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The Entity-Relationship Model 35 wi
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The Entity-Relationship Model 37 Mo
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The Entity-Relationship Model 39 2.
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The Entity-Relationship Model 41 Bu
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The Entity-Relationship Model 43 na
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The Entity-Relationship Model 45 An
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The Entity-Relationship Model 47 Gr
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The Entity-Relationship Model 49 Fo
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3 THE RELATIONAL MODEL TABLE: An ar
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The Relational Model 53 is a table,
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The Relational Model 55 The degree,
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The Relational Model 57 condition t
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The Relational Model 59 Specifying
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The Relational Model 61 cid CHAR(20
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The Relational Model 63 discuss the
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The Relational Model 65 The symbol
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The Relational Model 67 3.5.1 Entit
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The Relational Model 69 specify tha
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The Relational Model 71 CREATE TABL
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The Relational Model 73 To ensure t
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The Relational Model 75 1. We can m
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The Relational Model 77 name ssn lo
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The Relational Model 79 name sid co
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The Relational Model 81 Clubs(cname
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The Relational Model 83 ALTER TABLE
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The Relational Model 85 2. Write th
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The Relational Model 87 Integrity c
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4 RELATIONAL ALGEBRA AND CALCULUS S
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Relational Algebra and Calculus 93
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Relational Algebra and Calculus 117
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5 SQL: QUERIES, PROGRAMMING, TRIGGE
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SQL: Queries, Programming, Triggers
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6 QUERY-BY-EXAMPLE (QBE) Example is
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Query-by-Example (QBE) 179 intuitiv
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Query-by-Example (QBE) 181 Notice h
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Query-by-Example (QBE) 183 6.6 THE
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Query-by-Example (QBE) 185 Sailors
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Query-by-Example (QBE) 187 Sailors
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Query-by-Example (QBE) 189 two logi
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Query-by-Example (QBE) 191 Supplier
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PARTIII DATA STORAGE AND INDEXING
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196 Chapter 7 7.1 THE MEMORY HIERAR
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198 Chapter 7 single-sided or doubl
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200 Chapter 7 (This observation is
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202 Chapter 7 since the disk wears
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204 Chapter 7 Level 0+1: Striping a
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206 Chapter 7 A RAID Level 5 system
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208 Chapter 7 instructions: “Read
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210 Chapter 7 Incrementing pin coun
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212 Chapter 7 Buffer management in
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214 Chapter 7 7.5 FILES AND INDEXES
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216 Chapter 7 Directory of Pages An
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218 Chapter 7 Rids in commercial sy
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220 Chapter 7 in order to ensure th
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222 Chapter 7 Record formats in com
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224 Chapter 7 Large records in real
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226 Chapter 7 EXERCISES Exercise 7.
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228 Chapter 7 Exercise 7.19 Conside
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8 FILE ORGANIZATIONS & INDEXES If y
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232 Chapter 8 8.2 COMPARISON OF THR
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234 Chapter 8 file. We can locate t
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236 Chapter 8 be scanned.) The cost
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238 Chapter 8 age h1 h(age)=00 h(ag
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240 Chapter 8 Indexes that maintain
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242 Chapter 8 records in the data f
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244 Chapter 8 8.5 INDEX SPECIFICATI
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246 Chapter 8 sid name login age gp
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248 Chapter 9 9.1 INDEXED SEQUENTIA
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250 Chapter 9 Data Pages Index Page
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252 Chapter 9 placeholder for futur
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254 Chapter 9 Index entries (Direct
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256 Chapter 9 func find (search key
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258 Chapter 9 proc insert (nodepoin
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260 Chapter 9 sibling of this leaf
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262 Chapter 9 proc delete (parentpo
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264 Chapter 9 Root 5 13 17 30 2* 3*
