1 The Worlds of Database Systems 1
1.1 The Evolution of Database Systems 1
1.1.1 Early Database Management Systems 2
1.1.2 Relational Database Systems 3
1.1.3 Smaller and Smaller Systems 3
1.1.4 Bigger and Bigger Systems 4
1.1.5 Information Integration 4
1.2 Overview of a Database Management System 5
1.2.1 Data-Definition Language Commands 5
1.2.2 Overview of Query Processing 5
1.2.3 Storage and Buffer Management 7
1.2.4 Transaction Processing 8
1.2.5 The Query Processor 9
1.3 Outline of Database-System Studies 10
1.4 References for Chapter 1 12
Ⅰ Relational Database Modeling 15
2 The Relational Model of Data 17
2.1 An Overview of Data Models 17
2.1.1 What is a Data Model？ 17
2.1.2 Important Data Models 18
2.1.3 The Relational Model in Brief 18
2.1.4 The Semistructured Model in Brief 19
2.1.5 Other Data Models 20
2.1.6 Comparison of Modeling Approaches 21
2.2 Basics of the Relational Model 21
2.2.1 Attributes 22
2.2.2 Schemas 22
2.2.3 Tuples 22
2.2.4 Domains 23
2.2.5 Equivalent Representations of a Relation 23
2.2.6 Relation Instances 24
2.2.7 Keys of Relations 25
2.2.8 An Example Database Schema 26
2.2.9 Exercises for Section 2.2 28
2.3 Defining a Relation Schema in SQL 29
2.3.1 Relations in SQL 29
2.3.2 Data Types 30
2.3.3 Simple Table Declarations 31
2.3.4 Modifying Relation Schemas 33
2.3.5 Default Values 34
2.3.6 Declaring Keys 34
2.3.7 Exercises for Section 2.3 36
2.4 An Algebraic Query Language 38
2.4.1 Why Do We Need a Special Query Language？ 38
2.4.2 What is an Algebra？ 38
2.4.3 Overview of Relational Algebra 39
2.4.4 Set Operations on Relations 39
2.4.5 Projection 41
2.4.6 Selection 42
2.4.7 Cartesian Product 43
2.4.8 Natural Joins 43
2.4.9 Theta-Joins 45
2.4.10 Combinihg Operations to Form Queries 47
2.4.11 Naming and Renaming 49
2.4.12 Relationships Among Operations 50
2.4.13 A Linear Notation for Algebraic Expressions 51
2.4.14 Exercises for Section 2.4 52
2.5 Constraints on Relations 58
2.5.1 Relational Algebra as a Constraint Language 59
2.5.2 Referential Integrity Constraints 59
2.5.3 Key Constraints 60
2.5.4 Additional Constraint Examples 61
2.5.5 Exercises for Section 2.5 62
2.6 Summary of Chapter 2 63
2.7 References for Chapter 2 65
3 Design Theory for Relational Databases 67
3.1 Functional Dependencies 67
3.1.1 Definition of Functional Dependency 68
3.1.2 Keys of Relations 70
3.1.3 Superkeys 71
3.1.4 Exercises for Section 3.1 71
3.2 Rules About Functional Dependencies 72
3.2.1 Reasoning About Functional Dependencies 72
3.2.2 The Splitting/ Combining Rule 73
3.2.3 Trivial Functional Dependencies 74
3.2.4 Computing the Closure of Attributes 75
3.2.5 Why the Closure Algorithm Works 77
3.2.6 The Transitive Rule 79
3.2.7 Closing Sets of Functional Dependencies 80
3.2.8 Projecting Functional Dependencies 81
3.2.9 Exercises for Section 3.2 83
3.3 Design of Relational Database Schemas 85
3.3.1 Anomalies 86
3.3.2 Decomposing Relations 86
3.3.3 Boyce-Codd Normal Form 88
3.3.4 Decomposition into BCNF 89
3.3.5 Exercises for Section 3.3 92
3.4 Decomposition：The Good，Bad，and Ugly 93
3.4.1 Recovering Information from a Decomposition 94
3.4.2 The Chase Test for Lossless Join 96
3.4.3 Why the Chase Works 99
3.4.4 Dependency Preservation 100
3.4.5 Exercises for Section 3.4 102
3.5 Third Normal Form 102
3.5.1 Definition of Third Normal Form 102
3.5.2 The Synthesis Algorithm for 3NF Schemas 103
3.5.3 Why the 3NF Synthesis Algorithm Works 104
3.5.4 Exercises for Section 3.5 105
3.6 Multivalued Dependencies 105
3.6.1 Attribute Independence and Its Consequent Redundancy 106
3.6.2 Definition of Multivalued Dependencies 107
3.6.3 Reasoning About Multivalued Dependencies 108
3.6.4 Fourth Normal Form 110
3.6.5 Decomposition into Fourth Normal Form 111
3.6.6 Relationships Among Normal Forms 113
3.6.7 Exercises for Section 3.6 113
3.7 An Algorithm for Discovering MVD’s 115
3.7.1 The Closure and the Chase 115
3.7.2 Extending the Chase to MVD’s 116
3.7.3 Why the Chase Works for MVD’s 118
3.7.4 Projecting MVD’s 119
3.7.5 Exercises for Section 3.7 120
3.8 Summary of Chapter 3 121
3.9 References for Chapter 3 122
4 High-Level Database Models 125
4.1 The Entity/Relationship Model 126
4.1.1 Entity Sets 126
4.1.2 Attributes 126
4.1.3 Relationships 127
4.1.4 Entity-Relationship Diagrams 127
4.1.5 Instances of an E/R Diagram 128
4.1.6 Multiplicity of Binary E/R Relationships 129
4.1.7 Multiway Relationships 130
4.1.8 Roles in Relationships 131
4.1.9 Attributes on Relationships 134
4.1.10 Converting Multiway Relationships to Binary 134
4.1.11 Subclasses in the E/R Model 135
4.1.12 Exercises for Section 4.1 138
4.2 Design Principles 140
4.2.1 Faithfulness 140
4.2.2 Avoiding Redundancy 141
4.2.3 Simplicity Counts 142
4.2.4 Choosing the Right Relationships 142
