06 07 lock

6-7: 1
Gray& Reuter: Locking
Concurrency Control
Jim GrayJim Gray
Microsoft, Gray @ Microsoft.comMicrosoft, Gray @ Microsoft.com
Andreas ReuterAndreas Reuter
International University, Andreas.Reuter@i-u.deInternational University, Andreas.Reuter@i-u.de
9:00
11:00
1:30
3:30
7:00
Overview
Faults
Tolerance
T Models
Party
TP mons
Lock Theory
Lock Techniq
Queues
Workflow
Log
ResMgr
CICS & Inet
Adv TM
Cyberbrick
Files &Buffers
COM+
Corba
Replication
Party
B-tree
Access Paths
Groupware
Benchmark
Mon Tue Wed Thur Fri

6-7: 2
Concurrency Control:
Outline
• Why lock (isolation)Why lock (isolation)
• When to lock (2øWhen to lock (2ø locking, 1°, 2°,3° isolationlocking, 1°, 2°,3° isolation
• What to lock (granularity)What to lock (granularity)
• How to lockHow to lock
• Exotics (optimistic, field calls, escrow)Exotics (optimistic, field calls, escrow)
• DeadlockDeadlock
• PerformancePerformance

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Why Lock?
• Need isolation (the "I" of ACID):Need isolation (the "I" of ACID):
• Give each transaction the illusion thatGive each transaction the illusion that
there are no concurrent updatesthere are no concurrent updates
• Hide concurrency anomalies.Hide concurrency anomalies.
• Do itDo it automaticallyautomatically
– (system does not know transaction semantics)(system does not know transaction semantics)
• Goal:Goal:
– Although there is concurrency in systemAlthough there is concurrency in system
execution is equivalent to some serial executionexecution is equivalent to some serial execution
of the systemof the system
– Not deterministic outcome, just a consistentNot deterministic outcome, just a consistent
transformationtransformation

6-7: 4
The Essentials
• TransactionsTransactions ConflictConflict if Reads And Writes overlapif Reads And Writes overlap
• More formally:More formally:
Transaction T hasTransaction T has Read Set: R(T)Read Set: R(T)
Write Set: W(T)Write Set: W(T)
• T1 and T2 conflict IFFT1 and T2 conflict IFF
W(T2) & (R(T1) U W(T1))W(T2) & (R(T1) U W(T1)) ≠≠ ØØ
OrOr W(T1) & (R(T2) U W(T2))W(T1) & (R(T2) U W(T2)) ≠≠ ØØ
• If they conflict, delay one until the other finishesIf they conflict, delay one until the other finishes
OK: DISJOINT RANGE AND DOMAIN
BAD: T1 READS OUTPUTS OF T2

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Laws Of Concurrency Control
• First Law of Concurrency ControlFirst Law of Concurrency Control
Concurrent execution should not causeConcurrent execution should not cause
application programs to malfunction.application programs to malfunction.
• Second Law of Concurrency ControlSecond Law of Concurrency Control
Concurrent execution should not have lowerConcurrent execution should not have lower
throughput or much higher response times thanthroughput or much higher response times than
serial execution.serial execution.

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Concurrency Control: Outline

6-7: 7
Formal Model: Transactions and
Serial(izble) Histories
• StateState is a set of name value pairs: DB = {<e,v>}is a set of name value pairs: DB = {<e,v>}
• ActionsActions are defined on state:are defined on state:
<Ti, read, e> means Ti reads value of entity e<Ti, read, e> means Ti reads value of entity e
<Ti, write, e> means Ti writes value of entity e<Ti, write, e> means Ti writes value of entity e
• EachEach TransactionTransaction is a sequence of actions:is a sequence of actions:
Ti = < <Ti, a, e> | i = 1,...,ni>Ti = < <Ti, a, e> | i = 1,...,ni>
• Want to “run” a set of transactions: T = {Ti | i= 1,...,n}Want to “run” a set of transactions: T = {Ti | i= 1,...,n}
• AA HistoryHistory is any sequence S such thatis any sequence S such that
each and every Ti is a subsequence of Seach and every Ti is a subsequence of S
• A history isA history is SerialSerial if it is of the form:if it is of the form:
Ti,Tj,.....,Tz (i.e. one transaction at a time).Ti,Tj,.....,Tz (i.e. one transaction at a time).
• A history isA history is serializableserializable ((isolatedisolated)) if it is equivalent to aif it is equivalent to a
serial history.serial history.

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Formal Mode: Execution History
Equivalence
• Define the following permutation subgroup:Define the following permutation subgroup:
<Ti READ ei> commutes with <Tj READ ej> (for all i, j)<Ti READ ei> commutes with <Tj READ ej> (for all i, j)
<Ti WRITE ei> commutes with < Tj {READ|WRITE} ej><Ti WRITE ei> commutes with < Tj {READ|WRITE} ej>
(iff i(iff i ≠≠ j and eij and ei ≠≠ ej)ej)
• Si isSi is EquivalentEquivalent to Sj if it can be permuted to Sjto Sj if it can be permuted to Sj
• Alternative DefinitionAlternative Definition (inputs and outputs):(inputs and outputs):
• Define theDefine the DependencyDependency set of historyset of history S D(S):S D(S):
{<Ti,e,Tj> | <Ti,ai,e> ,...,<Tj,aj,e> is a subsequence of S{<Ti,e,Tj> | <Ti,ai,e> ,...,<Tj,aj,e> is a subsequence of S
and ai = write or aj = write }and ai = write or aj = write }
(note: some initial and terminal dependencies are also needed)(note: some initial and terminal dependencies are also needed)
• Two Schedules are equivalentTwo Schedules are equivalent iff they have sameiff they have same
dependenciesdependencies

