Transaction Management Overview

1. Transaction Management Overview Chapter 18

2. Transactions • Concurrent execution of user programs is essential for good DBMS performance. • Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently. • A user’s program may carry out many operations on the data retrieved from the database, but the DBMS is only concerned about what data is read/written from/to the database. • A transactionis the DBMS’s abstract view of a user program: a sequence of reads and writes.

3. Concurrency in a DBMS • Users submit transactions, and can think of each transaction as executing by itself. • Concurrency is achieved by the DBMS, which interleaves actions (reads/writes of DB objects) of various transactions. • Each transaction must leave the database in a consistent state if the DB is consistent when the transaction begins. • DBMS will enforce some ICs, depending on the ICs declared in CREATE TABLE statements. • Beyond this, the DBMS does not really understand the semantics of the data. (e.g., it does not understand how the interest on a bank account is computed). • Issues:Effect of interleaving transactions, and crashes.

4. Atomicity of Transactions • A transaction mightcommitafter completing all its actions, or it could abort(or be aborted by the DBMS) after executing some actions. • A very important property guaranteed by the DBMS for all transactions is that they are atomic.That is, a user can think of a Xact as always executing all its actions in one step, or not executing any actions at all. • DBMS logs all actions so that it can undothe actions of aborted transactions.

5. Example • Consider two transactions (Xacts): T1: BEGIN A=A+100, B=B-100 END T2: BEGIN A=1.06*A, B=1.06*B END • Intuitively, the first transaction is transferring $100 from B’s account to A’s account. The second is crediting both accounts with a 6% interest payment. • There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted together. However, the net effect must be equivalent to these two transactions running serially in some order.

6. Example (Contd.) • Consider a possible interleaving (schedule): T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B • This is OK. But what about: T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B • The DBMS’s view of the second schedule: T1: R(A), W(A), R(B), W(B) T2: R(A), W(A), R(B), W(B)

7. Scheduling Transactions • Serial schedule: Schedule that does not interleave the actions of different transactions. • Equivalent schedules:For any database state, the effect (on the set of objects in the database) of executing the first schedule is identical to the effect of executing the second schedule. • Serializable schedule: A schedule that is equivalent to some serial execution of the transactions. (Note: If each transaction preserves consistency, every serializable schedule preserves consistency. )

8. Anomalies with Interleaved Execution • Reading Uncommitted Data (WR Conflicts, “dirty reads”): • Unrepeatable Reads (RW Conflicts): T1: R(A), W(A), R(B), W(B), Abort T2: R(A), W(A), C T1: R(A), R(A), W(A), C T2: R(A), W(A), C

9. Anomalies (Continued) • Overwriting Uncommitted Data (WW Conflicts): T1: W(A), W(B), C T2: W(A), W(B), C

10. Lock-Based Concurrency Control • Strict Two-phase Locking (Strict 2PL) Protocol: • Each Xact must obtain a S (shared) lock on object before reading, and an X (exclusive) lock on object before writing. • All locks held by a transaction are released when the transaction completes • If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object. • Strict 2PL allows only serializable schedules.

11. Aborting a Transaction • If a transaction Ti is aborted, all its actions have to be undone. Not only that, if Tj reads an object last written by Ti, Tj must be aborted as well! • Most systems avoid such cascading abortsby releasing a transaction’s locks only at commit time. • If Ti writes an object, Tj can read this only after Ti commits. • In order to undo the actions of an aborted transaction, the DBMS maintains a log in which every write is recorded. This mechanism is also used to recover from system crashes: all active Xacts at the time of the crash are aborted when the system comes back up.

12. The Log • The following actions are recorded in the log: • Ti writes an object: the old value and the new value. • Log record must go to diskbeforethe changed page! • Ti commits/aborts: a log record indicating this action. • Log records are chained together by Xact id, so it’s easy to undo a specific Xact. • Log is often duplexed and archived on stable storage. • All log related activities (and in fact, all CC related activities such as lock/unlock, dealing with deadlocks etc.) are handled transparently by the DBMS.

