File Processing : Transaction Management

1. File Processing : Transaction Management 2018, Spring Pusan National University Ki-Joune Li

2. Basic Concepts of Transaction • Transaction • A set of operations • Atomic : • All or Nothing : Consistent State of Database • Example : Flight Reservation • Cf. Partially Done : Inconsistent State

3. Transaction States the initial state; the transaction stays in this state while it is executing PartiallyCommitted Committed ALL Active NOTHING Failed Aborted after the discovery that normal execution can no longer proceed. after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. - restart the transaction or - kill the transaction

4. All State 2 Consistent State 2’ PartiallyDone Consistent Nothing ACID Properties • Atomicity. • All or Nothing • Not Partially Done • Example : Failure in Flight Reservation • Consistency. • Execution of a transaction preserves the consistency of the database. State 1

5. No Effect ACID Properties • Isolation. • Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions. • Intermediate transaction results must be hidden from other concurrently executed transactions. • Durability. • After a transaction completes successfully, the changes it has made to the database persist, even if there are system failures. DB Transation 1 Transation 2

6. Example • Transaction : Transfer $50 from account A to account B: 1. read(A) 2. A := A –50 3. write(A) 4. read(B) 5. B := B + 50 6. write(B) • Consistency requirement • the sum of A and B is unchanged after the transaction. • Atomicity requirement • Durability • Isolation

7. Example : Concurrent Execution • Two Transactions • T1 : transfer $50 from A to B, • T2 transfer 10% of the balance from A to B Serial Schedule Concurrent Schedule

8. Serializability • What happens after these transactions ? • Serial Schedule : • Always Correct • T1 T2 and T2 T1 • Concurrent Schedule • Serializable if Result (T1 || T2) = Result(T1 T2) or Result(T2 T1)

9. Transaction Management • Transaction Management • Guarantee ACID Properties of Transaction by • Concurrency Control : Isolation and Consistency • Recovery : Atomicity and Durability

10. File Processing : Concurrency Control

11. For given transactions T1, T2,.., Tn, Schedule (History) S is serializable if Result(S)  Result(Sk) where Sk is a serial excution schedule. Note that Result(Si ) may be different from Result(Sj ) (i  j ) How to detect whether S is serializable Conflict Graph Serializability

12. S2 T1 r(a) r(b) affects T2 w(a) w(b) Conflict Graph S1 r(b) T1 r(a) affects Res(S1)  Res( (T1, T2) ) T2 w(a) w(b) Res(S1)  Res( (T1, T2) ) Res(S1)  Res( (T2, T1) )

13. T1 T2 Detect Cycle in Conflict Graph • If  Cycle in Conflict Graph • Then Not Serializable • Otherwise Serializable T1 r(a) r(b) affects T2 w(a) w(b)

14. How to make it serializable Control the order of execution of operations in concurrent transactions. Two Approaches Two Phase Locking Protocol Locking on each operation Timestamping : Ordering by timestamp on each transaction and each operation How to make it serializable

15. A lock mechanism to control concurrent access to a data item Data items can be locked in two modes : Exclusive (X) mode :Data item can be both read as well as written. X-lock is requested using lock-X instruction. Shared (S) mode : Data item can only be read. S-lock is requested using lock-S instruction. Lock requests are made to concurrency-control manager. Transaction can proceed only after request is granted. Lock-Based Protocols

16. Lock-compatibility matrix A transaction may be granted a lock on an item if the requested lock is compatible with locks already held Any number of transactions can hold shared locks If a lock cannot be granted, the requesting transaction is made to wait till all incompatible locks held have been released. the lock is then granted. Lock-Based Protocols (Cont.)

17. Example of a transaction performing locking: T2: lock-S(A); read (A); unlock(A); lock-S(B); read (B); unlock(B); Lock-Based Protocols

18. This is a protocol which ensures conflict-serializable schedules. Phase 1: Growing Phase transaction may obtain locks transaction may not release locks Phase 2: Shrinking Phase transaction may release locks transaction may not obtain locks The protocol assures serializability The Two-Phase Locking Protocol

19. Two-phase locking with lock conversions: First Phase: can acquire a lock-S on item can acquire a lock-X on item can convert a lock-S to a lock-X (upgrade) Second Phase: can release a lock-S can release a lock-X can convert a lock-X to a lock-S (downgrade) This protocol assures serializability Lock Conversions

20. A transaction Ti issues the standard read/write instruction, without explicit locking calls. Automatic Acquisition of Locks The operation read(D) is processed as: if Ti has a lock on D then read(D) else begin wait until no other transaction has a lock-X on D grant Ti a lock-S on D; read(D) end Where to insert Lock related operations ?