6-7: 9
<e,1>
T1
<e,2>
T2
W W
<e,3>
T1
<e,1>
T2
R W
<e,2><e,1>
T1
<e,2>
T2
R
<e,1>
W
<e,2>
Transaction Dependency Relations
• Shows data flow among transactionsShows data flow among transactions
T1 READT1 READ 〈〈e,1e,1〉〉 T1 WRITET1 WRITE 〈〈e,2e,2〉〉 T1 WRITET1 WRITE 〈〈e,2e,2〉〉
T2T2 WRITEWRITE 〈〈e,2e,2〉〉 T2 READT2 READ 〈〈e,2e,2〉〉 T2 WRITET2 WRITE 〈〈e,3e,3〉〉

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The Three Bad
Transaction Dependencies
Locks are often used to prevent these dependencies.
T1
<e,1>
<e,2>
T2
<e,1><e,1>
<e,3><e,2>
Lost Update
T2 READ 〈e,1〉
T1 WRITE 〈e,2〉
T2 WRITE 〈e,3〉
T1
<e,2>
T2
<e,2>
<e,1>
<e,2>
<e,3>
Dirty Read
T2 WRITE 〈e,2〉
T1 READ 〈e,2〉
T2 WRITE 〈e,3〉
T1 T2
<e, 1>
<e,2>
<e,1>
<e,2>
UnRepeatable
Read
T1 READ 〈e,1〉
T2 WRITE 〈e,2〉
T1 READ 〈e,2〉
T2
<e,1> <e,1>
T1
OK

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Dependencies Show Dataflows
Among Transactions
T1
T2
T3
T4
T5
T6
T1
T2
T3
T4
T5
T6
• Two histories are equivalent iff they have the same dependencies
• We want only histories equivalent to a serial history.
• If T2 depends on data from T1, then T2 ran after T1.
• If T4 depends on data from T3, then T4 ran after T3.
• This is a wormhole (in time): T4 ran after T4.
T3-> T4 -> T6 ->T3 ->T4
• Cycles in the dependency graph are bad.

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Locks Cover Actions
Introduce three new actions:Introduce three new actions:
LOCK [READ | WRITE]LOCK [READ | WRITE]
UNLOCKUNLOCK
Lock <Ti, LOCK a, e >Lock <Ti, LOCK a, e > CoversCovers
<Ti, a', e><Ti, a', e>
IfIf
<Ti, a', e> is at or after the lock step<Ti, a', e> is at or after the lock step
ANDAND
No intervening unlockNo intervening unlock
ANDAND
a is WRITE OR a' IS READa is WRITE OR a' IS READ
(write covers write and read)(write covers write and read)
t slock o1
t xlock o2
t read o1
t read o3
t write o1
t write o2
t read o2
t unlock o1
t unlock o2
t unlock o3
Not Covered
Not Covered
Not Covered

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Well Formed and Two-Phased
Transactions
• Transaction T is well formed if:
All actions of T are covered by a lock
Lock Act Unlock
• Transaction T is 2-phase if:
No unlock precedes a lock in T.
(i.e. A T has a LOCK phase and an UNLOCK phase)
GROW Shrink
• Basic rules:Basic rules:
– Lock everything you read/writeLock everything you read/write
– Hold locks to end-of-Hold locks to end-of-
transactiontransaction

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Lock Commutativity
<Ti ,LOCK, ei><Ti ,LOCK, ei> commutes withcommutes with <Tj ,LOCK, ej><Tj ,LOCK, ej>
(if i(if i ≠≠ j, and (eij, and (ei ≠≠ ej))ej))
<Ti ,LOCK READ, e> commutes with <Tj ,LOCK READ, e><Ti ,LOCK READ, e> commutes with <Tj ,LOCK READ, e>
(if i(if i ≠≠ j)j)
C O M P A T IB IL IT Y M O D E O F L O C K
SH A R E
C O M PA TIB LE
C O N FLIC T
E X C LU SIV E
C O N FLIC T
C O N FLIC T
SH A R E
E X C LU SIV E
M O D E O F
R E Q U E ST