13. Recovering From a Crash • There are 3 phases in the Aries recovery algorithm: • Analysis: Scan the log forward (from the most recent checkpoint) to identify all Xacts that were active, and all dirty pages in the buffer pool at the time of the crash. • Redo: Redoes all updates to dirty pages in the buffer pool, as needed, to ensure that all logged updates are in fact carried out and written to disk. • Undo: The writes of all Xacts that were active at the crash are undone (by restoring the before value of the update, which is in the log record for the update), working backwards in the log. (Some care must be taken to handle the case of a crash occurring during the recovery process!)

14. Summary • Concurrency control and recovery are among the most important functions provided by a DBMS. • Users need not worry about concurrency. • System automatically inserts lock/unlock requests and schedules actions of different Xacts in such a way as to ensure that the resulting execution is equivalent to executing the Xacts one after the other in some order. • Write-ahead logging (WAL) is used to undo the actions of aborted transactions and to restore the system to a consistent state after a crash. • Consistent state: Only the effects of commited Xacts seen.

15. Concurrency Control Chapter 19

16. Conflict Serializable Schedules • Two schedules are conflict equivalent if: • Involve the same actions of the same transactions • Every pair of conflicting actions is ordered the same way • Schedule S is conflict serializable if S is conflict equivalent to some serial schedule

17. Example • A schedule that is not conflict serializable: • The cycle in the graph reveals the problem. The output of T1 depends on T2, and vice-versa. T1: R(A), W(A), R(B), W(B) T2: R(A), W(A), R(B), W(B) A T1 T2 Dependency graph B

18. Dependency Graph • Dependency graph: One node per Xact; edge from Ti to Tj if Tj reads/writes an object last written by Ti. • Theorem: Schedule is conflict serializable if and only if its dependency graph is acyclic

19. Review: Strict 2PL • Strict Two-phase Locking (Strict 2PL) Protocol: • Each Xact must obtain a S (shared) lock on object before reading, and an X (exclusive) lock on object before writing. • All locks held by a transaction are released when the transaction completes • If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object. • Strict 2PL allows only schedules whose precedence graph is acyclic

20. Two-Phase Locking (2PL) • Two-Phase Locking Protocol • Each Xact must obtain a S (shared) lock on object before reading, and an X (exclusive) lock on object before writing. • A transaction can not request additional locks once it releases any locks. • If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.

21. View Serializability • Schedules S1 and S2 are view equivalent if: • If Ti reads initial value of A in S1, then Ti also reads initial value of A in S2 • If Ti reads value of A written by Tj in S1, then Ti also reads value of A written by Tj in S2 • If Ti writes final value of A in S1, then Ti also writes final value of A in S2 T1: R(A) W(A) T2: W(A) T3: W(A) T1: R(A),W(A) T2: W(A) T3: W(A)

22. Crash Recovery Chapter 20 If you are going to be in the logging business, one of the things that you have to do is to learn about heavy equipment. Robert VanNatta, Logging History of Columbia County

23. Review: The ACID properties • Atomicity: All actions in the Xact happen, or none happen. • Consistency: If each Xact is consistent, and the DB starts consistent, it ends up consistent. • Isolation: Execution of one Xact is isolated from that of other Xacts. • D urability: If a Xact commits, its effects persist. • The Recovery Manager guarantees Atomicity & Durability.

24. Motivation • Atomicity: • Transactions may abort (“Rollback”). • Durability: • What if DBMS stops running? (Causes?) • Desired Behavior after system restarts: • T1, T2 & T3 should be durable. • T4 & T5should be aborted (effects not seen). crash! T1 T2 T3 T4 T5

25. Assumptions • Concurrency control is in effect. • Strict 2PL, in particular. • Updates are happening “in place”. • i.e. data is overwritten on (deleted from) the disk. • A simple scheme to guarantee Atomicity & Durability?