21. write(D) is processed as: if Ti has a lock-X on D then write(D) else begin if necessary wait until no other trans. has any lock on D, if Ti has a lock-S on D then upgrade lock on D to lock-X else grant Ti a lock-X on D write(D) end; All locks are released after commit or abort Automatic Acquisition of Locks

22. Lock Manager • Transaction • Transaction sends lock request to Lock Manager • Lock Manager determines whether to allow or not • Lock Table • Keeps granted locks and pending locks for each item • In-memory Hash Table

23. Problem of Two Phase Locking Protocol • Deadlock • Growing Phase and Shrinking Phase • Prevention and Avoidance : Impossible • Only Detection may be possible • When a deadlock occurs • Detection of Deadlock : Wait-For-Graph • Abort a transaction • How to choose a transaction to kill ?

24. Tree Lock : A Special Locking Mechanism • Only exclusive locks are allowed. • The first lock by T may be on any data item. • Subsequently, a data Q can be locked by T only if the parent of Q is currently locked by T. • Data items may be unlocked at any time. Pairwise lock Not Allowed

25. Each transaction is issued a timestamp when TS(Ti) <TS(Tj) : old transaction Ti and new transaction Tj Each data Q, two timestamp : W-timestamp(Q) : largest time-stamp for successful write(Q) R-timestamp(Q) : largest time-stamp for successful read(Q) Timestamp-Based Protocols

26. Transaction Ti issues a read(Q) If TS(Ti) W-timestamp(Q), then Ti needs to read a value of Q that was already overwritten. Hence, the read operation is rejected, and Ti is rolled back. If TS(Ti) W-timestamp(Q), then the read operation is executed, and R-timestamp(Q) is set set Timestamp-Based Protocols : Read

27. Transaction Ti issues write(Q). If TS(Ti) < R-timestamp(Q), then the value of Q that Ti is producing was needed previously, and the system assumed that that value would never be produced. Hence, the write operation is rejected, and Ti is rolled back. If TS(Ti) < W-timestamp(Q), then Ti is attempting to write an obsolete value of Q. Hence, this write operation is rejected, and Ti is rolled back. Otherwise, the write operation is executed, and W-timestamp(Q) is reset Timestamp-Based Protocols : Write

28. The timestamp-ordering protocol guarantees serializability since all the arcs in the precedence graph are of the form: Thus, there will be no cycles in the conflict graph Timestamp protocol : free from deadlock Correctness of Timestamp-Ordering Protocol transaction with smaller timestamp transaction with larger timestamp

29. Rollback and Restarting Overhead Rollback and Restarting relatively more frequent than deadlock Instead of Deadlock Detection Cost ? pRB(CRB+CRStart) > pDLCDL + CDLDetect Problem of Time-Stamping Protocol

30. Long Duration Transaction • Transaction • of Long Duration • with large number of operations • Problem • Expensive rollback and restart • Degradation of concurrency • Approach • Nested Transaction • Semantic Consistency rather than Serializability

31. File Processing : Recovery

32. Transaction failure : Logical errors: internal error condition System errors: system error condition (e.g., deadlock) System crash: a power failure or other hardware or software failure Fail-stop assumption: non-volatile storage contents are assumed to not be corrupted by system crash Database systems have numerous integrity checks to prevent corruption of disk data Disk failure Failure Classification

33. Recovery Algorithms • Recovery algorithms : should ensure • database consistency • transaction atomicity and • durability despite failures • Recovery algorithms have two parts • Preparing Information for Recovery : During normal transaction • Actions taken after a failure to recover the database