4.2.5 Picking the Right Kind of Element 144
4.2.6 Exercises for Section 4.2 145
4.3 Constraints in the E/R Model 148
4.3.1 Keys in the E/R Model 148
4.3.2 Representing Keys in the E/R Model 149
4.3.3 Referential Integrity 150
4.3.4 Degree Constraints 151
4.3.5 Exercises for Section 4.3 151
4.4 Weak Entity Sets 152
4.4.1 Causes of Weak Entity Sets 152
4.4.2 Requirements for Weak Entity Sets 153
4.4.3 Weak Entity Set Notation 155
4.4.4 Exercises for Section 4.4 156
4.5 From E/R Diagrams to Relational Designs 157
4.5.1 From Entity Sets to Relations 157
4.5.2 From E/R Relationships to Relations 158
4.5.3 Combining Relations 160
4.5.4 Handling Weak Entity Sets 161
4.5.5 Exercises for Section 4.5 163
4.6 Converting Subclass Structures to Relations 165
4.6.1 E/R-Style Conversion 166
4.6.2 An Object-Oriented Approach 167
4.6.3 Using Null Values to Combine Relations 168
4.6.4 Comparison of Approaches 169
4.6.5 Exercises for Section 4.6 171
4.7 Unified Modeling Language 171
4.7.1 UML Classes 172
4.7.2 Keys for UML classes 173
4.7.3 Associations 173
4.7.4 Self-Associations 175
4.7.5 Association Classes 175
4.7.6 Subclasses in UML 176
4.7.7 Aggregations and Compositions 177
4.7.8 Exercises for Section 4.7 179
4.8 From UML Diagrams to Relations 179
4.8.1 UML-to-Relations Basics 179
4.8.2 From UML Subclasses to Relations 180
4.8.3 From Aggregations and Compositions to Relations 181
4.8.4 The UML Analog of Weak Entity Sets 181
4.8.5 Exercises for Section 4.8 183
4.9 Object Definition Language 183
4.9.1 Class Declarations 184
4.9.2 Attributes in ODL 184
4.9.3 Relationships in ODL 185
4.9.4 Inverse Relationships 186
4.9.5 Multiplicity of Relationships 186
4.9.6 Types in ODL 188
4.9.7 Subclasses in ODL 190
4.9.8 Declaring Keys in ODL 191
4.9.9 Exercises for Section 4.9 192
4.10 From ODL Designs to Relational Designs 193
4.10.1 From ODL Classes to Relations 193
4.10.2 Complex Attributes in Classes 194
4.10.3 Representing Set-Valued Attributes 195
4.10.4 Representing Other Type Constructors 196
4.10.5 Representing ODL Relationships 198
4.10.6 Exercises for Section 4.10 198
4.11 Summary of Chapter 4 200
4.12 References for Chapter 4 202
Ⅱ Relational Database Programming 203
5 Algebraic and Logical Query Languages 205
5.1 Relational Operations on Bags 205
5.1.1 Why Bags？ 206
5.1.2 Union，Intersection，and Difierence of Bags 207
5.1.3 Projection of Bags 208
5.1.4 Selection on Bags 209
5.1.5 Product of Bags 210
5.1.6 Joins of Bags 210
5.1.7 Exercises for Section 5.1 212
5.2 Extended Operators of Relational Algebra 213
5.2.1 Duplicate Elimination 214
5.2.2 Aggregation Operators 214
5.2.3 Grouping 215
5.2.4 The Grouping Operator 216
5.2.5 Extending the Projection Operator 217
5.2.6 The Sorting Operator 219
5.2.7 Outerjoins 219
5.2.8 Exercises for Section 5.2 222
5.3 A Logic for Relations 222
5.3.1 Predicates and Atoms 223
5.3.2 Arithmetic Atoms 223
5.3.3 Datalog Rules and Queries 224
5.3.4 Meaning of Datalog Rules 225
5.3.5 Extensional and Intensional Predicates 228
5.3.6 Datalog Rules Applied to Bags 228
5.3.7 Exercises for Section 5.3 230
5.4 Relational Algebra and Datalog 230
5.4.1 Boolean Operations 231
5.4.2 Projection 232
5.4.3 Selection 232
5.4.4 Product 235
5.4.5 Joins 235
5.4.6 Simulating Multiple Operations with Datalog 236
5.4.7 Comparison Between Datalog and Relational Algebra 238
5.4.8 Exercises for Section 5.4 238
5.5 Summary of Chapter 5 240
5.6 References for Chapter 5 241
6 The Database Language SQL 243
6.1 Simple Queries in SQL 244
6.1.1 Projection in SQL 246
6.1.2 Selection in SQL 248
6.1.3 Comparison of Strings 250
6.1.4 Pattern Matching in SQL 250
6.1.5 Dates and Times 251
6.1.6 Null Values and Comparisons Involving NULL 252
6.1.7 The Truth-Value UNKNOWN 253
6.1.8 Ordering the Output 255
6.1.9 Exercises for Section 6.1 256
6.2 Queries Involving More Than One Relation 258
6.2.1 Products and Joins in SQL 259
6.2.2 Disambiguating Attributes 260
6.2.3 Tuple Variables 261
6.2.4 Interpreting Multirelation Queries 262
6.2.5 Union，Intersection，and Difference of Queries 265
6.2.6 Exercises for Section 6.2 267
6.3 Subqueries 268
6.3.1 Subqueries that Produce Scalar Values 269
6.3.2 Conditions Involving Relations 270
6.3.3 Conditions Involving Tuples 271
6.3.4 Correlated Subqueries 273
6.3.5 Subqueries in FROM Clauses 274
6.3.6 SQL Join Expressions 275
6.3.7 Natural Joins 276
6.3.8 Outerjoins 277
6.3.9 Exercises for Section 6.3 279
6.4 Full-Relation Operations 281
6.4.1 Eliminating Duplicates 281
6.4.2 Duplicates in Unions，Intersections，and Differences 282
6.4.3 Grouping and Aggregation in SQL 283
6.4.4 Aggregation Operators 284
6.4.5 Grouping 285
6.4.6 Grouping，Aggregation，and Nulls 287
6.4.7 HAVING Clauses 288