26. Handling the Buffer Pool • Force every write to disk? • Poor response time. • But provides durability. • Steal buffer-pool frames from uncommited Xacts? • If not, poor throughput. • If so, how can we ensure atomicity? No Steal Steal Force Trivial Desired No Force

27. More on Steal and Force • STEAL (why enforcing Atomicity is hard) • To steal frame F: Current page in F (say P) is written to disk; some Xact holds lock on P. • What if the Xact with the lock on P aborts? • Must remember the old value of P at steal time (to support UNDOing the write to page P). • NO FORCE(why enforcing Durability is hard) • What if system crashes before a modified page is written to disk? • Write as little as possible, in a convenient place, at commit time,to support REDOing modifications.

28. Basic Idea: Logging • Record REDO and UNDO information, for every update, in a log. • Sequential writes to log (put it on a separate disk). • Minimal info (diff) written to log, so multiple updates fit in a single log page. • Log: An ordered list of REDO/UNDO actions • Log record contains: <XID, pageID, offset, length, old data, new data> • and additional control info (which we’ll see soon).

29. Write-Ahead Logging (WAL) • The Write-Ahead Logging Protocol: • Must force the log record for an update before the corresponding data page gets to disk. • Must write all log records for a Xact beforecommit. • #1 guarantees Atomicity. • #2 guarantees Durability. • Exactly how is logging (and recovery!) done? • We’ll study the ARIES algorithms.

30. DB RAM LSNs pageLSNs flushedLSN pageLSN WAL & the Log • Each log record has a unique Log Sequence Number (LSN). • LSNs always increasing. • Each data pagecontains a pageLSN. • The LSN of the most recent log record for an update to that page. • System keeps track of flushedLSN. • The max LSN flushed so far. • WAL:Before a page is written, • pageLSN £ flushedLSN Log records flushed to disk “Log tail” in RAM

31. prevLSN XID type pageID length offset before-image after-image Log Records LogRecord fields: Possible log record types: • Update • Commit • Abort • End (signifies end of commit or abort) • Compensation Log Records (CLRs) • for UNDO actions update records only

32. Other Log-Related State • Transaction Table: • One entry per active Xact. • Contains XID, status (running/commited/aborted), and lastLSN. • Dirty Page Table: • One entry per dirty page in buffer pool. • Contains recLSN -- the LSN of the log record which firstcaused the page to be dirty.

33. Normal Execution of an Xact • Series of reads & writes, followed by commit or abort. • We will assume that write is atomic on disk. • In practice, additional details to deal with non-atomic writes. • Strict 2PL. • STEAL, NO-FORCE buffer management, with Write-Ahead Logging.

34. Checkpointing • Periodically, the DBMS creates a checkpoint, in order to minimize the time taken to recover in the event of a system crash. Write to log: • begin_checkpoint record: Indicates when chkpt began. • end_checkpoint record: Contains current Xact table and dirty page table. This is a `fuzzy checkpoint’: • Other Xacts continue to run; so these tables accurate only as of the time of the begin_checkpoint record. • No attempt to force dirty pages to disk; effectiveness of checkpoint limited by oldest unwritten change to a dirty page. (So it’s a good idea to periodically flush dirty pages to disk!) • Store LSN of chkpt record in a safe place (master record).

35. prevLSN XID type pageID length offset before-image after-image The Big Picture: What’s Stored Where LOG RAM DB LogRecords Xact Table lastLSN status Dirty Page Table recLSN flushedLSN Data pages each with a pageLSN master record

36. Simple Transaction Abort • For now, consider an explicit abort of a Xact. • No crash involved. • We want to “play back” the log in reverse order, UNDOing updates. • Get lastLSN of Xact from Xact table. • Can follow chain of log records backward via the prevLSN field. • Before starting UNDO, write an Abort log record. • For recovering from crash during UNDO!

37. Abort, cont. • To perform UNDO, must have a lock on data! • No problem! • Before restoring old value of a page, write a CLR: • You continue logging while you UNDO!! • CLR has one extra field: undonextLSN • Points to the next LSN to undo (i.e. the prevLSN of the record we’re currently undoing). • CLRs never Undone (but they might be Redone when repeating history: guarantees Atomicity!) • At end of UNDO, write an “end” log record.

