1. CIS 720
Concurrency Control

2. Locking Atomic statement Th1: …. < x = x + 1; y = z>;…….
Can be used to perform two or more updates atomically
Th1: …. < x = x + 1; y = z>;…….
Th2:………….<m = m + 1;….>;…….

3. Transactions A database system is a set of shared data objects
A transaction is a sequential program which accesses data objects in the database
Each transaction is a sequence of read and write operations

4. The Transaction Model Examples of primitives for transactions.
Description
BEGIN_TRANSACTION
Make the start of a transaction
END_TRANSACTION
Terminate the transaction and try to commit
ABORT_TRANSACTION
Kill the transaction and restore the old values
READ
Read data from a file, a table, or otherwise
WRITE
Write data to a file, a table, or otherwise

5. Transactions
Each transaction is a sequence of read and write operations
The read set of transaction T, denoted by rs(t), is a set of variables read by T.
The write set ws(T) is defined similarly

6. Banking System } } Deposit(amount, account) Withdraw(amount, account)
{ x = db.account;
x = x + amount;
db.account = x; }
Withdraw(amount, account)
{ y = db.account;
if y > amount
y = y - amount;
db.account = y; }

7. Distributed Transactions
BEGIN_TRANSACTION reserve MCI -> JFK; reserve JFK -> FRK; END_TRANSACTION

8. Distributed Transactions
A nested transaction
A distributed transaction

9. A database has an invariant I (integrity constraint).
Each transaction is designed to preserve I
If transactions are executed simultaneously, then they may interfere and invalidate I.
The task of concurrency control is to preserve I.

10. Banking System } Transaction 1: Deposit $50 in Acc1
Possible interleavings
T1.x = db.Acc1;
T1.x = T1.x + 50
T2.x = db.Acc1;
T2.x = T2.x + 70;
db.Acc1 = T1.x
db.Acc1 = T2.x
Deposit(amount, account)
{ x = db.account;
x = x + amount;
db.account = x; }

11. Concurrency Control
General organization of managers for handling transactions.

12. Concurrency Control
General organization of managers for handling distributed transactions.

13. A schedule is any execution of a set of transaction operations
Two schedules T1 and T2 are equivalent if
- all read operations return the same value
in both schedules
- the final database state is the same in both schedules

14. T1: r1(x)0 w1(x)1
T2: r2(y)0 r2(x)1 w2(y)2
T1: r1(x) w1(x)1
T2: r2(y) r2(x) w2(y)2
T1: r1(x)0 w1(x)1
T2: r2(y) r2(x)1 w2(y)2

15. T1: r1(y) w1(x)1
T2: w2(y) r2(x) w2(y)2
T1: r1(y)0 w1(x)1
T2: w2(y)1 r2(x)1 w2(y)2
T1: r1(y)0 w1(x)1
T2: w2(y)1 r2(x)0 w2(y)2

16. A serial schedule is a schedule in which transactions execute one at a time.
We know that a serial schedule preserves IC of the database
A concurrency control algorithm can restricts the execution so that all schedules are serial.

17. A CC ensures that all schedules are equivalent to some serial schedule
A schedule that is equivalent to a serial schedule is called serializable

18. Untyped Concurrency control
Assumes that all transactions with intersecting read and write sets interfere with one another.
How can we determine whether a schedule is serializable
Let T1,…,Tn be a set of transactions
Define a graph G with transactions as nodes
There is an edge from Ti to Tj if
- there exists a read rj(x) which reads from wi(x)
- there exists a read ri(x) that occurs before wj(x)
- there exists a write wi(x) that occurs before wj(x)

19. A graph is serializable if the graph is acyclic

20. Two-phase Locking
Obtain a read or write lock before reading or writing a variable respectively.
rl(x): read lock operation
ul(x): unlock operation
wl(x): write lock operation

21. Locking rules:
- two read locks can be given at the same
time; read and write lock must be
exclusive
* conflict table

22. Simple locking does not ensure serializability

23. T1: r1(y) w1(x)1
T2: w2(y) r2(x) w2(y)2
T1: r1(y)0 w1(x)1
T2: w2(y)1 r2(x)1 w2(y)2
T1: r1(y)0 w1(x)1
T2: w2(y)1 r2(x)0 w2(y)2

24. T1: L(y) r1(y)1 ul(y) L(x( w1(x)1 ul(x)
T2: L(x)w2(y)1 UL(x) L(x) r2(x)1 ul(x) w2(y)2

25. Two phase locking rule Locking phase: acquire all locks
Unlocking phase: release all locks
Two-phase locking ensures serializability
It is prone to deadlocks

26. Two-Phase Locking (1)
Two-phase locking.

27. Two-Phase Locking (2)
Strict two-phase locking.

28. Writeahead Log a) A transaction
x = 0;
y = 0;
BEGIN_TRANSACTION;
x = x + 1;
y = y + 2
x = y * y;
END_TRANSACTION;
(a)
Log
[x = 0 / 1]
(b)
[y = 0/2]
(c)
[x = 1/4]
(d)
a) A transaction
b) – d) The log before each statement is executed

29. Graph based protocols Impose a partial ordering  on data items
If d1  d2, then any transaction accessing both d1 and d2 must first access d1 before d2.

30. Tree protocol Only exclusive locks are allowed
First item to be locked can be any one
Next, a data item can be locked only if the parent is already locked
Data items can be unlocked at any time
A data item cannot be relocked by a transaction.

31. Semantics-based concurrency control
If transactions T1 and T2 do not interfere then they can be executed concurrently.
Two operations op1 and op2 do not conflict if they commute (that is, op1; op2 is the same as op2; op1)

32. Predicate Locking Each transaction specifies a predicate as a lock.
A new transaction can execute if it does not interfere with existing predicate locks