6.4.8 Exercises for Section 6.4 289
6.5 Database Modifications 291
6.5.1 Insertion 291
6.5.2 Deletion 292
6.5.3 Updates 294
6.5.4 Exercises for Section 6.5 295
6.6 Transactions in SQL 296
6.6.1 Serializability 296
6.6.2 Atomicity 298
6.6.3 Transactions 299
6.6.4 Read-Only Transactions 300
6.6.5 Dirty Reads 302
6.6.6 Other Isolation Levels 304
6.6.7 Exercises for Section 6.6 306
6.7 Summary of Chapter 6 307
6.8 References for Chapter 6 308
7 Constraints and Triggers 311
7.1 Keys and Foreign Keys 311
7.1.1 Declaring Foreign-Key Constraints 312
7.1.2 Maintaining Referential Integrity 313
7.1.3 Deferred Checking of Constraints 315
7.1.4 Exercises for Section 7.1 318
7.2 Constraints on Attributes and Tuples 319
7.2.1 Not-Null Constraints 319
7.2.2 Attribute-Based CHECK Constraints 320
7.2.3 Tuple-Based CHECK Constraints 321
7.2.4 Comparison of Tuple- and Attribute-Based Constraints 323
7.2.5 Exercises for Section 7.2 323
7.3 Modification of Constraints 325
7.3.1 Giving Names to Constraints 325
7.3.2 Altering Constraints on Tables 326
7.3.3 Exercises for Section 7.3 327
7.4 Assertions 328
7.4.1 Creating Assertions 328
7.4.2 Using Assertions 329
7.4.3 Exercises for Section 7.4 330
7.5 Triggers 332
7.5.1 Triggers in SQL 332
7.5.2 The Options for Trigger Design 334
7.5.3 Exercises for Section 7.5 337
7.6 Summary of Chapter 7 339
7.7 References for Chapter 7 339
8 Views and Indexes 341
8.1 Virtual Views 341
8.1.1 Declaring Views 341
8.1.2 Querying Views 343
8.1.3 Renaming Attributes 343
8.1.4 Exercises for Section 8.1 344
8.2 Modifying Views 344
8.2.1 View Removal 345
8.2.2 Updatable Views 345
8.2.3 Instead-Of Triggers on Views 347
8.2.4 Exercises for Section 8.2 349
8.3 Indexes in SQL 350
8.3.1 Motivation for Indexes 350
8.3.2 Declaring Indexes 351
8.3.3 Exercises for Section 8.3 352
8.4 Selection of Indexes 352
8.4.1 A Simple Cost Model 352
8.4.2 Some Useful Indexes 353
8.4.3 Calculating the Best Indexes to Create 355
8.4.4 Automatic Selection of Indexes to Create 357
8.4.5 Exercises for Section 8.4 359
8.5 Materialized Views 359
8.5.1 Maintaining a Materialized View 360
8.5.2 Periodic Maintenance of Materialized Views 362
8.5.3 Rewriting Queries to Use Materialized Views 362
8.5.4 Automatic Creation of Materialized Views 364
8.5.5 Exercises for Section 8.5 365
8.6 Summary of Chapter 8 366
8.7 References for Chapter 8 367
9 SQL in a Server Environment 369
9.1 The Three-Tier Architecture 369
9.1.1 The Web-Server Tier 370
9.1.2 The Application Tier 371
9.1.3 The Database Tier 372
9.2 The SQL Environment 372
9.2.1 Environments 373
9.2.2 Schemas 374
9.2.3 Catalogs 375
9.2.4 Clients and Servers in the SQL Environment 375
9.2.5 Connections 376
9.2.6 Sessions 377
9.2.7 Modules 378
9.3 The SQL/Host-Language Interface 378
9.3.1 The Impedance Mismatch Problem 380
9.3.2 Connecting SQL to the Host Language 380
9.3.3 The DECLARE Section 381
9.3.4 Using Shared Variables 382
9.3.5 Single-Row Select Statements 383
9.3.6 Cursors 383
9.3.7 Modifications by Cursor 386
9.3.8 Protecting Against Concurrent Updates 387
9.3.9 Dynamic SQL 388
9.3.10 Exercises for Section 9.3 390
9.4 Stored Procedures 391
9.4.1 Creating PSM Functions and Procedures 391
9.4.2 Some Simple Statement Forms in PSM 392
9.4.3 Branching Statements 394
9.4.4 Queries in PSM 395
9.4.5 Loops in PSM 396
9.4.6 For-Loops 398
9.4.7 Exceptions in PSM 400
9.4.8 Using PSM Functions and Procedures 402
9.4.9 Exercises for Section 9.4 402
9.5 Using a Call-Level Interface 404
9.5.1 Introduction to SQL/CLI 405
9.5.2 Processing Statements 407
9.5.3 Fetching Data From a Query Result 408
9.5.4 Passing Parameters to Queries 410
9.5.5 Exercises for Section 9.5 412
9.6JDBC 412
9.6.1Introduction to JDBC 412
9.6.2Creating Statements in JDBC 413
9.6.3Cursor Operations in JDBC 415
9.6.4Parameter Passing 416
9.6.5Exercises for Section 9.6 416
9.7PHP 416
9.7.1 PHP Basics 417
9.7.2 Arrays 418
9.7.3The PEAR DB Library 419
9.7.4Creating a Database Connection Using DB 419
9.7.5Executing SQL Statements 419
9.7.6Cursor Operations in PHP 420
9.7.7Dynamic SQL in PHP 421
9.7.8Exercises for Section 422
9.8Summary of Chapter 9 422
9.9References for Chapter 9 423
10 Advanced Topics in Relational Databases 425
10.1 Security and User Authorization in SQL 425
10.1.1 Privileges 426
10.1.2 Creating Privileges 427
10.1.3 The Privilege-Checking Process 428
10.1.4 Granting Privileges 430
10.1.5 Grant Diagrams 431
10.1.6 Revoking Privileges 433
10.1.7 Exercises for Section 10.1 436
10.2 Recursion in SQL 437
10.2.1 Defining Recursive Relations in SQL 437
10.2.2 Problematic Expressions in Recursive SQL 440
10.2.3 Exercises for Section 10.2 443
10.3 The Object-Relational Model 445
10.3.1 From Relations to Object-Relations 445
10.3.2 Nested Relations 446