34. Volatile storage: does not survive system crashes examples: main memory, cache memory Nonvolatile storage: survives system crashes examples: disk, tape, flash memory, non-volatile (battery backed up) RAM Stable storage: a mythical form of storage that survives all failures approximated by maintaining multiple copies on distinct nonvolatile media Storage Structure

35. Modifying the database must be committed Otherwise it may leave the database in an inconsistent state. Example Consider transaction Ti that transfers $50 from account A to account B; goal is either to perform all database modifications made by Tior none at all. Several output operations may be required for Ti For example : output(A) and output(B). A failure may occur after one of these modifications have been made but before all of them are made. Recovery and Atomicity

36. Recovery and Atomicity (Cont.) • To ensure atomicity despite failures, • we first output information describing the modifications to stable storage without modifying the database itself. • We study two approaches: • log-based recovery, and • shadow-paging

37. A log : must be kept on stable storage. <Ti, Start>, and <Ti, Start> < Ti, X, V1, V2 > Logging Method When transaction Tistarts, <Tistart> log record When Tifinishes, <Ticommit> log record Before Tiexecutes write(X), <Ti, X, Vold , Vnew >log record We assume for now that log records are written directly to stable storage Two approaches using logs Deferred database modification Immediate database modification Log-Based Recovery

38. The deferred database modification scheme records all modifications to the log, writes them after commit. Log Scheme Transaction starts by writing <Ti start> record to log. write(X) : <Ti, X, V> Note: old value is not needed for this scheme The write is not performed on X at this time, but is deferred. When Ticommits, <Ticommit> is written to the log Finally, executes the previously deferred writes. Deferred Database Modification

39. Recovering Method During recovery after a crash, a transaction needs to be redone if and only if both <Tistart> and<Ti commit> are there in the log. Redoing a transaction Ti( redoTi) sets the value of all data items updated by the transaction to the new values. Deletes Tisuch that <Ti ,start> exists but <Ti commit> does not. Deferred Database Modification (Cont.)

40. If log on stable storage at time of crash is as in case: (a) No redo actions need to be taken (b) redo(T0) must be performed since <T0 commit> is present (c) redo(T0) must be performed followed by redo(T1) since <T0 commit> and <Ti commit> are present Deferred Database Modification : Example T0: read (A) T1 : read (C)A: = A - 50C:= C- 100 write (A) write (C) read (B) B:= B + 50write (B)

41. Immediate database modification scheme Database updates of an uncommitted transaction For undoing : both old value and new value Recovery procedure has two operations undo(Ti) : restores the value of all data items updated by Ti redo(Ti) : sets the value of all data items updated by Ti When recovering after failure: Undo if the log <Ti start>, but not <Ticommit>. Redo if the log both the record <Tistart> and <Ti commit>. Immediate Database Modification

42. Recovery actions in each case above are: (a) undo (T0): B is restored to 2000 and A to 1000. (b) undo (T1) and redo (T0): C is restored to 700, and then A and B are set to 950 and 2050 respectively. (c) redo (T0) and redo (T1): A and B are set to 950 and 2050 respectively. Then C is set to 600 Immediate Database Modification : Example

43. Idempotent Operation • Result (Op(x)) = Result (Op(Op(x)) • Example • Increment(x); : Not Idempotent • x=a; write(x); : Idempotent • Operations in Log Record • Must be Idempotent, otherwise • Multple Executions (for redo) may cause incorrect results

44. Problems in recovery procedure by Log record scheme : searching the entire log records : time-consuming Discard unnecessary redo transactions already executed. Checkpoint Method Marking Checkpoint Recovery from Checkpoint Marking Checkpoint Output all log records currently residing in main memory onto stable storage. Output all modified buffer blocks to the disk. Write a log record < checkpoint> onto stable storage. Checkpoints

45. In case of failure T1 can be ignored T2 and T3 redone. T4 undone Tf Tc T1 T2 T3 T4 system failure checkpoint Checkpoints (Cont.)

46. Mechanism maintain two page tables the current page table, and the shadow page table shadow page table state of the database before transaction execution Shadow page table is never modified during execution To start with, both the page tables are identical. Whenever any page is about to be written for the first time A copy of this page is made onto an unused page. The current page table is then made to point to the copy The update is performed on the copy Shadow Paging

47. Shadow Page : Example Old State New State