Sekolah Tinggi Ilmu Statistik (STIS)
Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
1
Lecture 3
Dr. Said Mirza Pahlevi, M.Eng.
2
Today’s Lecture

Concurrency Control
 Meaning of serializability
 Conflict serializability
 View serializability

Last time lecture
Locking Methods
Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
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Second Subtopic (from previous lecture)
Dr. Said Mirza Pahlevi, M.Eng.
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View Serializability

Conflict equivalent ----- View equivalent

Conflict serializable ----- View serializable
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Sekolah Tinggi Ilmu Statistik (STIS)
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Motivating example
Schedule Q
t1:
t2:
t3:
t4:
T1
Read(A)
T2
T3
Write(A)
Write(A)
Dr. Said Mirza Pahlevi, M.Eng.
Write(A)
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Motivating Example
Same as
Q = r1(A) w2(A) w1(A) w3(A)
P(Q): T1
T2
T3
 Not conflict serializable!
Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
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Compare Q to Serial Schedule (S)
Q
T1
Read(A)
Write(A)
S
T1
Read(A)
Write(A)
T2
T3
Write(A)
Write(A)
T2
Write(A)
T3
Write(A)
T1 reads same thing in Q dan S
T2, T3 read same thing (nothing?)
After Q or S, DB is left in same state
 So what is wrong with Q?



Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
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View Equivalent

Two schedules S1 and S2 are view equivalent:
1. IF in S1: wj(A)  ri(A), THEN in S2: wj(A)  ri(A)
2. IF in S1: ri(A) reads initial DB value, THEN in S2: ri(A) also
reads initial DB value
3. IF in S1: Ti does last write on A, THEN in S2: Ti also does last
write on A
 means “reads value produced by”
Dr. Said Mirza Pahlevi, M.Eng.
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View Serializability

Schedule is view serializable if it is view equivalent to a
serial schedule.

Offers less stringent definition of schedule equivalence
than conflict serializability.

Every conflict serializable schedule is view serializable,
although converse is not true.

It can be shown that any view serializable schedule
that is not conflict serializable contains one or more
blind writes.
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View Serializable Test
1. Add final transaction Tf that reads all DB
e.g.: S = …..W1(A)…….. W2(A)…  Rf(A)
last A write
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add
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View Serializable Test
2. Add initial transaction Tb that writes all DB
e.g.: S = wb(A)  ... r1(A) … w2(A) …
add
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View Serializable Test
3. Create labeled precedence (LP) graph of S:
0
(a) If wi(A)  rj(A) in S, add Ti 
Tj
 means “reads value produced by”
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View Serializable Test
(b) For each wi(A)  rj(A) do
consider each wk(A): [Tk Tb]
(i) IF Ti Tb  Tj Tf THEN insert
p
Tk  Ti
some new p
p
Tj  Tk
(ii) IF Ti =Tb  Tj Tf THEN insert
0 T
Tj 
k
(iii) IF Ti Tb  Tj =Tf THEN insert
0
Tk 
Ti
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View Serializable Test
4. Check if LP(S) is acyclic; if so, then S is view
serializable
- For each pair of “p” arcs (p  0),
choose one
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Example 1: View Serializable (VS)
Check if Q is view serializable:
Q = r1(A) w2(A) w1(A) w3(A)
Q’ = wb(A) r1(A) w2(A) w1(A) w3(A)rf(A)
T1
0
Tb
rule 3a
rule 3b (ii)
0
0
0
T2
Tf
0
Acyclic graph!!
Q is VS
Dr. Said Mirza Pahlevi, M.Eng.
rule 3b (iii)
0
T3
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Example 2: View Serializable (VS)
Z=wb(A)r1(A) w2(A) r3(A) w1(A) w3(A) rf(A)
T1
0
1
Tb
do not pick
this one of “1” pair
0 T2
1
0
rule 3a
rule 3b (i)
0
rule 3b (ii)
0
Tf
0
rule 3b (iii)
0
T3
Acyclic graph, so Z is VS
(equivalent to Tb T1 T2 T3 Tf)
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Recoverability

Serializability identifies schedules that maintain
database consistency, assuming no transaction fails.