10.3.3 References 447
10.3.4 Object-Oriented Versus Object-Relational 449
10.3.5 Exercises for Section 10.3 450
10.4 User-Defined Types in SQL 451
10.4.1 Defining Types in SQL 451
10.4.2 Method Declarations in UDT’s 452
10.4.3 Method Definitions 453
10.4.4 Declaring Relations with a UDT 454
10.4.5 References 454
10.4.6 Creating Object ID’s for Tables 455
10.4.7 Exercises for Section 10.4 457
10.5 Operations on Object-Relational Data 457
10.5.1 Following References 457
10.5.2 Accessing Components of Tuples with a UDT 458
10.5.3 Generator and Mutator Functions 460
10.5.4 Ordering Relationships on UDT’s 461
10.5.5 Exercises for Section 10.5 463
10.6 On-Line Analytic Processing 464
10.6.1 OLAP and Data Warehouses 465
10.6.2 OLAP Applications 465
10.6.3 A Multidimensional View of OLAP Data 466
10.6.4 Star Schemas 467
10.6.5 Slicing and Dicing 469
10.6.6 Exercises for Section 10.6 472
10.7 Data Cubes 473
10.7.1 The Cube Operator 473
10.7.2 The Cube Operator in SQL 475
10.7.3 Exercises for Section 10.7 477
10.8 Summary of Chapter 10 478
10.9 References for Chapter 10 480
Ⅲ Modeling and Programming for Semistructured Data 481
11 The Semistructured-Data Model 483
11.1 Semistructured Data 483
11.1.1 Motivation for the Semistructured-Data Model 483
11.1.2 Semistructured Data Representation 484
11.1.3 Information Integration Via Semistructured Data 486
11.1.4 Exercises for Section 11.1 487
11.2 XML 488
11.2.1 Semantic Tags 488
11.2.2 XML With and Without a Schema 489
11.2.3 Well-Formed XML 489
11.2.4 Attributes 490
11.2.5 Attributes That Connect Elements 491
11.2.6 Namespaces 493
11.2.7 XML and Databases 493
11.2.8 Exercises for Section 11.2 495
11.3 Document Type Definitions 495
11.3.1 The Form of a DTD 495
11.3.2 Using a DTD 499
11.3.3 Attribute Lists 499
11.3.4 Identifiers and References 500
11.3.5 Exercises for Section 11.3 502
11.4 XML Schema 502
11.4.1 The Form of an XML Schema 502
11.4.2 Elements 503
11.4.3 Complex Types 504
11.4.4 Attributes 506
11.4.5 Restricted Simple Types 507
11.4.6 Keys in XML Schema 509
11.4.7 Foreign Keys in XML Schema 510
11.4.8 Exercises for Section 11.4 512
11.5 Summary of Chapter 11 514
11.6 References for Chapter 11 515
12 Programming Languages for XML 517
12.1 XPath 517
12.1.1 The XPath Data Model 518
12.1.2 Document Nodes 519
12.1.3 Path Expressions 519
12.1.4 Relative Path Expressions 521
12.1.5 Attributes in Path Expressions 521
12.1.6 Axes 521
12.1.7 Context of Expressions 522
12.1.8 Wildcards 523
12.1.9 Conditions in Path Expressions 523
12.1.10 Exercises for Section 12.1 526
12.2 XQuery 528
12.2.1 XQuery Basics 530
12.2.2 FLWR Expressions 530
12.2.3 Replacement of Variables by Their Values 534
12.2.4 Joins in XQuery 536
12.2.5 XQuery Comparison Operators 537
12.2.6 Elimination of Duplicates 538
12.2.7 Quantification in XQuery 539
12.2.8 Aggregations 540
12.2.9 Branching in XQuery Expressions 540
12.2.10 Ordering the Result of a Query 541
12.2.11 Exercises for Section 12.2 543
12.3 Extensible Stylesheet Language 544
12.3.1 XSLT Basics 544
12.3.2 Templates 544
12.3.3 Obtaining Values From XML Data 545
12.3.4 Recursive Use of Templates 546
12.3.5 Iteration in XSLT 549
12.3.6 Conditionals in XSLT 551
12.3.7 Exercises for Section 12.3 551
12.4 Summary of Chapter 12 553
12.5 References for Chapter 12 554
Ⅳ Database System Implementation 555
13 Secondary Storage Management 557
13.1 The Memory Hierarchy 557
13.1.1 The Memory Hierarchy 557
13.1.2 Transfer of Data Between Levels 560
13.1.3 Volatile and Nonvolatile Storage 560
13.1.4 Virtual Memory 560
13.1.5 Exercises for Section 13.1 561
13.2 Disks 562
13.2.1 Mechanics of Disks 562
13.2.2 The Disk Controller 564
13.2.3 Disk Access Characteristics 564
13.2.4 Exercises for Section 13.2 567
13.3 Accelerating Access to Secondary Storage 568
13.3.1 The I/O Model of Computation 568
13.3.2 Organizing Data by Cylinders 569
13.3.3 Using Multiple Disks 570
13.3.4 Mirroring Disks 571
13.3.5 Disk Scheduling and the Elevator Algorithm 571
13.3.6 Prefetching and Large-Scale Buffering 573
13.3.7 Exercises for Section 13.3 573
13.4 Disk Failures 575
13.4.1 Intermittent Failures 576
13.4.2 Checksums 576
13.4.3 Stable Storage 577
13.4.4 Error-Handling Capabilities of Stable Storage 578
13.4.5 Recovery from Disk Crashes 578
13.4.6 Mirroring as a Redundancy Technique 579
13.4.7 Parity Blocks 580
13.4.8 An Improvement：RAID 5 583
13.4.9 Coping With Multiple Disk Crashes 584
13.4.10 Exercises for Section 13.4 587
13.5 Arranging Data on Disk 590
13.5.1 Fixed-Length Records 590
13.5.2 Packing Fixed-Length Records into Blocks 592
13.5.3 Exercises for Section 13.5 593
13.6 Representing Block and Record Addresses 593
13.6.1 Addresses in Client-Server Systems 593
