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ï‚ž Goals: Understand the basic properties of a
transaction and learn the concepts underlying
transaction processing as well as the concurrent
executions of transactions.
ï‚ž A transaction is a unit of a program execution that
accesses and possibly modies various data objects
(tuples, relations).
ï‚ž DBMS has to maintain the following properties of
transactions:
ï‚ž Atomicity: A transaction is an atomic unit of
processing, and it either has to be performed in its
entirety or not at all.
ï‚ž Consistency: A successful execution of a
transaction must take a consistent database state to
a (new) consistent database state. (; integrity
constraints).
Continue…
ï‚ž Isolation: A transaction must not make its
modications visible to other transactions until it is
committed, i.e., each transaction is unaware of
other transactions executing concurrently in the
system. (; concurrency control)
ï‚ž Durability: Once a transaction has committed its
changes, these changes must never get lost due to
subsequent (system) failures. (; recovery).
Continue…
ï‚ž Model used for representing database modications
of a transaction:
ï‚ž read(A,x): assign value of database object A to
variable x;
ï‚ž write(x,A): write value of variable x to database
object A.
Continue…
ï‚ž Example of a Transaction T
read(A,x)
x := x - 200
write(x,A) Transaction Schedule reflect
read(B,y) chronological order of operations
y := y + 100
write(y,B)
Continue…
ï‚ž Goal: Synchronization" of transactions; allowing
concurrency (instead of insisting on a strict serial
transaction execution, i.e., process complete T1,
then T2, then T3 etc.) ; increase the throughput of
the system, ; minimize response time for each
transaction.
Continue…
ï‚ž Lost Update
Time Transaction T1 Transaction T2
1 read(A,x)
2 x:=x+200
3 read(A,y)
4 y:=y+100
5 write(x,A)
6 write(y,A)
7 commit
8 commit
ï‚ž The update performed by T1 gets lost; possible
solution: T1
ï‚ž locks/unlocks database object A
ï‚ž =) T2 cannot read A while A is modied by T1
ï‚ž DBMS must control concurrent execution of
transactions to ensure read consistency, i.e., to
avoid dirty reads etc.
ï‚ž A (possibly concurrent) schedule S is
serializable if it is equivalent to a serial
schedule S’, i.e., S has the same result database
state as S’.
ï‚ž How to ensure serializability of concurrent
transactions?
Continue…
ï‚ž Conflicts between operations of two transactions:
Ti Tj Ti Tj
read(A,x) read(A,x)
read(A,y) write(y,A)
(order does not matter) (order matters)
Ti Tj Ti Tj
write(x,A) write(x,A)
read(A,y) write(y,A)
(order matters) (order matters)
ï‚ž A schedule S is serializable with regard to the above conicts i
ï‚ž S can be transformed into a serial schedule S' by a series of swaps
ï‚ž of non-conicting operations.
Continue…
ï‚ž Checks for serializability are based on precedence
graph that describes dependencies among concurrent
transactions; if the graph has no cycle, then the
transactions are serializable.
ï‚ž they can be executed concurrently without aecting
each others transaction result.
Continue…
Testing for conflict serializability: Algorithm
ï‚¡ Looks at only read_Item (X) and write_Item (X)
operations.
 Constructs a precedence graph (serialization graph) - a
graph with directed edges.
 An edge is created from Ti to Tj if one of the
operations in Ti appears before a conflicting operation
in Tj.
ï‚¡ The schedule is serializable if and only if the
precedence graph has no cycles.
Continue…
ï‚ž FIGURE 17.7 Constructing the precedence graphs for schedules A and D
from Figure 17.5 to test for conflict serializability.
ï‚¡ (a) Precedence graph for serial schedule A.
ï‚¡ (b) Precedence graph for serial schedule B.
ï‚¡ (c) Precedence graph for schedule C (not serializable).
ï‚¡ (d) Precedence graph for schedule D (serializable, equivalent to schedule A).
ï‚ž One way to ensure serializability is to require that
accesses to data objects must be done in a mutually
exclusive manner.
ï‚ž Allow transaction to access data object only if it is
currently holding a lock on that object.