Could also examine recoverability of transactions
within schedule.

If transaction fails, atomicity requires effects of
transaction to be undone

Durability states that once transaction commits, its
changes cannot be undone (without running another,
compensating, transaction).
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If T9 Rollback Instead of Commit
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
We should undo
T10 but T10 has
committed the
transaction
(durability does
not allow it).

This is a nonrecoverable
schedule
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Recoverable Schedule

A schedule where, for each pair of transactions Ti
and Tj, if Tj reads a data item previously written by
Ti, then the commit operation of Ti precedes the
commit operation of Tj.

If commit operation of Tj precedes the commit
operation of Ti then it is unrecoverable, because of
the durability.
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Third Topic
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Concurrency Control Techniques

Two basic concurrency control techniques:


Locking,
Timestamping.

Both are conservative approaches: delay
transactions in case they conflict with other
transactions.

Optimistic methods assume conflict is rare and
only check for conflicts at commit.
Dr. Said Mirza Pahlevi, M.Eng.
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Locking

Transaction uses locks to deny access to other
transactions and so prevent incorrect updates.

Most widely used approach to ensure serializability.

Generally, a transaction must claim a shared (read) or
exclusive (write) lock on a data item before read or
write.

Lock prevents another transaction from modifying
item or even reading it, in the case of a write lock.
Dr. Said Mirza Pahlevi, M.Eng.
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Locking - Basic Rules
1.
If transaction has shared lock on item, it can read
but not update item.
2.
If transaction has exclusive lock on item, it can both
read and update item.
3.
Reads cannot conflict, so more than one transaction
can hold shared locks simultaneously on same item.
4.
Exclusive lock gives transaction exclusive access to
that item.
Dr. Said Mirza Pahlevi, M.Eng.
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Locking - Basic Rules
5.
Some systems allow transaction to upgrade read
lock to an exclusive lock, or downgrade exclusive
lock to a shared lock.
But this basic rules does not guarantee serializability
of schedules by themselves
Dr. Said Mirza Pahlevi, M.Eng.
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Incorrect Locking Schedule
Valid schedule using basic rules:
S = {write_lock(T9, balx), read(T9, balx),
write(T9, balx), unlock(T9, balx),
write_lock(T10, balx), read(T10, balx), write(T10,
balx), unlock(T10, balx), write_lock(T10, baly),
read(T10, baly), write(T10, baly), unlock(T10,
baly), commit(T10), write_lock(T9, baly),
read(T9, baly), write(T9, baly), unlock(T9, baly),
commit(T9) }
Dr. Said Mirza Pahlevi, M.Eng.
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Example - Incorrect Locking Schedule

If at start, balx = 100, baly = 400, result should be:
 balx = 220, baly = 330, if T9 executes before T10, or
 balx = 210, baly = 340, if T10 executes before T9.

However, result gives balx = 220 and baly = 340.

S is not a serializable schedule.
 Problem is that transactions release locks too soon, resulting in loss
of total isolation and atomicity.
 To guarantee serializability, need an additional protocol concerning
the positioning of lock and unlock operations in every transaction.
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Two-Phase Locking (2PL)

Transaction follows 2PL protocol if all locking
operations precede first unlock operation in the
transaction.

Two phases for transaction:
 Growing phase - acquires all locks but cannot release any
locks.
 Shrinking phase - releases locks but cannot acquire any new
locks.
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Preventing Lost Update Problem
using 2PL
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Preventing Uncommitted
Dependency Problem using 2PL
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Apply 2PL!
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Preventing Inconsistent Analysis
Problem using 2PL
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Apply 2PL!
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Cascading Rollback

If every transaction in a schedule follows 2PL,
schedule is serializable.

However, problems can occur with interpretation
of when locks can be released.
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Cascading Rollback
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
Transactions conform to
2PL.

T14 aborts.