13.6.2 Logical and Structured Addresses 595
13.6.3 Pointer Swizzling 596
13.6.4 Returning Blocks to Disk 600
13.6.5 Pinned Records and Blocks 600
13.6.6 Exercises for Section 13.6 602
13.7 Variable-Length Data and Records 603
13.7.1 Records With Variable-Length Fields 604
13.7.2 Records With Repeating Fields 605
13.7.3 Variable-Format Records 607
13.7.4 Records That Do Not Fit in a Block 608
13.7.5 BLOBs 608
13.7.6 Column Stores 609
13.7.7 Exercises for Section 13.7 610
13.8 Record Modifications 612
13.8.1 Insertion 612
13.8.2 Deletion 614
13.8.3 Update 615
13.8.4 Exercises for Section 13.8 615
13.9 Summary of Chapter 13 615
13.10References for Chapter 13 617
14 Index Structures 619
14.1 Index-Structure Basics 620
14.1.1 Sequential Files 621
14.1.2 Dense Indexes 621
14.1.3 Sparse Indexes 622
14.1.4 Multiple Levels of Index 623
14.1.5 Secondary Indexes 624
14.1.6 Applications of Secondary Indexes 625
14.1.7 Indirection in Secondary Indexes 626
14.1.8 Document Retrieval and Inverted Indexes 628
14.1.9 Exercises for Section 14.1 631
14.2 B-Trees 633
14.2.1 The Structure of B-trees 634
14.2.2 Applications of B-trees 637
14.2.3 Lookup in B-Trees 639
14.2.4 Range Queries 639
14.2.5 Insertion Into B-Trees 640
14.2.6 Deletion From B-Trees 642
14.2.7 Efficiency of B-Trees 645
14.2.8 Exercises for Section 14.2 646
14.3 Hash Tables 648
14.3.1 Secondary-Storage Hash Tables 649
14.3.2 Insertion Into a Hash Table 649
14.3.3 Hash-Table Deletion 650
14.3.4 Efficiency of Hash Table Indexes 651
14.3.5 Extensible Hash Tables 652
14.3.6 Insertion Into Extensible Hash Tables 653
14.3.7 Linear Hash Tables 655
14.3.8 Insertion Into Linear Hash Tables 657
14.3.9 Exercises for Section 14.3 659
14.4 Multidimensional Indexes 661
14.4.1 Applications of Multidimensional Indexes 661
14.4.2 Executing Range Queries Using Conventional Indexes 663
14.4.3 Executing Nearest-Neighbor Queries Using Conventional Indexes 664
14.4.4 Overview of Multidimensional Index Structures 664
14.5 Hash Structures for Multidimensional Data 665
14.5.1 Grid Files 665
14.5.2 Lookup in a Grid File 666
14.5.3 Insertion Into Grid Files 667
14.5.4 Performance of Grid Files 669
14.5.5 Partitioned Hash Functions 671
14.5.6 Comparison of Grid Files and Partitioned Hashing 673
14.5.7 Exercises for Section 14.5 673
14.6 Tree Structures for Multidimensional Data 675
14.6.1 Multiple-Key Indexes 675
14.6.2 Performance of Multiple-Key Indexes 676
14.6.3 kd-Trees 677
14.6.4 Operations on kd-Trees 679
14.6.5 Adapting kd-Trees to Secondary Storage 681
14.6.6 Quad Trees 681
14.6.7 R-Trees 683
14.6.8 Operations on R-Trees 684
14.6.9 Exercises for Section 14.6 686
14.7 Bitmap Indexes 688
14.7.1 Motivation for Bitmap Indexes 689
14.7.2 Compressed Bitmaps 691
14.7.3 Operating on Run-Length-Encoded Bit-Vectors 693
14.7.4 Managing Bitmap Indexes 693
14.7.5 Exercises for Section 14.7 695
14.8 Summary of Chapter 14 695
14.9 References for Chapter 14 697
15 Query Execution 701
15.1 Introduction to Physical-Query-Plan Operators 703
15.1.1 Scanning Tables 703
15.1.2 Sorting While Scanning Tables 704
15.1.3 The Computation Model for Physical Operators 704
15.1.4 Parameters for Measuring Costs 705
15.1.5 I/O Cost for Scan Operators 706
15.1.6 Iterators for Implementation of Physical Operators 707
15.2 One-Pass Algorithms 709
15.2.1 One-Pass Algorithms for Tuple-at-a-Time Operations 711
15.2.2 One-Pass Algorithms for Unary，Full-Relation Operations 712
15.2.3 One-Pass Algorithms for Binary Operations 715
15.2.4 Exercises for Section 15.2 718
15.3 Nested-Loop Joins 718
15.3.1 Tuple-Based Nested-Loop Join 719
15.3.2 An Iterator for Tuple-Based Nested-Loop Join 719
15.3.3 Block-Based Nested-Loop Join Algorithm 719
15.3.4 Analysis of Nested-Loop Join 721
15.3.5 Summary of Algorithms so Far 722
15.3.6 Exercises for Section 15.3 722
15.4 Two-Pass Algorithms Based on Sorting 723
15.4.1 Two-Phase，Multiway Merge-Sort 723
15.4.2 Duplicate Elimination Using Sorting 725
15.4.3 Grouping and Aggregation Using Sorting 726
15.4.4 A Sort-Based Union Algorithm 726
15.4.5 Sort-Based Intersection and Difference 727
15.4.6 A Simple Sort-Based Join Algorithm 728
15.4.7 Analysis of Simple Sort-Join 729
15.4.8 A More Efficient Sort-Based Join 729
15.4.9 Summary of Sort-Based Algorithms 730
15.4.10 Exercises for Section 15.4 730
15.5 Two-Pass Algorithms Based on Hashing 732
15.5.1 Partitioning Relations by Hashing 732
15.5.2 A Hash-Based Algorithm for Duplicate Elimination 732
15.5.3 Hash-Based Grouping and Aggregation 733
15.5.4 Hash-Based Union，Intersection，and Difference 734
15.5.5 The Hash-Join Algorithm 734
15.5.6 Saving Some Disk I/O’s 735
15.5.7 Summary of Hash-Based Algorithms 737
15.5.8 Exercises for Section 15.5 738
15.6 Index-Based Algorithms 739
