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 users 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 transaction is the DBMSs 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 might commit after 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 undo the
  actions of aborted transactions.

5
Example

• Consider two transactions (Xacts)

T1 BEGIN AA100, BB-100 END T2 BEGIN
A1.06A, B1.06B END

• Intuitively, the first transaction is
  transferring 100 from Bs account to As
  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 AA100, BB-100 T2
A1.06A, B1.06B

• This is OK. But what about

T1 AA100, BB-100 T2
A1.06A, B1.06B

• The DBMSs 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 aborts by
  releasing a transactions 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 disk before the changed
  page!
• Ti commits/aborts a log record indicating this
  action.
• Log records are chained together by Xact id, so
  its 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

• A tomicity All actions in the Xact happen, or
  none happen.
• C onsistency If each Xact is consistent, and
  the DB starts consistent, it ends up consistent.
• I solation 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 T5 should 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
• ltXID, pageID, offset, length, old data, new datagt
  
• and additional control info (which well 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 before
  commit.
• 1 guarantees Atomicity.
• 2 guarantees Durability.
• Exactly how is logging (and recovery!) done?
• Well study the ARIES algorithms.

30
WAL the Log

• Each log record has a unique Log Sequence Number
  (LSN).
• LSNs always increasing.
• Each data page contains 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
Log Records

• Possible log record types
• Update
• Commit
• Abort
• End (signifies end of commit or abort)
• Compensation Log Records (CLRs)
• for UNDO actions

LogRecord fields
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 first caused 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 its a good
  idea to periodically flush dirty pages to disk!)
• Store LSN of chkpt record in a safe place (master
  record).

35
The Big Picture Whats 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 were 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 Xacts 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).
• REDO all 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
  lastLSNLSN, change Xact status on commit.
• Update record If P not in Dirty Page Table,
• Add P to D.P.T., set its recLSNLSN.

41
Recovery The REDO Phase

• We repeat History to reconstruct state at crash
• Reapply all updates (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 gt 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 undonextLSNNULL
• 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
Example of Recovery
LSN LOG
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
00 05 10 20 30 40
45 50 60
prevLSNs
Xact Table lastLSN status Dirty Page
Table recLSN flushedLSN
ToUndo
44
Example Crash During Restart!
LSN LOG
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
00,05 10 20 30 40,45 50
60 70 80,85 90
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!