1. Indra Budi indra@cs.ui.ac.id
Transaction
Indra Budi

2. Exercise
A series of actions to be taken on the database such that either all actions are completed successfully, or none of them can be completed, is known as a(n):
a.) checkpoint.
b.) log.
c.) lock.
d.) transaction.
e.) concurrent. 2

3. Exercise
When two transactions are being processed against the database at the same time,
a.) they are called concurrent transactions.
b.) they are usually interleaved.
c.) they always result in a lost update problem.
d.) one must be rolled back.
e.) both a and b 3

4. Exercise
…. means a transaction executes when all actions of the transaction are completed fully, or none are. This means there are no partial transactions (such as when half the actions complete and the other half do not).
…. involves beginning a transaction with a ’consistent’ database, and finishing with a ’consistent’ database. For example, in a bank database, money should never be ”created” or ”deleted” without an appropriate deposit or withdrawal. Every transaction should see a consistent database.
….ensures that a transaction can run independently, without considering any side effects that other concurrently running transactions might have.
….define the persistence of committed data: once a transaction commits, the data should persist in the database even if the system crashes before the data is written to non-volatile storage.
A …. is a series of (possibly overlapping) transactions.
A …..occurs when a transaction reads a database object that has been modified by another not-yet-committed transaction.
A ….over a set S of transactions is a schedule whose effect on any consistent database instance is identical to that of some complete serial schedule over the set of committed transactions in S.
A …..is one in which a transaction can commit only after all other transactions whose changes it has read have committed. 4

5. Serializable schedule Schedule Atomicity Durability Isolation
Recoverable schedule
Serializable schedule
Schedule
Atomicity
Durability
Isolation
Dirty Read
Unrepeatable problem
Consistency
Cascading rollback 5

6. Exercise
Do exercise Elmasri pages 581 6

7. Schedule C is Serializable ?
25 25
125
250
T1 T2
Read(A); A  A+100
Write(A);
Read(A);A  A2;
Read(B); B  B+100;
Write(B);
Read(B);B  B2; 7

8. Is Schedule D serializable ?
25 25
125
250 50
150
T1 T2
Read(A); A  A+100
Write(A);
Read(A);A  A2;
Read(B);B  B2;
Write(B);
Read(B); B  B+100; 8

9. Database Administration
All large and small databases need database administration
Data administration refers to a function concerning all of an organization’s data assets
Database administration (DBA) refers to a person or office specific to a single database and its applications 9

10. DBA Tasks Managing database structure
Controlling concurrent processing
Managing processing rights and responsibilities
Developing database security
Providing for database recovery
Managing the DBMS
Maintaining the data repository 10

11. Managing Database Structure
DBA’s tasks:
Participate in database and application development
Assist in requirements stage and data model creation
Play an active role in database design and creation
Facilitate changes to database structure
Seek community-wide solutions
Assess impact on all users
Provide configuration control forum
Be prepared for problems after changes are made
Maintain documentation 11

12. Concurrency Control
Concurrency control ensures that one user’s work does not inappropriately influence another user’s work
No single concurrency control technique is ideal for all circumstances
Trade-offs need to be made between level of protection and throughput 12

13. Atomic Transactions
A transaction, or logical unit of work (LUW), is a series of actions taken against the database that occurs as an atomic unit
Either all actions in a transaction occur or none of them do 13

14. Example: Atomic Transaction14

15. Example: Atomic Transaction15

16. Concurrent Transaction
Concurrent transactions refer to two or more transactions that appear to users as they are being processed against a database at the same time
In reality, CPU can execute only one instruction at a time
Transactions are interleaved meaning that the operating system quickly switches CPU services among tasks so that some portion of each of them is carried out in a given interval
Concurrency problems: lost update and inconsistent reads 16

17. Example: Concurrent Transactions17

18. Example: Lost Update Problem18

19. Concurrency Control and Locking
We need a way to guarantee that our concurrent transactions can be serialized. Locking is one such means.
Locking is done to data items in order to reserve them for future operations.
A lock is a logical flag set by a transaction to alert other transactions the data item is in use. 19