38. Transaction Commit • Write commit record to log. • All log records up to Xact’s lastLSN are flushed. • Guarantees that flushedLSN ³ lastLSN. • Note that log flushes are sequential, synchronous writes to disk. • Many log records per log page. • Commit() returns. • Write end record to log.

39. Crash Recovery: Big Picture Oldest log rec. of Xact active at crash • Start from a checkpoint (found via master record). • Three phases. Need to: • Figure out which Xacts committed since checkpoint, which failed (Analysis). • REDOall actions. • (repeat history) • UNDO effects of failed Xacts. Smallest recLSN in dirty page table after Analysis Last chkpt CRASH A R U

40. Recovery: The Analysis Phase • Reconstruct state at checkpoint. • via end_checkpoint record. • Scan log forward from checkpoint. • End record: Remove Xact from Xact table. • Other records: Add Xact to Xact table, set lastLSN=LSN, change Xact status on commit. • Update record: If P not in Dirty Page Table, • Add P to D.P.T., set its recLSN=LSN.

41. Recovery: The REDO Phase • We repeat History to reconstruct state at crash: • Reapply allupdates (even of aborted Xacts!), redo CLRs. • Scan forward from log rec containing smallest recLSN in D.P.T. For each CLR or update log rec LSN, REDO the action unless: • Affected page is not in the Dirty Page Table, or • Affected page is in D.P.T., but has recLSN > LSN, or • pageLSN (in DB) ³ LSN. • To REDO an action: • Reapply logged action. • Set pageLSN to LSN. No additional logging!

42. Recovery: The UNDO Phase ToUndo={ l | l a lastLSN of a “loser” Xact} Repeat: • Choose largest LSN among ToUndo. • If this LSN is a CLR and undonextLSN==NULL • Write an End record for this Xact. • If this LSN is a CLR, and undonextLSN != NULL • Add undonextLSN to ToUndo • Else this LSN is an update. Undo the update, write a CLR, add prevLSN to ToUndo. Until ToUndo is empty.

43. RAM Example of Recovery LSN LOG 00 05 10 20 30 40 45 50 60 begin_checkpoint end_checkpoint update: T1 writes P5 update T2 writes P3 T1 abort CLR: Undo T1 LSN 10 T1 End update: T3 writes P1 update: T2 writes P5 CRASH, RESTART prevLSNs Xact Table lastLSN status Dirty Page Table recLSN flushedLSN ToUndo

44. RAM Example: Crash During Restart! LSN LOG 00,05 10 20 30 40,45 50 60 70 80,85 90 begin_checkpoint, end_checkpoint update: T1 writes P5 update T2 writes P3 T1 abort CLR: Undo T1 LSN 10, T1 End update: T3 writes P1 update: T2 writes P5 CRASH, RESTART CLR: Undo T2 LSN 60 CLR: Undo T3 LSN 50, T3 end CRASH, RESTART CLR: Undo T2 LSN 20, T2 end undonextLSN Xact Table lastLSN status Dirty Page Table recLSN flushedLSN ToUndo

45. Additional Crash Issues • What happens if system crashes during Analysis? During REDO? • How do you limit the amount of work in REDO? • Flush asynchronously in the background. • Watch “hot spots”! • How do you limit the amount of work in UNDO? • Avoid long-running Xacts.

46. Summary of Logging/Recovery • Recovery Manager guarantees Atomicity & Durability. • Use WAL to allow STEAL/NO-FORCE w/o sacrificing correctness. • LSNs identify log records; linked into backwards chains per transaction (via prevLSN). • pageLSN allows comparison of data page and log records.

47. Summary, Cont. • Checkpointing: A quick way to limit the amount of log to scan on recovery. • Recovery works in 3 phases: • Analysis: Forward from checkpoint. • Redo: Forward from oldest recLSN. • Undo: Backward from end to first LSN of oldest Xact alive at crash. • Upon Undo, write CLRs. • Redo “repeats history”: Simplifies the logic!