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Properties of Transactions � Consistency: � transactions retain internal consistency of the data base � many kinds of integrity � unique keys � referential f ti l integrity i t it � fixed relationships hold � responsibility belongs to the programmer, not to the data base � if each transaction is consistent, then all sequences of transactions are as well Transactions © 2009 Universität Karlsruhe, System Architecture Group 40
Properties of Transactions � Isolation: Transactions � result of running multiple concurrent transactions is the same as running them in complete isolation � often called “serializability” © 2009 Universität Karlsruhe, System Architecture Group 41
Page 1 and 2: © 2009 Universität Karlsruhe, Sys
Page 3 and 4: The Transaction Model (1) � Updat
Page 5 and 6: The Transaction Model (3) BEGIN_TRA
Page 7 and 8: Private Workspace a) The file index
Page 9 and 10: Concurrency Control (1) � General
Page 11 and 12: Serializability BEGIN_TRANSACTION x
Page 13 and 14: Two-Phase Locking (2) � Strict tw
Page 15 and 16: Transactions Transactions Notion: A
Page 17 and 18: Control of Concurrency � Critical
Page 19 and 20: Example (1) {Transfers money from A
Page 21 and 22: Example (2) “Lost Update Problem
Page 23 and 24: Motivation Critical section Waiting
Page 25 and 26: Approach 1: Strictly Serial Schedul
Page 27 and 28: Motivation Requirements for a highe
Page 29 and 30: Operations of a Transaction � An
Page 31 and 32: Example for Commit and Abort {trans
Page 33 and 34: Transactions Transaction: “End to
Page 35 and 36: Simple FTP Example Open File Locall
Page 37 and 38: Implementation Client update Server
Page 39: Requirements: ACID-Principle Atomic
Page 43 and 44: How to achieve ACID-Principle? •A
Page 45 and 46: Transaction Types � Flat Transact
Page 47 and 48: Serializability � Remember sequen
Page 49 and 50: Main Modules of Transaction Systems
Page 51 and 52: Transaction States start Undefined
Page 53 and 54: Conflicting Operations Definition:
Page 55 and 56: Schedule Transactions Definition: A
Page 57 and 58: Execution of a Schedule T1 T2 T3 re
Page 59 and 60: Recoverability Definition: A schedu
Page 61 and 62: Dirty Write (1) Initially x = 1 tim
Page 63 and 64: Dirty Write (3) Initially x = 1 tim
Page 65 and 66: Serial Schedule Transactions Defini
Page 67 and 68: How to get a Correct Schedule? Cons
Page 69 and 70: Assumptions: Serializable Transacti
Page 71 and 72: Towards Serializable Schedules Tran
Page 73 and 74: T 1 read1(x) read1(y) write1(y) wri
Page 75 and 76: T 1 read1(x) read1(y) d1( ) write1(
Page 77 and 78: Serialization Graph Definition: The
Page 79 and 80: Serializability Theorem A shedule S
Page 81 and 82: Summary of Schedules Recoverable sc
Page 83 and 84: Reordering of Commuting Operations
Page 85 and 86: T 1 read(x) write(x) read(y) write(
Page 87 and 88: T 1 read(x) write(x) read(y) write(
Page 89 and 90: Implementing Serializability � Im
Page 91 and 92:
Two Lock Types � ReadLock (shared
Page 93 and 94:
Locking Granularity in a Data Base
Page 95 and 96:
Locking Granularity in Data Base Pr
Page 97 and 98:
Two Phase Locking Protocol Result:
Page 99 and 100:
T1 T2 read_lock(x) read(x) read_unl
Page 101 and 102:
Transactions Strict 2-Phase Locking
Page 103 and 104:
Transactions start commit start com
Page 105 and 106:
Transactions Locks and Deadlocks Lo
Page 107 and 108:
Transactions Improving Locking Perf
Page 109 and 110:
Transactions Types of Failures �
Page 111 and 112:
Transactions System Crashes Causes:
Page 113 and 114:
Transactions Principal Recovery Mec
Page 115 and 116:
Transactions The Log (write-ahead l
Page 117 and 118:
Transactions Simple Recovery Algori
Page 119 and 120:
Transactions T1 last checkpoint fai
Page 121 and 122:
Transactions Cache Management Due t
Page 123 and 124:
Transactions Recovery � How to ma
Page 125 and 126:
Transactions Overview on Recovery M
Page 127 and 128:
Transactions Master Master Master D
Page 129 and 130:
Assumptions � Homogeneous system,
Page 131 and 132:
Potential Failures Network Failures
Page 133 and 134:
Coordination of Distributed Transac
Page 135:
Centralized Scheduler Analysis: �
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