15.6.1 Clustering and Nonclustering Indexes 739
15.6.2 Index-Based Selection 740
15.6.3 Joining by Using an Index 742
15.6.4 Joins Using a Sorted Index 743
15.6.5 Exercises for Section 15.6 745
15.7 Buffer Management 746
15.7.1 Buffer Management Architecture 746
15.7.2 Buffer Management Strategies 747
15.7.3 The Relationship Between Physical Operator Selection and Buffer Management 750
15.7.4 Exercises for Section 15.7 751
15.8 Algorithms Using More Than Two Passes 752
15.8.1 Multipass Sort-Based Algorithms 752
15.8.2 Performance of Multipass，Sort-Based Algorithms 753
15.8.3 Multipass Hash-Based Algorithms 754
15.8.4 Performance of Multipass Hash-Based Algorithms 754
15.8.5 Exercises for Section 15.8 755
15.9 Summary of Chapter 15 756
15.10References for Chapter 15 757
16 The Query Compiler 759
16.1 Parsing and Preprocessing 760
16.1.1 Syntax Analysis and Parse Trees 760
16.1.2 A Grammar for a Simple Subset of SQL 761
16.1.3 The Preprocessor 764
16.1.4 Preprocessing Queries Involving Views 765
16.1.5 Exercises for Section 16.1 767
16.2 Algebraic Laws for Improving Query Plans 768
16.2.1 Commutative and Associative Laws 768
16.2.2 Laws Involving Selection 770
16.2.3 Pushing Selections 772
16.2.4 Laws Involving Projection 774
16.2.5 Laws About Joins and Products 776
16.2.6 Laws Involving Duplicate Elimination 777
16.2.7 Laws Involving Grouping and Aggregation 777
16.2.8 Exercises for Section 16.2 780
16.3 From Parse Trees to Logical Query Plans 781
16.3.1 Conversion to Relational Algebra 782
16.3.2 Removing Subqueries From Conditions 783
16.3.3 Improving the Logical Query Plan 788
16.3.4 Grouping Associative/ Commutative Operators 790
16.3.5 Exercises for Section 16.3 791
16.4 Estimating the Cost of Operations 792
16.4.1 Estimating Sizes of Intermediate Relations 793
16.4.2 Estimating the Size of a Projection 794
16.4.3 Estimating the Size of a Selection 794
16.4.4 Estimating the Size of a Join 797
16.4.5 Natural Joins With Multiple Join Attributes 799
16.4.6 Joins of Many Relations 800
16.4.7 Estimating Sizes for Other Operations 801
16.4.8 Exercises for Section 16.4 802
16.5 Introduction to Cost-Based Plan Selection 803
16.5.1 Obtaining Estimates for Size Parameters 804
16.5.2 Computation of Statistics 807
16.5.3 Heuristics for Reducing the Cost of Logical Query Plans 808
16.5.4 Approaches to Enumerating Physical Plans 810
16.5.5 Exercises for Section 16.5 813
16.6 Choosing an Order for Joins 814
16.6.1 Significance of Left and Right Join Arguments 815
16.6.2 Join Trees 815
16.6.3 Left-Deep Join Trees 816
16.6.4 Dynamic Programming to Select a Join Order and Grouping 819
16.6.5 Dynamic Programming With More Detailed Cost Functions 823
16.6.6 A Greedy Algorithm for Selecting a Join Order 824
16.6.7 Exercises for Section 16.6 825
16.7 Completing the Physical-Query-Plan 826
16.7.1 Choosing a Selection Method 827
16.7.2 Choosing a Join Method 829
16.7.3 Pipelining Versus Materialization 830
16.7.4 Pipelining Unary Operations 830
16.7.5 Pipelining Binary Operations 830
16.7.6 Notation for Physical Query Plans 834
16.7.7 Ordering of Physical Operations 837
16.7.8 Exercises for Section 16.7 838
16.8 Summary of Chapter 16 839
16.9 References for Chapter 16 841
17 Coping With System Failures 843
17.1 Issues and Models for Resilient Operation 843
17.1.1 Failure Modes 844
17.1.2 More About Transactions 845
17.1.3 Correct Execution of Transactions 846
17.1.4 The Primitive Operations of Transactions 848
17.1.5 Exercises for Section 17.1 851
17.2 Undo Logging 851
17.2.1 Log Records 851
17.2.2 The Undo-Logging Rules 853
17.2.3 Recovery Using Undo Logging 855
17.2.4 Checkpointing 857
17.2.5 Nonquiescent Checkpointing 858
17.2.6 Exercises for Section 17.2 862
17.3 Redo Logging 863
17.3.1 The Redo-Logging Rule 863
17.3.2 Recovery With Redo Logging 864
17.3.3 Checkpointing a Redo Log 866
17.3.4 Recovery With a Checkpointed Redo Log 867
17.3.5 Exercises for Section 17.3 868
17.4 Undo/Redo Logging 869
17.4.1 The Undo/Redo Rules 870
17.4.2 Recovery With Undo/Redo Logging 870
17.4.3 Checkpointing an Undo/Redo Log 872
17.4.4 Exercises for Section 17.4 874
17.5 Protecting Against Media Failures 875
17.5.1 The Archive 875
17.5.2 Nonquiescent Archiving 875
17.5.3 Recovery Using an Archive and Log 878
17.5.4 Exercises for Section 17.5 879
17.6 Summary of Chapter 17 879
17.7 References for Chapter 17 881
18 Concurrency Control 883
18.1 Serial and Serializable Schedules 884
18.1.1 Schedules 884
18.1.2 Serial Schedules 885
18.1.3 Serializable Schedules 886
18.1.4 The Effect of Transaction Semantics 887
18.1.5 A Notation for Transactions and Schedules 889
18.1.6 Exercises for Section 18.1 889
18.2 Conflict-Serializability 890
18.2.1 Conflicts 890