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LOCKS define LEGAL HISTORIES
History isHistory is legallegal if:if:
Don't grant incompatible locks to two at once.Don't grant incompatible locks to two at once.
If T1 covers e with a WRITE lock,If T1 covers e with a WRITE lock,
No T2 covers e at that point in the historyNo T2 covers e at that point in the history (if T1(if T1 ≠≠
T2).T2). Legal & Serial
T1 SLOCK A
T1 XLOCK B
T1 READ A
T1 WRITE B
T1 UNLOCK A
T1 UNLOCK B
T2 SLOCK A
T2 READ A
T2 XLOCK B
T2 WRITE B
T2 WRITE B
T2 UNLOCK A
T2 UNLOCK B
T1 Begin
T1 Slock A
T1 Xlock B
T1 Read A
T1 Write B
T1 Commit
T2 Begin
T2 Slock A
T2 Read A
T2 Xlock B
T2 Write B
T2 Rollback
T2 SLOCK A
T1 SLOCK A
T2 READ A
T2 XLOCK B
T2 WRITE B
T2 WRITE B
T2 UNLOCK A
T2 UNLOCK B
T1 XLOCK B
T1 READ A
T1 WRITE B
T1 UNLOCK A
T1 UNLOCK B
T2 Begin
T2 Slock A
T2 Read A
T2 Xlock B
T2 Write B
T2 Rollback
T1 Begin
T1 Slock A
T1 Xlock B
T1 Read A
T1 Write B
T1 Commit
Legal & Not Serial
T1 SLOCK A
T1 XLOCK B
T2 SLOCK A
T2 READ A
T2 XLOCK B
T2 WRITE B
T2 WRITE B
T2 UNLOCK A
T2 UNLOCK B
T1 READ A
T1 WRITE B
T1 UNLOCK A
T1 UNLOCK B
T Begin
T Slock A
T Xlock B
T Read A
T Write B
T Commit
T' Begin
T' Slock A
T' Read A
T' Xlock B
T' Write B
T' Rollback
NotLegal & Not Serial

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SERIALIZABILITY THEOREM
(Wormhole Theorem)
1. If all transactions are well formed and 21. If all transactions are well formed and 2∅∅
then all legal histories are serializable.then all legal histories are serializable.
2. If T1 is not well formed or not 22. If T1 is not well formed or not 2∅∅
then there is a T2 such thatthen there is a T2 such that
T1 and T2 have a legalT1 and T2 have a legal
but not serializable historybut not serializable history
except for trivial cases.except for trivial cases.

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WF & 2∅ => No Wormholes
• Consider first unlock in scheduleConsider first unlock in schedule
<Ti, unlock, e><Ti, unlock, e>
• Claim: Ti is a “first”Claim: Ti is a “first”
– There is no Tj >> Ti for all jThere is no Tj >> Ti for all j ≠≠ II (Tj before Ti)(Tj before Ti)
• Suppose not (Suppose not (suppose Tj >> Tisuppose Tj >> Ti):):
– Then Tj accesses some e2Then Tj accesses some e2
– Then Tj unlocks e2 (Tj is WF)Then Tj unlocks e2 (Tj is WF)
– Then Ti locks e2 (Ti is WF)Then Ti locks e2 (Ti is WF)
– Then Ti reads or writes e2Then Ti reads or writes e2
– So Tj unlock is before Ti unlock (2So Tj unlock is before Ti unlock (2∅∅) =><=) =><=
• Contradiction proves Ti is a first.Contradiction proves Ti is a first.

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Proof of Wormhole Theorem
If no wormhole, then equivalent to serial
Induction:Induction:
If no cycles, then there is a “last” transactionIf no cycles, then there is a “last” transaction
Permute it to end of history (this will preserve dependencies).Permute it to end of history (this will preserve dependencies).
So, equivalent history.So, equivalent history.
By induction remaining history is equivalent to a serial history.By induction remaining history is equivalent to a serial history.
Original T4 Moved T3 Moved T2 Moved = Serial
T1
T2
T3
T4
T1
T1
T1
T2
T2
T2
T2
T3
T3
T3
T3
T4
T4
T4
T4T1
T2
T3
T4
T1
T1
T1
T2
T2
T2
T2
T3
T3
T3
T3
T4
T4
T4
T4
T1
T2
T3
T4
T1
T1
T1
T2
T2
T2
T2
T3
T3
T3
T3
T4
T4
T4
T4
T1
T2
T3
T4
T1
T1
T1
T2
T2
T2
T2
T3
T3
T3
T3
T4
T4
T4
T4

6-7: 19
Proof of serializability theorem
2.1. Not WF = > nonserial
T1 not well formed: <T1, a, e> not covered by a lock.T1 not well formed: <T1, a, e> not covered by a lock.
ConstructConstruct WF & 2WF & 2∅∅ T2 =T2 = <<T2,LOCK WRITE,e><<T2,LOCK WRITE,e>
,<T2, WRITE,e>,<T2, WRITE,e>
,<T2,UNLOCK,e>>,<T2,UNLOCK,e>>
Now the history H:Now the history H: < ...< ...
,<T2,LOCK WRITE,e>,<T2,LOCK WRITE,e>
,<T1,a, e>,<T1,a, e>
,<T2, WRITE,e>,<T2, WRITE,e>
,<T2,UNLOCK,e>,<T2,UNLOCK,e>
,...>,...>
Is legal, but not equivalent to serialIs legal, but not equivalent to serial
T1 is "after" T2 and also "before" T2.T1 is "after" T2 and also "before" T2.
T1
T2 e
e
e

6-7: 20
Proof of serializability theorem
2.1. Not 2∅ = > nonserial
T1 NOT 2T1 NOT 2∅∅ meansmeans <T1,unlock, e1> ... <T1, LOCK, e2<T1,unlock, e1> ... <T1, LOCK, e2
Construct WF & 2Construct WF & 2∅∅ T2:T2: <<T2,LOCK READ, e1>
,<T2, LOCK READ,e2>
,<T2, UNLOCK, e1>
,<T2,UNLOCK, e2>>
Now the historyNow the history H:H: < ...
,<T1,UNLOCK, e1>
,<T2,LOCK READ, e1>
,<T2, LOCK READ,e2>
,<T2, UNLOCK, e1>
,<T2,UNLOCK, e2>>
,<T1,LOCK, e2
,...>
Is legal, but not equivalent to a serial historyIs legal, but not equivalent to a serial history
T1 is "after" T2 and also "before" T2T1 is "after" T2 and also "before" T2
T2
T1e1
e1
e2
e2