ï‚ž Serializability can be guaranteed using locks in a
certain fashion.
=> Tests for serializability are redundant !
ï‚ž Types of locks that can be used in a transaction T:
• slock(X): shared-lock (read-lock); no other transaction
than T can write data object X, but they can read X.
• xlock(X): exclusive-lock; T can read/write data object
X; no other transaction can read/write X, and
• unlock(X): unlock data object X.
Continue…
ï‚ž Lock-Compatibility Matrix:
requested lock existing lock
slock xlock
slock OK No
xlock No No
ï‚ž E.g., xlock(A) has to wait until all slock(A) have
been released.
Continue…
ï‚ž Using locks in a transaction (lock requirements, LR):
ï‚ž before each read(X) there is either a xlock(X) or a
slock(X) and no unlock(X) in between
ï‚ž before each write(X) there is a xlock(X) and no
unlock(X) in between
ï‚ž a slock(X) can be tightened using a xlock(X)
ï‚ž after a xlock(X) or a slock(X) sometime an unlock(X)
must occur.
 But: “Simply setting locks/unlocks is not sucient“
 replace each read(X)  slock(X); read(X) unlock(X),
and write(X)  xlock(X);write(X);unlock(X).
ï‚ž Two-Phase Locking Protocol (TPLP):
ï‚ž A transaction T satises the TPLP iff
ï‚ž after the rst unlock(X) no locks xlock(X) or slock(X) occur
ï‚ž That is, rst T obtains locks, but may not release any lock
(growing phase)
and then T may release locks, but may not obtain new locks
(shrinking phase)
ï‚ž Strict Two-Phase Locking Protocol:
ï‚ž All unlocks at the end of the transaction T =) no dirty reads
are possible, i.e., no other transaction can write the (modied)
data objects in case of a rollback of T.
ï‚ž Transaction Concept
ï‚ž Properties of transaction
ï‚ž Serializability of transaction
ï‚ž Testing of serializability
ï‚ž Two-Phase Commit protocol
Transaction  management DBMS

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Transaction management DBMS

  • 1.
  • 2. ï‚ž Goals: Understand the basic properties of a transaction and learn the concepts underlying transaction processing as well as the concurrent executions of transactions. ï‚ž A transaction is a unit of a program execution that accesses and possibly modies various data objects (tuples, relations).
  • 3. ï‚ž DBMS has to maintain the following properties of transactions: ï‚ž Atomicity: A transaction is an atomic unit of processing, and it either has to be performed in its entirety or not at all. ï‚ž Consistency: A successful execution of a transaction must take a consistent database state to a (new) consistent database state. (; integrity constraints). Continue…
  • 4. ï‚ž Isolation: A transaction must not make its modications visible to other transactions until it is committed, i.e., each transaction is unaware of other transactions executing concurrently in the system. (; concurrency control) ï‚ž Durability: Once a transaction has committed its changes, these changes must never get lost due to subsequent (system) failures. (; recovery). Continue…
  • 5. ï‚ž Model used for representing database modications of a transaction: ï‚ž read(A,x): assign value of database object A to variable x; ï‚ž write(x,A): write value of variable x to database object A. Continue…
  • 6. ï‚ž Example of a Transaction T read(A,x) x := x - 200 write(x,A) Transaction Schedule reflect read(B,y) chronological order of operations y := y + 100 write(y,B) Continue…
  • 7. ï‚ž Goal: Synchronization" of transactions; allowing concurrency (instead of insisting on a strict serial transaction execution, i.e., process complete T1, then T2, then T3 etc.) ; increase the throughput of the system, ; minimize response time for each transaction. Continue…
  • 8. ï‚ž Lost Update Time Transaction T1 Transaction T2 1 read(A,x) 2 x:=x+200 3 read(A,y) 4 y:=y+100 5 write(x,A) 6 write(y,A) 7 commit 8 commit ï‚ž The update performed by T1 gets lost; possible solution: T1 ï‚ž locks/unlocks database object A ï‚ž =) T2 cannot read A while A is modied by T1