18.2.2 Precedence Graphs and a Test for Conflict-Serializability 892
18.2.3 Why the Precedence-Graph Test Works 894
18.2.4 Exercises for Section 18.2 895
18.3 Enforcing Serializability by Locks 897
18.3.1 Locks 898
18.3.2 The Locking Scheduler 900
18.3.3 Two-Phase Locking 900
18.3.4 Why Two-Phase Locking Works 901
18.3.5 Exercises for Section 18.3 903
18.4 Locking Systems With Several Lock Modes 905
18.4.1 Shared and Exclusive Locks 905
18.4.2 Compatibility Matrices 907
18.4.3 Upgrading Locks 908
18.4.4 Update Locks 909
18.4.5 Increment Locks 911
18.4.6 Exercises for Section 18.4 913
18.5 An Architecture for a Locking Scheduler 915
18.5.1 A Scheduler That Inserts Lock Actions 915
18.5.2 The Lock Table 918
18.5.3 Exercises for Section 18.5 921
18.6 Hierarchies of Database Elements 921
18.6.1 Locks With Multiple Granularity 921
18.6.2 Warning Locks 922
18.6.3 Phantoms and Handling Insertions Correctly 926
18.6.4 Exercises for Section 18.6 927
18.7 The Tree Protocol 927
18.7.1 Motivation for Tree-Based Locking 927
18.7.2 Rules for Access to Tree-Structured Data 928
18.7.3 Why the Tree Protocol Works 929
18.7.4 Exercises for Section 18.7 932
18.8 Concurrency Control by Timestamps 933
18.8.1 Timestamps 934
18.8.2 Physically Unrealizable Behaviors 934
18.8.3 Problems With Dirty Data 935
18.8.4 The Rules for Timestamp-Based Scheduling 937
18.8.5 Multiversion Timestamps 939
18.8.6 Timestamps Versus Locking 941
18.8.7 Exercises for Section 18.8 942
18.9 Concurrency Control by Validation 942
18.9.1 Architecture of a Validation-Based Scheduler 942
18.9.2 The Validation Rules 943
18.9.3 Comparison of Three Concurrency-Control Mechanisms 946
18.9.4 Exercises for Section 18.9 948
18.10Summary of Chapter 18 948
18.11References for Chapter 18 950
19 More About Transaction Management 953
19.1 Serializability and Recoverability 953
19.1.1 The Dirty-Data Problem 954
19.1.2 Cascading Rollback 955
19.1.3 Recoverable Schedules 956
19.1.4 Schedules That Avoid Cascading Rollback 957
19.1.5 Managing Rollbacks Using Locking 957
19.1.6 Group Commit 959
19.1.7 Logical Logging 960
19.1.8 Recovery From Logical Logs 963
19.1.9 Exercises for Section 19.1 965
19.2 Deadlocks 966
19.2.1 Deadlock Detection by Timeout 967
19.2.2 The Waits-For Graph 967
19.2.3 Deadlock Prevention by Ordering Elements 970
19.2.4 Detecting Deadlocks by Timestamps 970
19.2.5 Comparison of Deadlock-Management Methods 972
19.2.6 Exercises for Section 19.2 974
19.3 Long-Duration Transactions 975
19.3.1 Problems of Long Transactions 976
19.3.2 Sagas 978
19.3.3 Compensating Transactions 979
19.3.4 Why Compensating Transactions Work 980
19.3.5 Exercises for Section 19.3 981
19.4 Summary of Chapter 19 982
19.5 References for Chapter 19 983
20 Parallel and Distributed Databases 985
20.1 Parallel Algorithms on Relations 985
20.1.1 Models of Parallelism 986
20.1.2 Tuple-at-a-Time Operations in Parallel 989
20.1.3 Parallel Algorithms for Full-Relation Operations 989
20.1.4 Performance of Parallel Algorithms 990
20.1.5 Exercises for Section 20.1 993
20.2 The Map-Reduce Parallelism Framework 993
20.2.1 The Storage Model 993
20.2.2 The Map Function 994
20.2.3 The Reduce Function 995
20.2.4 Exercises for Section 20.2 996
20.3 Distributed Databases 997
20.3.1 Distribution of Data 997
20.3.2 Distributed Transactions 998
20.3.3 Data Replication 999
20.3.4 Exercises for Section 20.3 1000
20.4 Distributed Query Processing 1000
20.4.1 The Distributed Join Problem 1000
20.4.2 Semijoin Reductions 1001
20.4.3 Joins of Many Relations 1002
20.4.4 Acyclic Hypergraphs 1003
20.4.5 Full Reducers for Acyclic Hypergraphs 1005
20.4.6 Why the Full-Reducer Algorithm Works 1006
20.4.7 Exercises for Section 20.4 1007
20.5 Distributed Commit 1008
20.5.1 Supporting Distributed Atomicity 1008
20.5.2 Two-Phase Commit 1009
20.5.3 Recovery of Distributed Transactions 1011
20.5.4 Exercises for Section 20.5 1013
20.6 Distributed Locking 1014
20.6.1 Centralized Lock Systems 1015
20.6.2 A Cost Model for Distributed Locking Algorithms 1015
20.6.3 Locking Replicated Elements 1016
20.6.4 Primary-Copy Locking 1017
20.6.5 Global Locks From Local Locks 1017
20.6.6 Exercises for Section 20.6 1019
20.7 Peer-to-Peer Distributed Search 1020
20.7.1 Peer-to-Peer Networks 1020
20.7.2 The Distributed-Hashing Problem 1021
20.7.3 Centralized Solutions for Distributed Hashing 1022
20.7.4 Chord Circles 1022
20.7.5 Links in Chord Circles 1024
20.7.6 Search Using Finger Tables 1024
20.7.7 Adding New Nodes 1027
20.7.8 When a Peer Leaves the Network 1030
20.7.9 When a Peer Fails 1030
20.7.10 Exercises for Section 20.7 1031
20.8 Summary of Chapter 20 1031
20.9 References for Chapter 20 1033
Ⅴ Other Issues in Management of Massive Data 1035