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266 Chapter 9 Duplicate handling in
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268 Chapter 9 Daniel Lee David Smit
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270 Chapter 9 We have redistributed
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272 Chapter 9 9.8.4 The Effect of I
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274 Chapter 9 A B C 10 20 30 80 I1
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276 Chapter 9 1. How many levels do
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10 HASH-BASED INDEXING Not chaos-li
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280 Chapter 10 The main problem wit
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282 Chapter 10 Next, let us conside
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284 Chapter 10 LOCAL DEPTH GLOBAL D
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286 Chapter 10 10.3 LINEAR HASHING
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288 Chapter 10 conditions based on
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290 Chapter 10 Level=0 h1 h0 PRIMAR
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292 Chapter 10 We observe that the
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294 Chapter 10 3 64 16 Bucket A 000
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296 Chapter 10 3. Static Hashing ve
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298 Chapter 10 BIBLIOGRAPHIC NOTES
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11 EXTERNAL SORTING Good order is t
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External Sorting 303 proc 2-way ext
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External Sorting 305 11.2 EXTERNAL
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External Sorting 307 As an example,
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External Sorting 309 the current ru
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External Sorting 311 N B=1,000 B=5,
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External Sorting 313 Index entries
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External Sorting 315 N Sorting p=1
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External Sorting 317 2. How many pa
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12 EVALUATION OF RELATIONAL OPERATO
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Evaluation of Relational Operators
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Evaluation of Relational Operators
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13 INTRODUCTION TO QUERY OPTIMIZATI
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A Typical Relational Query Optimize
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15 SCHEMA REFINEMENT AND NORMAL FOR
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Schema Refinement and Normal Forms
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16 PHYSICAL DATABASE DESIGN AND TUN
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Physical Database Design and Tuning
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17 SECURITY I know that’s a secre
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Security 499 the GRANT and REVOKE c
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Security 501 Role-based authorizati
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Security 503 Suppose that this comm
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Security 505 the name of the object
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Security 507 System (System, Joe, S
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Security 509 unauthorized user can
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Security 511 bid bname color Securi
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Security 513 example, military data
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Security 515 Another approach to en
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Security 517 Further, because the c
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Security 519 1. Show the view defin
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PARTVI TRANSACTION MANAGEMENT
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524 Chapter 18 an execution of a us
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526 Chapter 18 Of course, since use
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528 Chapter 18 18.3.2 Serializabili
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530 Chapter 18 to another, a transa
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532 Chapter 18 There is another pot
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534 Chapter 18 T 1 T 2 X(A) R(A) W
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536 Chapter 18 if there is a subseq
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538 Chapter 18 whose effect is iden
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19 CONCURRENCY CONTROL Pooh was sit
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542 Chapter 19 T1 T2 T1 T2 (a) (b)
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544 Chapter 19 the data object iden
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546 Chapter 19 19.2.2 Deadlocks Con
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548 Chapter 19 T1 T2 T1 T2 T4 T3 T4
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550 Chapter 19 If the collection of
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552 Chapter 19 that exploit the hie
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554 Chapter 19 This approach improv
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556 Chapter 19 or a CREATE TABLE st
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558 Chapter 19 smaller number of lo
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560 Chapter 19 If, indeed, there ar
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562 Chapter 19 The Thomas Write Rul
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564 Chapter 19 What do real systems
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566 Chapter 19 EXERCISES Exercise 1
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568 Chapter 19 View Serializable Al
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570 Chapter 19 BIBLIOGRAPHIC NOTES
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572 Chapter 20 2. Redo: Repeats all
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574 Chapter 20 For recovery purpose
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576 Chapter 20 transaction for whic
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578 Chapter 20 Further, the log is