  • 9. ï‚ž DBMS must control concurrent execution of transactions to ensure read consistency, i.e., to avoid dirty reads etc. ï‚ž A (possibly concurrent) schedule S is serializable if it is equivalent to a serial schedule S’, i.e., S has the same result database state as S’. ï‚ž How to ensure serializability of concurrent transactions? Continue…
  • 10. ï‚ž Conflicts between operations of two transactions: Ti Tj Ti Tj read(A,x) read(A,x) read(A,y) write(y,A) (order does not matter) (order matters) Ti Tj Ti Tj write(x,A) write(x,A) read(A,y) write(y,A) (order matters) (order matters) ï‚ž A schedule S is serializable with regard to the above conicts i ï‚ž S can be transformed into a serial schedule S' by a series of swaps ï‚ž of non-conicting operations. Continue…
  • 11. ï‚ž Checks for serializability are based on precedence graph that describes dependencies among concurrent transactions; if the graph has no cycle, then the transactions are serializable. ï‚ž they can be executed concurrently without aecting each others transaction result. Continue…
  • 12. Testing for conflict serializability: Algorithm ï‚¡ Looks at only read_Item (X) and write_Item (X) operations.  Constructs a precedence graph (serialization graph) - a graph with directed edges.  An edge is created from Ti to Tj if one of the operations in Ti appears before a conflicting operation in Tj. ï‚¡ The schedule is serializable if and only if the precedence graph has no cycles. Continue…
  • 13. ï‚ž FIGURE 17.7 Constructing the precedence graphs for schedules A and D from Figure 17.5 to test for conflict serializability. ï‚¡ (a) Precedence graph for serial schedule A. ï‚¡ (b) Precedence graph for serial schedule B. ï‚¡ (c) Precedence graph for schedule C (not serializable). ï‚¡ (d) Precedence graph for schedule D (serializable, equivalent to schedule A).
  • 14. ï‚ž One way to ensure serializability is to require that accesses to data objects must be done in a mutually exclusive manner. ï‚ž Allow transaction to access data object only if it is currently holding a lock on that object. ï‚ž Serializability can be guaranteed using locks in a certain fashion. => Tests for serializability are redundant !
  • 15. ï‚ž Types of locks that can be used in a transaction T: • slock(X): shared-lock (read-lock); no other transaction than T can write data object X, but they can read X. • xlock(X): exclusive-lock; T can read/write data object X; no other transaction can read/write X, and • unlock(X): unlock data object X. Continue…
  • 16. ï‚ž Lock-Compatibility Matrix: requested lock existing lock slock xlock slock OK No xlock No No ï‚ž E.g., xlock(A) has to wait until all slock(A) have been released. Continue…
  • 17. ï‚ž Using locks in a transaction (lock requirements, LR): ï‚ž before each read(X) there is either a xlock(X) or a slock(X) and no unlock(X) in between ï‚ž before each write(X) there is a xlock(X) and no unlock(X) in between ï‚ž a slock(X) can be tightened using a xlock(X) ï‚ž after a xlock(X) or a slock(X) sometime an unlock(X) must occur. ï‚ž But: “Simply setting locks/unlocks is not sucient“ ï‚ž replace each read(X)  slock(X); read(X) unlock(X), and write(X)  xlock(X);write(X);unlock(X).
  • 18. ï‚ž Two-Phase Locking Protocol (TPLP): ï‚ž A transaction T satises the TPLP iff ï‚ž after the rst unlock(X) no locks xlock(X) or slock(X) occur ï‚ž That is, rst T obtains locks, but may not release any lock (growing phase) and then T may release locks, but may not obtain new locks (shrinking phase) ï‚ž Strict Two-Phase Locking Protocol: ï‚ž All unlocks at the end of the transaction T =) no dirty reads are possible, i.e., no other transaction can write the (modied) data objects in case of a rollback of T.
  • 19. ï‚ž Transaction Concept ï‚ž Properties of transaction ï‚ž Serializability of transaction ï‚ž Testing of serializability ï‚ž Two-Phase Commit protocol

Editor's Notes

  1. Unit: 6 Transaction Management