21 Information Integration 1037
21.1 Introduction to Information Integration 1037
21.1.1 Why Information Integration？ 1038
21.1.2 The Heterogeneity Problem 1040
21.2 Modes of Information Integration 1041
21.2.1 Federated Database Systems 1042
21.2.2 Data Warehouses 1043
21.2.3 Mediators 1046
21.2.4 Exercises for Section 21.2 1048
21.3 Wrappers in Mediator-Based Systems 1049
21.3.1 Templates for Query Patterns 1050
21.3.2 Wrapper Generators 1051
21.3.3 Filters 1052
21.3.4 Other Operations at the Wrapper 1053
21.3.5 Exercises for Section 21.3 1054
21.4 Capability-Based Optimization 1056
21.4.1 The Problem of Limited Source Capabilities 1056
21.4.2 A Notation for Describing Source Capabilities 1057
21.4.3 Capability-Based Query-Plan Selection 1058
21.4.4 Adding Cost-Based Optimization 1060
21.4.5 Exercises for Section 21.4 1060
21.5 Optimizing Mediator Queries 1061
21.5.1 Simplified Adornment Notation 1061
21.5.2 Obtaining Answers for Subgoals 1062
21.5.3 The Chain Algorithm 1063
21.5.4 Incorporating Union Views at the Mediator 1067
21.5.5 Exercises for Section 21.5 1068
21.6 Local-as-View Mediators 1069
21.6.1 Motivation for LAV Mediators 1069
21.6.2 Terminology for LAV Mediation 1070
21.6.3 Expanding Solutions 1071
21.6.4 Containment of Conjunctive Queries 1073
21.6.5 Why the Containment-Mapping Test Works 1075
21.6.6 Finding Solutions to a Mediator Query 1076
21.6.7 Why the LMSS Theorem Holds 1077
21.6.8 Exercises for Section 21.6 1078
21.7 Entity Resolution 1078
21.7.1 Deciding Whether Records Represent a Common Entity 1079
21.7.2 Merging Similar Records 1081
21.7.3 Useful Properties of Similarity and Merge Functions 1082
21.7.4 The R-Swoosh Algorithm for ICAR Records 1083
21.7.5 Why R-Swoosh Works 1086
21.7.6 Other Approaches to Entity Resolution 1086
21.7.7 Exercises for Section 21.7 1087
21.8 Summary of Chapter 21 1089
21.9 References for Chapter 21 1091
22 Data Mining 1093
22.1 Frequent-Itemset Mining 1093
22.1.1 The Market-Basket Model 1094
22.1.2 Basic Definitions 1095
22.1.3 Association Rules 1097
22.1.4 The Computation Model for Frequent Itemsets 1098
22.1.5 Exercises for Section 22.1 1099
22.2 Algorithms for Finding Frequent Itemsets 1100
22.2.1 The Distribution of Frequent Itemsets 1100
22.2.2 The Naive Algorithm for Finding Frequent Itemsets 1101
22.2.3 The A-Priori Algorithm 1102
22.2.4 Implementation of the A-Priori Algorithm 1104
22.2.5 Making Better Use of Main Memory 1105
22.2.6 When to Use the PCY Algorithm 1106
22.2.7 The Multistage Algorithm 1107
22.2.8 Exercises for Section 22.2 1109
22.3 Finding Similar Items 1110
22.3.1 The Jaccard Measure of Similarity 1110
22.3.2 Applications of Jaccard Similarity 1110
22.3.3 Minhashing 1112
22.3.4 Minhashing and Jaccard Distance 1113
22.3.5 Why Minhashing Works 1113
22.3.6 Implementing Minhashing 1114
22.3.7 Exercises for Section 22.3 1115
22.4 Locality-Sensitive Hashing 1116
22.4.1 Entity Resolution as an Example of LSH 1117
22.4.2 Locality-Sensitive Hashing of Signatures 1118
22.4.3 Combining Minhashing and Locality-Sensitive Hashing 1121
22.4.4 Exercises for Section 22.4 1122
22.5 Clustering of Large-Scale Data 1123
22.5.1 Applications of Clustering 1123
22.5.2 Distance Measures 1125
22.5.3 Agglomerative Clustering 1128
22.5.4 k-Means Algorithms 1130
22.5.5 k-Means for Large-Scale Data 1132
22.5.6 Processing a Memory Load of Points 1133
22.5.7 Exercises for Section 22.5 1136
22.6 Summary of Chapter 22 1137
22.7 References for Chapter 22 1139
23 Database Systems and the Internet 1141
23.1 The Architecture of a Search Engine 1141
23.1.1 Components of a Search Engine 1142
23.1.2 Web Crawlers 1143
23.1.3 Query Processing in Search Engines 1146
23.1.4 Ranking Pages 1146
23.2 PageRank for Identifying Important Pages 1147
23.2.1 The Intuition Behind PageRank 1147
23.2.2 Recursive Formulation of PageRank — First Try 1148
23.2.3 Spider Traps and Dead Ends 1150
23.2.4 PageRank Accounting for Spider Traps and Dead Ends 1153
23.2.5 Exercises for Section 23.2 1154
23.3 Topic-Specific PageRank 1156
23.3.1 Teleport Sets 1156
23.3.2 Calculating A Topic-Specific PageRank 1158
23.3.3 Link Spam 1159
23.3.4 Topic-Specific PageRank and Link Spam 1160
23.3.5 Exercises for Section 23.3 1161
23.4 Data Streams 1161
23.4.1 Data-Stream-Management Systems 1162
23.4.2 Stream Applications 1163
23.4.3 A Data-Stream Data Model 1164
23.4.4 Converting Streams Into Relations 1165
23.4.5 Converting Relations Into Streams 1166
23.4.6 Exercises for Section 23.4 1168
23.5 Data Mining of Streams 1169
23.5.1 Motivation 1169
23.5.2 Counting Bits 1171
23.5.3 Counting the Number of Distinct Elements 1175
23.5.4 Exercises for Section 23.5 1176
23.6 Summary of Chapter 23 1177
23.7 References for Chapter 23 1179
Index 1183