6-7: 21
Restatement of serializability theorem
• Lock everything transaction accessesLock everything transaction accesses
• Do not lock after unlockDo not lock after unlock..
• Backout may have to undo a unlock (Backout may have to undo a unlock (== lock).lock).
• So do not release locks prior to commitSo do not release locks prior to commit øø11
• Keep exclusive locks (write locks) to commitKeep exclusive locks (write locks) to commit øø22

6-7: 22
Serializability Theorems
• Wormhole TheoremWormhole Theorem::
A history is isolated if, and only if, it has no wormholeA history is isolated if, and only if, it has no wormhole
transactions.transactions.
• Locking TheoremLocking Theorem::
If all transactions are well-formed and two-phase, then anyIf all transactions are well-formed and two-phase, then any
legal history will be isolated.legal history will be isolated.
• Locking Theorem (converse)Locking Theorem (converse)::
If a transaction is not well-formed or is not two-phase, thenIf a transaction is not well-formed or is not two-phase, then
it is possible to write another transaction, such that theit is possible to write another transaction, such that the
resulting pair is a wormhole.resulting pair is a wormhole.
• Rollback TheoremRollback Theorem::
An update transaction that does an UNLOCK and then aAn update transaction that does an UNLOCK and then a
ROLLBACK is not two-phase.ROLLBACK is not two-phase.

6-7: 23

6-7: 24
Isolation Levels
= Degrees of { Isolation | Consistency }
00°°:: transaction gets short xlocks for writestransaction gets short xlocks for writes
(well formed writes not 2Ø, no read locks)(well formed writes not 2Ø, no read locks)
11°°:: transaction gets no read lockstransaction gets no read locks
(well formed and(well formed and 22ØØ writes,)writes,)
22°°:: transaction releases read locks right aftertransaction releases read locks right after readread
(well formed with respect to reads(well formed with respect to reads
but notbut not 22ØØ with respect to reads)with respect to reads)
33°°:: well formed and 2Øwell formed and 2Ø
(= Serializable by previous theorems!!)(= Serializable by previous theorems!!)
Transaction backout prohibits 0Transaction backout prohibits 0°°..

6-7: 25
What Do Systems Do?
Most non SQL systems support 2Most non SQL systems support 2°°
Most SQL systems default to 3Most SQL systems default to 3°° and allow forms of 1and allow forms of 1°°,, 22°°
e.g.:e.g.: NonStop SQL:NonStop SQL: 11°° = BROWSE= BROWSE
22°° ~ STABLE READ~ STABLE READ
DB2:DB2: 22°° ~ CURSOR STABILITY~ CURSOR STABILITY
33°° ~ REPEATABLE READ~ REPEATABLE READ
SQL StandardSQL Standard
11°° = READ UNCOMMITTED= READ UNCOMMITTED
22°° = READ COMMITTED= READ COMMITTED
2.992.99°° = REPEATABLE READ= REPEATABLE READ
33°° = SERIALIZABLE= SERIALIZABLE

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Isolation Levels Theorem
If others lock 1° or 2°If others lock 1° or 2°
and I lock 3° then I get 3° (serializable).and I lock 3° then I get 3° (serializable).
Any other trans is before me or after me.Any other trans is before me or after me.
BUTBUT
DB may be corrupted by them.DB may be corrupted by them.

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Comparison of Isolation Levels
Protection
Provided
Lets others run
at higher
isolation
0 and
no lost updates
1+
No dirty reads
2 +
Repeatable
reads
Committed data Writes visible
immediately
Writes visible at
eot
Same Same
Dirty data You don't
overwrite dirty
data
0 and others do
not overwrite
your dirty data
0, 1, and you
don't read dirty
data
0,1,2 and others
don't dirty data
you read
Lock protocol Set short Set long 1 and set short 1 and set long
exclusive locks
on data you
write
exclusive locks
on data you
write
share locks on
data you read
share locks on
data you read
Trans structure Well-formed
Wrt writes
Well-formed wrt
writes
Two-phase wrt
writes
Well-formed
And
Two-phase wrt
writes
Well-formed
and
Two-phase
Concurrency Greatest:
only set short
write locks
Great:
only wait for
write locks
Medium:
hold few read
locks
Lowest:
any data
touched
Locked to eot
Issue Degree 0 Degree 1 Degree 2 Degree 3
Common name Chaos Isolated
Serializable
Repeatable reads
Browse
read uncommited
Cursor stability
read committed
Rollback supported

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Comparison of Isolation Levels
IssueIssue Degree 0Degree 0 Degree 1Degree 1 Degree 2Degree 2 Degree 3Degree 3
OverheadOverhead Least:Least:
short W locksshort W locks
Small:Small:
Only write locksOnly write locks
Medium:Medium:
Set R&WSet R&W
but short Rbut short R
Most:Most:
Set long R&WSet long R&W
RollbackRollback UNDO mayUNDO may
cascadecascade
Cant rollbackCant rollback
Can UndoCan Undo
incompleteincomplete
transactionstransactions
samesame SameSame
System RecoverySystem Recovery Dangerous,Dangerous,
Updates mayUpdates may
be lost andbe lost and
violate 3violate 3°°
Apply log in 1Apply log in 1°°
orderorder
SameSame samesame
DependenciesDependencies NoneNone WW →→ WW WW →→ WW
WW →→ RR
WW →→ WW
WW →→ RR
RR →→ WW