Since T15 is dependent
on T14, T15 must also be
rolled back. Since T16 is
dependent on T15, it too
must be rolled back.

This is called cascading
rollback.

To prevent this with 2PL,
leave release of all locks
until end of transaction.
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Deadlock
An impasse (kebuntuan) that may result when
two (or more) transactions are each waiting for
locks held by the other to be released.
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Deadlock

Only one way to break deadlock: abort one or
more of the transactions.

Deadlock should be transparent to user, so DBMS
should restart transaction(s).

Three general techniques for handling deadlock:
 Timeouts.
 Deadlock prevention.
 Deadlock detection and recovery.
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Sekolah Tinggi Ilmu Statistik (STIS)
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Timeouts

Transaction that requests lock will only wait for a
system-defined period of time.

If lock has not been granted within this period,
lock request times out.

In this case, DBMS assumes transaction may be
deadlocked, even though it may not be, and it
aborts and automatically restarts the transaction.
Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
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Deadlock Prevention

DBMS looks ahead to see if transaction would cause
deadlock and never allows deadlock to occur.

Could order transactions using transaction
timestamps:
 Wait-Die - only an older transaction can wait for younger one,
otherwise transaction is aborted (dies) and restarted with same
timestamp.
 Wound-Wait - only a younger transaction can wait for an older one.
If older transaction requests lock held by younger one, younger one
is aborted (wounded).
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Wait-Die

Transactions given a timestamp when they arrive
…. ts(T1)

T1 can only wait for T2 if ts(T1)< ts(T2)
...else die
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Wound-Wait
Transactions given a timestamp when they arrive
… ts(T1)
 T1 wounds T2 if ts(T1)< ts(T2)
else T1 waits

“Wound”: T2 rolls back (if it cannot finish in small
interval of time) and gives lock to T1
Dr. Said Mirza Pahlevi, M.Eng.
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Deadlock Detection and Recovery

DBMS allows deadlock to occur but recognizes it
and breaks it.

Usually handled by construction of wait-for graph
(WFG) showing transaction dependencies:
 Create a node for each transaction.
 Create edge Ti  Tj, if Ti waiting to lock item locked by Tj.

Deadlock exists if and only if WFG contains cycle.

WFG is created at regular intervals.
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Example - Wait-For-Graph (WFG)
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Granularity of Data Items

Size of data items chosen as unit of protection by
concurrency control protocol.

Ranging from coarse to fine:





The entire database
A file
A page (or area or database spaced)
A record
A field value of a record
Dr. Said Mirza Pahlevi, M.Eng.
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Granularity of Data Items

Tradeoff:
 Coarser, the lower the degree of concurrency;
 Finer, more locking information that is needed to be stored.

Best item size depends on the types of
transactions.
 What will happen if we use database lock for transaction
updating a single record/tuple?
 What will happen if we use tuple lock for transaction
updating 95% of tuple?
Dr. Said Mirza Pahlevi, M.Eng.
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Hierarchy of Granularity

Could represent granularity of locks in a
hierarchical structure.

Root node represents entire database, level 1s
represent files, etc.

When node is locked, all its descendants are also
locked.

DBMS should check hierarchical path before
granting lock.
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Levels of
Locking
If page2 is locked, the
record1, record2, field1
and field2 are locked
If lock request on
record1, check page2,
file2 and database
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Intension Lock

Intention lock could be used to lock all ancestors
of a locked node.

Intention locks can be read or write.

Applied top-down, released bottom-up.
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Intention Lock

If another transaction requests a lock on any of
descendants of the locked node, the DBMS checks
the hierachical path from the root to the requested
node.

A transaction may request a lock on a node and a
descendant of the node is already locked.
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Locking Level + 2PL
1.
No lock can be granted once any node has been
locked.
2.
No node may be locked until its parent is locked
by an intention lock.
3.
No node may be unlocked until all its
descendants are unlocked
Dr. Said Mirza Pahlevi, M.Eng.
Sekolah Tinggi Ilmu Statistik (STIS)
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