CS4432: Database Systems II
Database Consistency and
Violations?
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Transactions, etc.
• Crash recovery
Chapter 17
• Concurrency control
Chapter 18
• Transaction processing
Chapter 19
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Integrity or correctness of data ?
• We would like data in our database to be
“accurate” ( “correct” ) at all times.
EMP
Name
Age
White
52
Green 3421
Gray
1
• How DBMS decides if data is consistent?
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Integrity or consistency constraints
• Utilize predicates data must satisfy
• Examples:
-
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x is key of relation R
x  y holds in R
Domain(x) = {Red, Blue, Green}
no employee should make more than
twice the average salary
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Definitions:
• Consistent state: satisfies all constraints
• Consistent DB: DB in consistent state
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Such constraints may
not capture “full correctness”
Example 1 : Transaction constraints
• When salary is updated,
new salary > old salary
• When account record is deleted,
balance = 0
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Constraints (as we use here) may
not capture “full correctness”
Example 2
Database should reflect
real world
Reality
DB
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in any case, continue with constraints ...
Observation: DB cannot be consistent always
Example:
Constraint : a1 + a2 +…. an = TOT
Action:
Deposit $100 in a2:
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a2  a2 + 100
TOT  TOT + 100
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Example: a1 + a2 +…. an = TOT (constraint)
Deposit $100 in a2: a2  a2 + 100
TOT  TOT + 100
a2
.
.
50
.
.
150
.
.
150
TOT
.
.
1000
.
.
1000
.
.
1100
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Transaction: a collection of actions
that preserve consistency
Consistent DB
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T
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Consistent DB’
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Big assumption:
If T starts with consistent state
AND
T executes in isolation
 T leaves consistent state
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Correctness
(informally)
• If we stop running transaction(s),
DB left consistent
• Each transaction sees a consistent DB
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How can constraints be violated?
• Transaction bug
• DBMS bug
• Hardware failure
e.g., disk crash alters balance of account
• Data sharing
e.g.: T1: give 10% raise to programmers
T2: change programmers
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 systems analysts
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Will not consider:
• How to write correct transactions
• How to write correct DBMS system
• Constraint checking & repair
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How can we prevent/fix violations?
• Chapter 17: due to failures only
• Chapter 18: due to data sharing only
• Chapter 19: due to failures and sharing
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Chapter 17: Recovery
• First :
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Failure Model
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Events
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Desired
Undesired
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Expected
Unexpected
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Our failure model
processor
CPU
memory
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D
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Desired events: see product manuals….
Undesired expected events:
System crash
- memory lost
- cpu halts, resets
that’s it!!
Undesired Unexpected:
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Everything else!
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Undesired Unexpected:
Everything else!
Examples:
• Disk data is lost
• Memory lost without CPU halt
• CPU implodes wiping out universe….
• You name it …
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Operations re
Storage Hierarchy:
x
Memory
x
Disk
• Input (x): block containing x  memory
• Output (x): block containing x  disk
• Read (x,t): do input(x) if necessary
t  value of x in block
• Write (x,t): do input(x) if necessary
value of x in block  t
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Key problem : Unfinished transaction
Example:
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Constraint: A=B
T1: A  A  2
B  B2
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T1: Read (A,t); t  t2
Write (A,t);
Read (B,t); t  t2
Write (B,t);
Output-to-Disk (A);
Output-to-Disk (B);failure!
A: 8 16
B: 8 16
A: 8 16
B: 8
memory
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• Need atomicity:
– execute all actions of a
transaction or none at all
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One solution: undo logging
(immediate
modification)
A la Hansel and Gretel recording their
navigation through forest via bread
crumbs …
Must have durable undo logging !!!
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Undo logging
(Immediate modification)
T1: Read (A,t); t  t2
Write (A,t);
Read (B,t); t  t2
Write (B,t);
Output-to-disk (A);
Output-to-disk (B);
A:8 16
B:8 16
A:8 16
B:8 16
disk
memory
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A=B
<T1, start>
<T1, A, 8>
<T1, B, 8>
<T1, commit>
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One “complication” : First disk, then log
• Log is first written in memory
• Not written to disk on every action
memory
A: 8 16
B: 8 16
Log:
<T1,start>
<T1, A, 8>
<T1, B, 8>
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A: 8 16
B: 8
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DB
BAD STATE
#1
Log
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One “complication” : first log, then disk.