6-7: 29

6-7: 30
The Phantom Detail
• If I try to readIf I try to read hair = "red" and eyes = "blue"hair = "red" and eyes = "blue"
and getand get not foundnot found, what gets locked?, what gets locked?
No records have been accessed so no records get lockedNo records have been accessed so no records get locked
• If I delete a record, what gets locked?(the record is gone)If I delete a record, what gets locked?(the record is gone)
• These are cases ofThese are cases of phantomphantom records.records.
• Predicate locksPredicate locks solve this problem (see below)solve this problem (see below)
• Page LocksPage Locks (done right) can solve this problem(done right) can solve this problem
lock the red hair page and the blue eye page,lock the red hair page and the blue eye page,
prevents others red hair and blue eye inserts & updatesprevents others red hair and blue eye inserts & updates
• High volume TP systems use esoteric locking mechanisms:High volume TP systems use esoteric locking mechanisms:
Key Range LocksKey Range Locks:: to protect b-treesto protect b-trees
Hole LocksHole Locks:: to protect space for uncommitted deletesto protect space for uncommitted deletes

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Predicate Locks
Read and write sets can be defined by predicatesRead and write sets can be defined by predicates
(e.g. Where clauses in SQL statements)(e.g. Where clauses in SQL statements)
When a transaction accesses a set for the first time,When a transaction accesses a set for the first time,
1. Automatically capture the predicate1. Automatically capture the predicate
2. Do set intersection with predicates of others.2. Do set intersection with predicates of others.
3. Delay this transaction if conflict with others.3. Delay this transaction if conflict with others.
Problems with predicate locks:Problems with predicate locks:
1.1. Set intersection = predicate satisfiability is NP completeSet intersection = predicate satisfiability is NP complete
(slow).(slow).
2.2. Hard to capture predicatesHard to capture predicates
3. Pessimistic:3. Pessimistic: Jim locksJim locks eye = blueeye = blue
Andreas locksAndreas locks hair=redhair=red
Predicate says conflict, but DB may not have blue eyed red hairedPredicate says conflict, but DB may not have blue eyed red haired
person.person.

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Precision Locks: Lazy Predicate
Locks
Precision locksPrecision locks solve problems 1 & 3:solve problems 1 & 3:
Check returned records against predicates onCheck returned records against predicates on
each read/writeeach read/write
Example:Example:
Andreas can't insert/read blue eyesAndreas can't insert/read blue eyes
Jim can't insert/read red hair.Jim can't insert/read red hair.
check records as they go bycheck records as they go by

6-7: 33
Granularity Of Locks
An Engineering Solution To Predicate Locks
Can lock whole DB, whole file, or just one key value.
Size of lock is called granule.
DATABASE
FILE-1 FILE-2 FILE-3
KEY-A KEY-A KEY-A
Idea:Idea:
Pick a fixed set of predicatesPick a fixed set of predicates
They form a lattice under and, orThey form a lattice under and, or
This can be represented as a graphThis can be represented as a graph
Lock the nodes in this graphLock the nodes in this graph
Simple example:Simple example:

6-7: 34
Lock Granularity
Batch wants to lock whole DBBatch wants to lock whole DB
Interactive wants to lock recordsInteractive wants to lock records
How can we allow both granularities?How can we allow both granularities?
Intention modeIntention mode locks on coarse granuleslocks on coarse granules
Simple compatibility matrixSimple compatibility matrix
Compatibility Matrix
Mode Intent S hare eX clusive
I + - -
S - + -
X - - -

6-7: 35
Lock Granularity: refined intent modes
Intent mode locks say locks being set at finer granularityIntent mode locks say locks being set at finer granularity
If only reading at finer granularity then I compatible with S.If only reading at finer granularity then I compatible with S.
IntroduceIntroduce IS: intend to set fine S locksIS: intend to set fine S locks
IX: intend to set fine S or X locksIX: intend to set fine S or X locks
SIX: S + IXSIX: S + IX
IS IX S SIX X
IS + + + + -
IX + + - - -
S + - + - -
SIX + - - - -
X - - - - -

6-7: 36
Granularity Example
Notes:Notes:
T3 is waitingT3 is waiting
T2 has all of file 3 locked sharedT2 has all of file 3 locked shared
Most of file 2 locked shared (Fine granularity)Most of file 2 locked shared (Fine granularity)
T1 has record locks in file-1 and file-2T1 has record locks in file-1 and file-2
Rules:Rules:
Lock root to leafLock root to leaf
If set X,S below get IX or IS aboveIf set X,S below get IX or IS above
On a DAG (Directed Acyclic Graph)On a DAG (Directed Acyclic Graph)
GetGet ONEONE IS,IS,...,S path for readsIS,IS,...,S path for reads
GetGet ALLALL IX,IX,...,X paths for a writeIX,IX,...,X paths for a write
DATABASE
FILE-1 FILE-2 FILE-3
KEY-A KEY-A KEY-A
T1:IX, T2:IS T3:S
T1:X T1:S, T2:S
T1:IX T1:IX, T2:IS T2:S
T1:XT2:S
T1:IX T2:IS
T1:IX
T1:X
T3:S
T1:IX
T1:S
T2:IS
T2:S
T2:ST2:ST2:S
T2:S