20. Resource Locking
Resource locking prevents multiple applications from obtaining copies of the same record when the record is about to be changed 20

21. Characteristics of Lock
Locks may be applied to data items in two ways: Implicit Locks are applied by the DBMS Explicit Locks are applied by application programs.
Locks may be applied to:
a single data item (value)
an entire row of a table
a page (memory segment) (many rows worth)
an entire table
an entire database
This is referred to as the Lock granularity
Locks may be of type types depending on the requirements of the transaction:
An Exclusive Lock prevents any other transaction from reading or modifying the locked item.
A Shared Lock allows another transaction to read an item but prevents another transaction from writing the item. 21

22. Example: Explicit Locks22

23. The Two-Phase Locking Protocol
This is a protocol which ensures conflict-serializable schedules.
Phase 1: Growing Phase
transaction may obtain locks
transaction may not release locks
Phase 2: Shrinking Phase
transaction may release locks
transaction may not obtain locks
The protocol assures serializability. It can be proved that the transactions can be serialized in the order of their lock points (i.e. the point where a transaction acquired its final lock). 23

24. 2PL Examples User A places an exclusive lock on the balance
User A reads the balance
User A deducts $100 from the balance
User B attempts to place a lock on the balance but fails because A already has an exclusive lock User B is placed into a wait state
User A writes the new balance of $100
User A releases the exclusive lock on the balance User B places an exclusive lock on the balance
User B reads the balance
User B deducts $100 from the balance
User B writes the new balance of $100 24

25. 2PL Example User A places a shared lock on item raise_rate
User A reads raise_rate
User A places an exclusive lock on item Amy_salary
User A reads Amy_salary
User B places a shared lock on item raise_rate
User B reads raise_rate
User A calculates a new salary as Amy_salary * (1+raise_rate)
User B places an exclusive lock on item Bill_salary
User B reads Bill_salary
User B calculates a new salary as Bill_salary * (1+raise_rate)
User B writes Bill_salary
User A writes Amy_salary
User A releases exclusive lock on Amy_salary
User B releases exclusive lock on Bill_Salary
User B releases shared lock on raise_rate
User A releases shared lock on raise_rate 25

26. Deadlock User A places an exclusive lock on item 1001
User B places an exclusive lock on item 2002
User A attempts to place an exclusive lock on item 2002 User A placed into a wait state
User B attempts to place an exclusive lock on item 1001 User B placed into a wait state
This is called a deadlock. One transaction has locked some of the resources and is waiting for locks so it can complete. A second transaction has locked those needed items but is awaiting the release of locks the first transaction is holding so it can continue. 26

27. Deadlock
Deadlock, or the deadly embrace, occurs when two transactions are each waiting on a resource that the other transaction holds
Preventing deadlock
Allow users to issue all lock requests at one time
Require all application programs to lock resources in the same order
Breaking deadlock
Almost every DBMS has algorithms for detecting deadlock
When deadlock occurs, DBMS aborts one of the transactions and rollbacks partially completed work 27

28. Another Deadlock Example28

29. Optimistic/Pessimistic Locking
Optimistic locking assumes that no transaction conflict will occur
DBMS processes a transaction; checks whether conflict occurred
If not, the transaction is finished
If so, the transaction is repeated until there is no conflict
Pessimistic locking assumes that conflict will occur
Locks are issued before transaction is processed, and then the locks are released
Optimistic locking is preferred for the Internet and for many intranet applications 29

30. Example: Optimistic Locking30

31. Example: Pessimistic Locking31

32. Final Test Scheduled on Dec, 29th 2004, 09.00 – 11.00 WIB
May open all notes written by hand, no copies, no print-out, close textbook
Material from “Introduction to DB” to Concurrency Control 32

33. Next Wednesday (Dec 15th)
Quiz
Close Books & Close Notes
Material
SQL (Join, Aggregation, Grouping, Having, View)
Transactions Processing & Concurrency Control 33