• Log is first written in memory
• Not written to disk on every action
A: 8 16
B: 8 16
Log:
<T1,start>
<T1, A, 8>
<T1, B, 8>
<T1, commit>
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A: 8 16
B: 8
DB
Log
BAD STATE
#2
...
memory
<T1, B, 8>
<T1, commit>
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Undo logging rules
(1) For every action generate undo log record
(containing old value)
(2) Before x is modified on disk,
log records pertaining to x must be
on disk (write ahead logging)
(3) Before commit is written to log on disk,
all writes of transaction must be
reflected on disk
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Recovery rules:
Undo logging
(1) Let S = set of transactions with
<Ti, start> in log, but no
<Ti, commit> (or <Ti, abort>) record in log
(2) For each <Ti, X, v> in log,
in reverse order (latest  earliest) do:
- write old value from log back to disk:
- if Ti  S then - write (X, v)
- output (X)
(3) For each Ti  S do
- write <Ti, abort> to log
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What if failure during recovery?
No problem!  Undo idempotent
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To discuss next :
• Redo logging
• Undo/redo logging, why both?
• Checkpoints
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Redo logging (deferred modification)
T1: Read(A,t); t t2; write (A,t);
Read(B,t); t t2; write (B,t);
Output(A); Output(B)
A: 8 16
B: 8 16
memory
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A: 8 16
B: 8
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<T1, start>
<T1, A, 16>
<T1, B, 16>
<T1, commit>
LOG
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Redo logging rules
(1) For every action, generate redo log
record (containing new value)
(2) Before X is modified on disk (DB),
all log records for transaction that
modified X (including commit) must
be on disk
(3) Flush log at commit
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Recovery rules:
Redo logging
(1) Let S = set of transactions with
<Ti, commit> in log
(2) For each <Ti, X, v> in log, in forward
order (earliest  latest) do:
- if Ti  S then Write(X, v)
Output(X)
optional
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Recovery is very, very
SLOW !
Redo log:
...
First
Record
(1 year ago)
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...
...
T1 wrote A,B
Committed a year ago
--> STILL, Need to redo after crash!!
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Last
Crash
Record
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Solution: Checkpoint
(simple version)
Periodically:
(1) Do not accept new transactions
(2) Wait until all transactions finish
(3) Flush all log records to disk (log)
(4) Flush all buffers to disk (DB) (do not discard buffers)
(5) Write “checkpoint” record on disk (log)
(6) Resume transaction processing
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Example: what to do at recovery?
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...
<T3,C,21>
...
<T2,commit>
...
<T2,B,17>
...
Checkpoint
...
<T1,commit>
...
<T1,A,16>
Redo log (disk):
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Key drawbacks:
• Undo logging: Too many disk IOs
• Redo logging: need to keep all modified
blocks in memory
until commit
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Solution: undo/redo logging!
Combine Undo/Redo Logging, namely:
Update  <Ti, Xid, New X val, Old X val>
page X
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Rules
• Page X can be flushed before or
after Ti commit
• Log record flushed before
corresponding updated page (WAL)
• Flush at commit (log only)
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Non-quiescent checkpoint
L
O
G
...
end
ckpt
...
...
...
Start-ckpt
active TR:
Ti,T2,...
for
undo
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dirty buffer
pool pages
flushed
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Examples what to do at recovery time?
no T1 commit
L
O
G
...
T1,a
 Undo T1
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Ckpt
T1
...
Ckpt
end
...
T 1b
(undo a,b)
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Example
L
O
G
ckpt-s
T1
T1
ckptT1
T1
...
... T1 ...
...
...
...
...
a
b
end
c
cmt
 Redo T1: (redo b,c)
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Recovery process:
• Backwards pass
(end of log  latest checkpoint start)
– construct set S of committed transactions
– undo actions of transactions not in S
• Undo pending transactions
– follow undo chains for transactions in
(checkpoint active list) - S
• Forward pass
(latest checkpoint start  end of log)
– redo actions of S transactions
start
checkpoint
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forward pass
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Summary
• Consistency of data
• One source of problems: failures
- Logging
- Redundancy
• Another source of problems:
Data Sharing..... next
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