6-7: 37
Update Mode Locks (minor tangent)
Most common form of deadlockMost common form of deadlock
T1 READ AT1 READ A (lock A shared)(lock A shared)
T2 READ AT2 READ A (lock A shared)(lock A shared)
T1 UPDATE AT1 UPDATE A (lock A exclusive, wait for T2)(lock A exclusive, wait for T2)
T2 UPDATE AT2 UPDATE A (deadlock A exclusive, wait for T1)(deadlock A exclusive, wait for T1)
So introduce update mode lock:So introduce update mode lock:
IS IX S SIX U X
IS + + + + - -
IX + + - - - -
S + - + - - -
SIX + - - - - -
U - - + - - -
X - - - - - -
U compatible with S so updators do not hurt readers.
If certain to update record then get x mode lock right away.

6-7: 38
Escalation
If transaction gets too many locks, system probably guessedIf transaction gets too many locks, system probably guessed
wrong about granularitywrong about granularity
Convert fine grain locks to one coarse oneConvert fine grain locks to one coarse one
Example:Example:
1000 record locks on table t becomes1000 record locks on table t becomes
1 file lock on table t.1 file lock on table t.
In some contexts, DE-Escalation is best:
Get course grained locks.Get course grained locks.
Remember fine grain resource names.Remember fine grain resource names.
On callback:On callback:
request fine-grained locks andrequest fine-grained locks and
de-escalate coarse lockde-escalate coarse lock

6-7: 39
Lock Conversion
If requested lock already held in oneIf requested lock already held in one
mode,mode,
new mode is: max (old, requested)new mode is: max (old, requested)X
SIX U
IX S
IS

6-7: 40
Key Range Locking
(for Phantoms)
Suppose operations are:Suppose operations are:
Read(key)Read(key);; /* return current value/* return current value */*/
Write(key, value)Write(key, value); /* set key's value; /* set key's value */*/
Delete(key)Delete(key);; /* delete key + value/* delete key + value */*/
Read_Next(key)Read_Next(key);; /* returns next key + val/* returns next key + val */*/
Insert between X and Y must test to see thatInsert between X and Y must test to see that
No one else cares that [X,Y] was empty, but isNo one else cares that [X,Y] was empty, but is
now fullnow full
no other concurrent trans did a Read_Next("X");).no other concurrent trans did a Read_Next("X");).

6-7: 41
Key Range Locking (a solution)
Prev-Key Key-Range locking.Prev-Key Key-Range locking.
Fixed rangesFixed ranges [A,B), [B,C),...., [Z,[A,B), [B,C),...., [Z,∞∞))
(this is easy)(this is easy)
Dynamic ranges:Dynamic ranges:
If X, Y, Z are in listIf X, Y, Z are in list
....[X, Y), [Y,Z), [Z,....[X, Y), [Y,Z), [Z,∞∞))
are the lock ranges. List changes as list changes.are the lock ranges. List changes as list changes.
Ranges named by first key in range.Ranges named by first key in range.
Lock a range when operating on the rangeLock a range when operating on the range
Insert and delete Lock 3 ranges [X. Y), [X, Z), [Y, Z)Insert and delete Lock 3 ranges [X. Y), [X, Z), [Y, Z)
DualDual Is next keyIs next key locking.locking.
Best solution is not published.Best solution is not published.

6-7: 42
DAG Locking
In general predicate locks and key-range locks form a DAGIn general predicate locks and key-range locks form a DAG
not just a tree:not just a tree:
a lock can have many parents.a lock can have many parents.
Blue-eye key rangeBlue-eye key range
Blonde-hair key range.Blonde-hair key range.
Hierarchical locks work for this.Hierarchical locks work for this.
Read locks any pathRead locks any path
Writes lock all paths.Writes lock all paths.
Hair Index
Auburn
Black
Blonde
Brunette
Platinum
Red
White
Yellow
Eye Index
Black
Blue
Brown
Green
Gray
Red
Famous People T : IX, T' : IXT : IX T’ : IX
T : X
T' : S
Blonde
Hair
Red Hair
Blue Eyes
Don
Marilyn
Monroe
T : X

6-7: 43
• How to lock

6-7: 44
Basic Synchronization Primitives
(hardware)
boolean CompareAndSwap(long * cell, long old, long new)
{ if ( *cell == old) { *cell = *new; return TRUE:}
{ *old = * cell; return FALSE} }
value = Load Locked(long * cell);
other stuff;
boolean = StoreConditional(*cell, value);
/* store conditional fails if cell has changed */
Can use these operators to implement:
Shared storage managers
Queues
Semaphores (latches)

