View Equivalence 19.2.2 Polygraphs and the Test for View-Serializability 19.2.3 Testing for View-Serializability 19.2.4 Exercises for Section 19.2 19.3 Resolving Deadlocks 19.3.1 Deadlock Detection by Timeout 19.3.2 The Waits-For Graph 19.3.3 Deadlock Prevention by Ordering Elements 19.3.4 Detecting Deadlocks by Timestamps 19.3.5 Comparison of Deadlock-Management Methods 19.3.6 Exercises for Section 19.3 19.4 Distributed Databases 19.4.1 Distribution of Data 19.4.2 Distributed Transactions 19.4.3 Data Replication 19.4.4 Distributed Query Optimization 19.4.5 Exercises for Section 19.4 19.5 Distributed Commit 19.5.1 Supporting Distributed Atomicity 19.5.2 Two-Phase Commit 19.5.3 Recovery of Distributed Transactions 19.5.4 Exercises for Section 19.5 19.6 Distributed Locking 19.6.1 Centralized Lock Systems 19.6.2 A Cost Model for Distributed Locking Algorithms 19.6.3 Locking Replicated Elements 19.6.4 Primary-Copy Locking 19.6.5 Global Locks From Local Locks 19.6.6 Exercises for Section 19.6 19.7 Long-Duration Transactions 19.7.1 Problems of Long Transactions 19.7.2 Sagas 19.7.3 Compensating Transactions 19.7.4 Why Compensating Transactions Work 19.7.5 Exercises for Section 19.7 19.8 Summary of Chapter 19 19.9 References for Chapter 19 20 Information Integration 20.1 Modes of Information Integration 20.1.1 Problems of Information Integration 20.1.2 Federated Database Systems 20.1.3 Data Warehouses 20.1.4 Mediators 20.1.5 Exercises for Section 20.1 20.2 Wrappers in Mediator-Based Systems 20.2.1 Templates for Query Patterns 20.2.2 Wrapper Generators 20.2.3 Filters 20.2.4 Other Operations at the Wrapper 20.2.5 Exercises for Section 20.2 20.3 Capability-Based Optimization in Mediators 20.3.1 The Problem of Limited Source Capabilities 20.3.2 A Notation for Describing Source Capabilities 20.3.3 Capability-Based Query-Plan Selection 20.3.4 Adding Cost-Based Optimization 20.3.5 Exercises for Section 20.3 20.4 On-Line Analytic Processing 20.4.1 OLAP Applications 20.4.2 A Multidimensional View of OLAP Data 20.4.3 Star Schemas 20.4.4 Slicing and Dicing 20.4.5 Exercises for Section 20.4 20.5 Data Cubes 20.5.1 The Cube Operator 20.5.2 Cube Implementation by Materialized Views 20.5.3 The Lattice of Views 20.5.4 Exercises for Section 20.5 20.6 Data Mining 20.6.1 Data-Mining Applications 20.6.2 Finding Frequent Sets of Items 20.6.3 The A-Priori Algorithm 20.6.4 Exercises for Section 20.6 20.7 Summary of Chapter 20 20.8 References for Chapter 20

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


<http://www.worldcat.org/oclc/244097685>
library:oclcnum"244097685"
library:placeOfPublication
owl:sameAs<info:oclcnum/244097685>
rdf:typeschema:Book
schema:bookEdition"2nd ed."
schema:contributor
schema:contributor
schema:creator
schema:datePublished"2009"
schema:exampleOfWork<http://worldcat.org/entity/work/id/793048268>
schema:inLanguage"en"
schema:name"Database systems : the complete book."
schema:publisher
schema:url
schema:workExample

Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.