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580 Chapter 20 step. See Exercise 2
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582 Chapter 20 because either this
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584 Chapter 20 T 1000 while T 1000
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586 Chapter 20 This example illustr
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588 Chapter 20 the original page. T
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590 Chapter 20 LSN 00 10 20 30 40 5
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592 Chapter 20 LSN LOG 00 begin_che
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PARTVII ADVANCED TOPICS
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598 Chapter 21 sites have a signifi
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600 Chapter 21 SPEED-UP SCALE-UP wi
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602 Chapter 21 A parallel evaluatio
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604 Chapter 21 the join of A and B;
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606 Chapter 21 21.4 PARALLEL QUERY
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608 Chapter 21 The key to building
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610 Chapter 21 21.7 STORING DATA IN
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612 Chapter 21 21.8.1 Naming Object
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614 Chapter 21 21.9 DISTRIBUTED QUE
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616 Chapter 21 we will assume that
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618 Chapter 21 that only 20 percent
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620 Chapter 21 should be transparen
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622 Chapter 21 Frankfurt, and salar
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624 Chapter 21 Data Warehousing: An
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626 Chapter 21 For example, suppose
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628 Chapter 21 21.13.1 Normal Execu
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630 Chapter 21 recovers; we say tha
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632 Chapter 21 21.13.4 Three-Phase
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634 Chapter 21 periodically. There
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636 Chapter 21 1. Find the highest
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638 Chapter 21 1. Half the departme
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640 Chapter 21 10. Suppose that 2PC
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22 INTERNET DATABASES He profits mo
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644 Chapter 22 Science: Author:
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646 Chapter 22 The Database Booksto
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648 Chapter 22 #!/usr/bin/perl use
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650 Chapter 22 Web Browser HTTP Web
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652 Chapter 22 The design goals of
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654 Chapter 22 RichardFeynman
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656 Chapter 22 Until now we only c
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658 Chapter 22 even when two elemen
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660 Chapter 22 a LASTNAME element.
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662 Chapter 22 BOOK BOOK BOOK AUTHO
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664 Chapter 22 There are two common
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666 Chapter 22 A query containing a
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668 Chapter 22 breadth. Thus, query
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670 Chapter 22 Computing hub and au
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672 Chapter 22 and are said to be s
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674 Chapter 22 Exercise 22.5 Consid
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676 Chapter 22 advanced reader have
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678 Chapter 23 from many sources in
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680 Chapter 23 to achieve satisfact
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682 Chapter 23 query engines, data
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684 Chapter 23 country, state, andc
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686 Chapter 23 sales for each locat
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688 Chapter 23 CUBE pid, locid, tim
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690 Chapter 23 Beyond B+ trees: Com
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692 Chapter 23 bit vector for a giv
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694 Chapter 23 by the database desi
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696 Chapter 23 FROM Products P, Sal
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698 Chapter 23 23.5.4 Issues in Vie
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700 Chapter 23 23.6.1 Top N Queries
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702 Chapter 23 STATUS PRIORITIZE st
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704 Chapter 23 2. What is the relat
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706 Chapter 23 1. How is the follow
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708 Chapter 24 Finding useful trend
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710 Chapter 24 Usually the number o
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712 Chapter 24 such that the custom
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714 Chapter 24 24.3.1 Association R
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716 Chapter 24 transid custid date
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718 Chapter 24 We begin by introduc
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720 Chapter 24 tion on the basis of
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722 Chapter 24 depends on the measu
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724 Chapter 24 Input: noden, partit
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726 Chapter 24 WHERE R.age
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728 Chapter 24 Salary C 60k 30k A B
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730 Chapter 24 from another sequenc
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732 Chapter 24 24.8 POINTS TO REVIE
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734 Chapter 24 3. Illustrate your a