6-7: 45
Lock Interface (API)
LOCK (name,(name, - name of resource- name of resource
,mode,mode - S, X, SIX, IX, IS, U- S, X, SIX, IX, IS, U
,duration,duration - instant, short, long- instant, short, long
,wait,wait )) - no, timeout,yes- no, timeout,yes
UNLOCK (name(name - name of resource- name of resource
,clear,clear )- decrement count to zero)- decrement count to zero
or not.or not.
Locks must count: if lock twice and unlock once, lock keptLocks must count: if lock twice and unlock once, lock kept
Lock state must be saved (somehow) atLock state must be saved (somehow) at
transaction save points (allow rollback)transaction save points (allow rollback)
commit (allow restart to reacquire)commit (allow restart to reacquire)
generally, save is implicit (recompute them)generally, save is implicit (recompute them)

6-7: 46
LOCK NAME
HASH LINK
SEMAPHORE
MODE
WAITS?
QUEUE
HEADER
FROM
HASH
TABLE
NEXT IN
HASH CHAIN
NEXT IN QUEUE
HEADER
MODE HELD
MODE DESIRED
GRANTED?
DURATION
COUNT
TRANSACTION
GRANTED GROUP
WAITING GROUP
list of locks
of transaction
T (from Trans
control block) next lock of T
Most locks are free most of the timeMost locks are free most of the time
so only allocate space for a lock if busyso only allocate space for a lock if busy
hash table points at lock nameshash table points at lock names
Lock queue:Lock queue:
Notes: this is a very busy one, most queues = 1 holderNotes: this is a very busy one, most queues = 1 holder
transaction lock queue helps at commit (want to free all locks of T)transaction lock queue helps at commit (want to free all locks of T)
semaphores cover hash chain, lock queue (not shown below)semaphores cover hash chain, lock queue (not shown below)

6-7: 47
LOCK Control Flow
Hash Name & Search for NameHash Name & Search for Name
Not Found:Not Found: Allocate & FormatAllocate & Format
Header and BodyHeader and Body
ExitExit
Requestor Already Granted To Requestor?Requestor Already Granted To Requestor?
Yes: Requested Mode Compatible With Other Granted?Yes: Requested Mode Compatible With Other Granted?
Yes:Yes: Grant, Bump Count, ExitGrant, Bump Count, Exit
No:No: Bump Count, Set Desire, WaitBump Count, Set Desire, Wait
No:No:Allocate Queue Element at EndAllocate Queue Element at End
Anyone Waiting?Anyone Waiting?
Yes: Mark Waiting, WaitYes: Mark Waiting, Wait
No: Compatible With Grantees?No: Compatible With Grantees?
Yes: GrantYes: Grant
No: WaitNo: Wait
ExitExit

6-7: 48
UNLOCK Control Flow
Hash Name & Find NameHash Name & Find Name
Find Requestor In QueueFind Requestor In Queue
Decrement CountDecrement Count
If Count > 0 Then Exit -- No ChangeIf Count > 0 Then Exit -- No Change
Dequeue RequestorDequeue Requestor
If Queue Empty ThenIf Queue Empty Then Deallocate HeaderDeallocate Header
ExitExit
For Each Waiting ConversionFor Each Waiting Conversion
If Compatible With Granted GroupIf Compatible With Granted Group
Then Mark Granted & WakeupThen Mark Granted & Wakeup
If No More Conversions Waiting ThenIf No More Conversions Waiting Then
For Each Waiter (in FIFO order)For Each Waiter (in FIFO order)
If Compatible With GrantedIf Compatible With Granted
Then Mark Granted & WakeupThen Mark Granted & Wakeup
Else ExitElse Exit
ExitExit

6-7: 49
• Exotics (optimistic, field calls, escrow)

6-7: 50
Optimistic Locking
Idea: hope no one else changes dataIdea: hope no one else changes data
Timestamp:Timestamp: keep timestamp with each objectkeep timestamp with each object
defer all updatesdefer all updates
at ø1 commit:at ø1 commit: lock objectslock objects
if timestamps original then abortif timestamps original then abort
else release read lockselse release read locks
at ø2 commit: apply deferred updatesat ø2 commit: apply deferred updates
Value:Value: keep original value of each objectkeep original value of each object
at ø1 commit:at ø1 commit: lock objectslock objects
if values original then abortif values original then abort
else release read lockselse release read locks
at ø2 commit: apply deferred updatesat ø2 commit: apply deferred updates

6-7: 51
Optimistic Locking: Field Calls
Field call: if predicate then update
predicates: single variable query
updates: SQL update clause
(single variable update)
Assumption:
if predicate true, transform applies
good for hot spots
original idea in IMS/FP MSDBS.
at call: test predicate
if false give diagnostic
else record call in log
at commit ø1: lock
test predicate
if false then abort (restart)
at commit ø2: apply update
unlock
Examples:Examples:
no predicate, just an update ,just an update ,
no contention:no contention:
updateupdate transactionstransactions
set count := count + 1set count := count + 1
where branch =where branch =
:home_branch;:home_branch;
typical predicate:
updateupdate inventoryinventory
set quantity = quantity -set quantity = quantity -
:delta:delta
where part_no = :partwhere part_no = :part
and quantity > :delta;and quantity > :delta;

6-7: 52
Escrow Locking
Schemes that hold locks at end of Ø1 fail to solve hot spotSchemes that hold locks at end of Ø1 fail to solve hot spot
problem for distributed system since ø1 to Ø2 transitionproblem for distributed system since ø1 to Ø2 transition
may take timemay take time
Idea:Idea: leave value fuzzy,leave value fuzzy,
store minimum and maximum valuesstore minimum and maximum values
Poly-values of (Warren Montgomery's MIT thesis)Poly-values of (Warren Montgomery's MIT thesis)
Escrow locking of (Pat O’Neil)Escrow locking of (Pat O’Neil)
Example: I order 100 widgets:Example: I order 100 widgets:
quantityquantity was:was: [1000,1000][1000,1000]
now is:now is: [900, 1000][900, 1000]
I commitI commit now is:now is: [900, 900][900, 900]
No locks are heldNo locks are held
Works only for commutative opsWorks only for commutative ops

6-7: 53
Versioning vs Locking
(Oracle’s Approach)
Records & Objects have values over time:
R: [T0..T1): V0, [T1…T2) V1, [T2….now) V3.
Value time Ti is transaction commit timestamp.
Writes set conventional locks and transaction sees its own updates
Transaction makes read request at time Tx, return
Value as of that time
Value as of time statement began (Oracle Consistent Read)
Value as of time transaction began (Snapshot Isolation)
(= Oracle Serializable)
There is a whole neat theory here waiting to be worked out:
see “A Critique of SQL Isolation Levels”, SIGMOD 95.

6-7: 54
Tradeoffs
• Deferred updates are confusing for user (application).Deferred updates are confusing for user (application).
• Value is good if object small (record)Value is good if object small (record)
• Timestamp is good if object large (file)Timestamp is good if object large (file)
• Field calls more general than eitherField calls more general than either
• Field calls great for SQL systems (automatic)Field calls great for SQL systems (automatic)
• Field call commutativity assumption is prone to errorField call commutativity assumption is prone to error

6-7: 55
Weird Lock Options
Available To Application
Read past locks:
caller wants to skip locked
items
e.g.,: get next free item in a
queue,
Notify locks:
caller waits for object to change
e.g.: wait for nonempty queue
or trigger on data change
Bounce locks:
caller never waits (timeout = 0)
example: want any free record.
Read thru locks:
wants to see all data,
even uncommitted updates
example: ad hoc query
Adaptive locking:
holder of lock notified that
others wait
holder releases/changes
lock access

6-7: 56
• Deadlock

6-7: 57
Deadlock Detection
Deadlock:Deadlock: a cycle in the wait-for grapha cycle in the wait-for graph
Kinds of waits:Kinds of waits: database locksdatabase locks
terminal/deviceterminal/device
storagestorage
sessionsession
serverserver
Correct detection must get complete graphCorrect detection must get complete graph
Not likely, so always fall back on timeoutNot likely, so always fall back on timeout
Model of deadlock shows:Model of deadlock shows:
waits are rarewaits are rare
deadlocks are raredeadlocks are rare22
(very very rare)(very very rare)
virtually all cycles are length 2virtually all cycles are length 2
so do depth-first search eitherso do depth-first search either as soon as you waitas soon as you wait
OR after a timeout

6-7: 58
How To Find a Deadlock
Call each object manager getting his part ofCall each object manager getting his part of
wait-for graphwait-for graph
Do depth-first search (transitive closure) ofDo depth-first search (transitive closure) of
graphgraph
If find cycle: pick minimum cost victimIf find cycle: pick minimum cost victim
Reference: Obermarck and BeriReference: Obermarck and Beri

6-7: 59
Model of Deadlock (1)
R:R:number of objects (locks)number of objects (locks)
r:r: objects locked per transactionobjects locked per transaction
N+1: Concurrent TransactionsN+1: Concurrent Transactions
ASSUMEASSUME
Transaction is: LOCKTransaction is: LOCK
rr
locklock
steps, then commitsteps, then commit
Uniform distributionUniform distribution
exclusive locks onlyexclusive locks only
Nr << RNr << R
r
R
Nxr/2
Probability a request waits: PW request
r N
R
( ) ≈
×
×2
Prob a transaction waits: PW Transaction
r N
R
( ) ≈
×
×
2
2

6-7: 60
Model of Deadlock (2)
R:R: number of objects (locks)number of objects (locks)
r:r: objects locked per transactionobjects locked per transaction
N+1: Concurrent TransactionsN+1: Concurrent Transactions
Probability of cycleProbability of cycle
length 2 + length 3 +...length 2 + length 3 +...
PW
N
PW
N
2 3
1 2




 +





+...
≈ ≈
PW
N
2
≈
r N
R
4
2
4
Prob transaction deadlocks PD:
assumes all cycles of length 2 ≈
r N
R
4 2
2
4System deadlock rate, N+1 times higher
Conclusions: control transaction size and duration
limit multiprogramming

6-7: 61
Common Performance Bugs
Convoys on semaphores or high-traffic locksConvoys on semaphores or high-traffic locks
Log semaphore is hotspotLog semaphore is hotspot
Sequential insert is hotspotSequential insert is hotspot
Lock manager costs too muchLock manager costs too much
A good number: 300 instructions for lock+unlockA good number: 300 instructions for lock+unlock
(no wait case))(no wait case))
= 1500 clocks on a P6/200= 1500 clocks on a P6/200
file or page granularity locking causes hotspot forfile or page granularity locking causes hotspot for
small filessmall files

6-7: 62
• Why lock (isolation)
• When to lock (2ø locking, 1°, 2°,3° isolation
• What to lock (granularity)
• How to lock
• Exotics (optimistic, field calls, escrow)
• Deadlock
• Performance

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