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25 OBJECT-DATABASE SYSTEMS with Jos
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738 Chapter 25 than the dollars and
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740 Chapter 25 1. CREATE TABLE Fram
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742 Chapter 25 25.2 USER-DEFINED AB
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744 Chapter 25 the DBMS uses a Java
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746 Chapter 25 gives us a collectio
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748 Chapter 25 Objects and oids: In
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750 Chapter 25 As an example, consi
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752 Chapter 25 for JPEG images and
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754 Chapter 25 camera: string, vide
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756 Chapter 25 25.6.2 Object Identi
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758 Chapter 25 pid camera listof(ro
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760 Chapter 25 25.7.1 Storage and A
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762 Chapter 25 User-Defined Aggrega
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764 Chapter 25 Optimizer extensibil
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766 Chapter 25 Class = interface +
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768 Chapter 25 An object of class S
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770 Chapter 25 25.9.2 OODBMS versus
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772 Chapter 25 nonreference types i
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774 Chapter 25 All tuples for all k
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776 Chapter 25 Array chunking is de
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778 Chapter 26 obtained through mea
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780 Chapter 26 between the wheel an
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782 Chapter 26 index will fully uti
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784 Chapter 26 The advantage of thi
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786 Chapter 26 and with radius r. W
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788 Chapter 26 2 1, 2, 3 A 2 1, 2,
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790 Chapter 26 Figure 26.6 shows tw
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792 Chapter 26 26.6.2 Insert and De
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794 Chapter 26 page that contains o
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796 Chapter 26 data, and multimedia
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798 Chapter 26 2. Assume that delet
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800 Chapter 27 Recursion in SQL: Th
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802 Chapter 27 by setting Part=trik
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804 Chapter 27 of relational calcul
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806 Chapter 27 According to this ru
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808 Chapter 27 by repeatedly evalua
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810 Chapter 27 We say that a table
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812 Chapter 27 Big2(Part) AS (SELEC
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814 Chapter 27 Unnecessary inferenc
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816 Chapter 27 27.4.2 Pushing Selec
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818 Chapter 27 When a query is pose
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820 Chapter 27 4. Write a program i
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28 ADDITIONAL TOPICS This is not th
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824 Chapter 28 actions, locks held
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826 Chapter 28 design decisions, si
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828 Chapter 28 discussed in Chapter
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830 Chapter 28 chapter illustrates,
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832 Appendix A A.2 CONCEPTUAL DESIG
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834 Appendix A the importance of th
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836 Appendix A author qty_in_stock
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838 Appendix A A.5.1 Tuning the Dat
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840 Appendix A A.7 APPLICATION LAYE
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B THE MINIBASE SOFTWARE Practice is
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844 Appendix B variants include fix
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REFERENCES [1] R. Abbott and H. Gar
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REFERENCES 849 [39] P. Atzeni, G. M
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REFERENCES 851 [84] J. Biskup and B
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REFERENCES 853 [128] D. Chamberlin.
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REFERENCES 855 [177] C. Delobel. No
- Page 881 and 882:
REFERENCES 857 [224] C. Faloutsos,
- Page 883 and 884:
REFERENCES 859 [270] D. Gifford. We
- Page 885 and 886:
REFERENCES 861 [315] J. Hellerstein
- Page 887 and 888:
REFERENCES 863 [363] L. Kerschberg,
- Page 889 and 890:
REFERENCES 865 [410] T. Leung and R
- Page 891 and 892:
REFERENCES 867 [455] J. Melton and
- Page 893 and 894:
REFERENCES 869 [500] P. O’Neil an
- Page 895 and 896:
REFERENCES 871 [544] A. Reuter. Per
- Page 897 and 898:
REFERENCES 873 [589] D. Shasha. Dat
- Page 899 and 900:
REFERENCES 875 [636] W. Sun, Y. Lin
- Page 901 and 902:
REFERENCES 877 [682] R. Williams, D
- Page 903 and 904:
SUBJECT INDEX 1NF, 430 2NF, 434 2PC
- Page 905 and 906:
Subject Index 881 Complete axioms,
- Page 907 and 908:
Subject Index 883 global object nam
- Page 909 and 910:
Subject Index 885 Granting privileg
- Page 911 and 912:
Subject Index 887 Local depth in ex
- Page 913 and 914:
Subject Index 889 Order of a B+ tre
- Page 915 and 916:
Subject Index 891 oids, 757 violati
- Page 917 and 918:
Subject Index 893 cursors, 153 orde
- Page 919 and 920:
895 Tuning, 26, 457, 459, 474 Tunin
- Page 921 and 922:
Author Index 897 Breitbart, Y., 641
- Page 923 and 924:
Author Index 899 Gehani, N.H., 176,
- Page 925 and 926:
Author Index 901 Lebowitz, F., 91 L
- Page 927 and 928:
Author Index 903 Prescod, P., 675,
- Page 929 and 930:
Author Index 905 Swagerman, R., 776