©Silberschatz, Korth and Sudarshan14.1Database System Concepts - 6 th Edition UNIT 5 :Transactions Transaction concepts, properties of transactions, serializability

©Silberschatz, Korth and Sudarshan14.1Database System Concepts - 6th Edition

UNIT 5 :TransactionsUNIT 5 :Transactions

Transaction concepts, properties of transactions, serializability of transactions, testing for serializability, System recovery, Two- Phase Commit protocol, Recovery and Atomicity, Log-based recovery, concurrent executions of transactions and related problems, Locking mechanism, solution to concurrency related problems, deadlock, , two-phase locking protocol, Isolation, Intent locking


ACID PropertiesACID Properties

Atomicity. Either all operations of the transaction are properly reflected in the database or none are.

Consistency. Execution of a transaction in isolation preserves the consistency of the database.

Isolation. Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions. Intermediate transaction results must be hidden from other concurrently executed transactions.

Durability. After a transaction completes successfully, the changes it has made to the database persist, even if there are system failures.

A transaction is a unit of program execution that accesses and possibly updates various data items.To preserve the integrity of data the database system must ensure:


Transaction ConceptTransaction Concept

A transaction is a unit of program execution that accesses and possibly updates various data items.

E.g. transaction to transfer $50 from account A to account B:

1. read(A)

2. A := A – 50

3. write(A)

4. read(B)

5. B := B + 50

6. write(B)

Two main issues to deal with:

Failures of various kinds, such as hardware failures and system crashes

Concurrent execution of multiple transactions


Example of Fund TransferExample of Fund Transfer

Transaction to transfer $50 from account A to account B:

1. read(A)

2. A := A – 50

3. write(A)

4. read(B)

5. B := B + 50

6. write(B)

Atomicity requirement

if the transaction fails after step 3 and before step 6, money will be “lost” leading to an inconsistent database state

Failure could be due to software or hardware

the system should ensure that updates of a partially executed transaction are not reflected in the database

Durability requirement — once the user has been notified that the transaction has completed (i.e., the transfer of the $50 has taken place), the updates to the database by the transaction must persist even if there are software or hardware failures.


Example of Fund Transfer (Cont.)Example of Fund Transfer (Cont.)

Transaction to transfer $50 from account A to account B:1. read(A)

2. A := A – 50

3. write(A)

4. read(B)

5. B := B + 50

6. write(B) Consistency requirement in above example:

the sum of A and B is unchanged by the execution of the transaction A transaction must see a consistent database. During transaction execution the database may be temporarily inconsistent. When the transaction completes successfully the database must be

consistent Erroneous transaction logic can lead to inconsistency


Example of Fund Transfer (Cont.)Example of Fund Transfer (Cont.)

Isolation requirement — if between steps 3 and 6, another transaction T2 is allowed to access the partially updated database, it will see an inconsistent database (the sum A + B will be less than it should be). T1 T2

1. read(A)

2. A := A – 50

3. write(A) read(A), read(B), print(A+B)

4. read(B)

5. B := B + 50

6. write(B

Isolation can be ensured trivially by running transactions serially that is, one after the other.


Transaction StateTransaction State

Active – the initial state; the transaction stays in this state while it is executing

Partially committed – after the final statement has been executed.

Failed -- after the discovery that normal execution can no longer proceed.

Aborted – after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted:

restart the transaction

can be done only if no internal logical error

kill the transaction

Committed – after successful completion.


Transaction State (Cont.)Transaction State (Cont.)


Concurrent ExecutionsConcurrent Executions

Multiple transactions are allowed to run concurrently in the system. Advantages are:

increased processor and disk utilization, leading to better transaction throughput

E.g. one transaction can be using the CPU while another is reading from or writing to the disk

reduced average response time for transactions: short transactions need not wait behind long ones.

Concurrency control schemes – mechanisms to achieve isolation

that is, to control the interaction among the concurrent transactions in order to prevent them from destroying the consistency of the database


SchedulesSchedules

Schedule – a sequences of instructions that specify the chronological order in which instructions of concurrent transactions are executed

a schedule for a set of transactions must consist of all instructions of those transactions

must preserve the order in which the instructions appear in each individual transaction.

A transaction that successfully completes its execution will have a commit instructions as the last statement

by default transaction assumed to execute commit instruction as its last step

A transaction that fails to successfully complete its execution will have an abort instruction as the last statement


Schedule 1Schedule 1

Let T1 transfer $50 from A to B, and T2 transfer 10% of the balance from A to B.

A serial schedule in which T1 is followed by T2 :



• A serial schedule where T2 is followed by T1



Let T1 and T2 be the transactions defined previously. The following schedule is not a serial schedule, but it is equivalent to Schedule 1.

In Schedules 1, 2 and 3, the sum A + B is preserved.



The following concurrent schedule does not preserve the value of (A + B ).


SerializabilitySerializability

Basic Assumption – Each transaction preserves database consistency.

Thus serial execution of a set of transactions preserves database consistency.

A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule. Different forms of schedule equivalence give rise to the notions of:

1. conflict serializability

2. view serializability


Simplified view of transactionsSimplified view of transactions

We ignore operations other than read and write instructions

We assume that transactions may perform arbitrary computations on data in local buffers in between reads and writes.

Our simplified schedules consist of only read and write instructions.


Conflicting Instructions Conflicting Instructions

Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q.

1. li = read(Q), lj = read(Q). li and lj don’t conflict. 2. li = read(Q), lj = write(Q). They conflict. 3. li = write(Q), lj = read(Q). They conflict 4. li = write(Q), lj = write(Q). They conflict

Intuitively, a conflict between li and lj forces a (logical) temporal order between them.

If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule.


Purpose of Concurrency ControlPurpose of Concurrency Control

To enforce Isolation (through mutual exclusion) among conflicting transactions.

To preserve database consistency through consistency preserving execution of transactions.

To resolve read-write and write-write conflicts.


Locking MechanismLocking MechanismIn a multiuser environment where several

users are accessing same resources, then in order to maintain the consistency of the database. It is very important that the resources being used by one user should be protected from rest of the users until the first user completes its task i.e in order to prevent the problem of data inconsistency, database must of locking mechanism.


LockLock

Def: Lock is the mechanism used to prevent distributive interaction between the users that are accessing same resources simultaneously. Locks are used to tempararily restrict other users to access the resources when one user is using that resource.The resource(table or view) remains locked until commit or rollback is used.


Locking TechniquesLocking Techniques

Locking is an operation which secures (a) permission to Read (b) permission to Write a data item for a transaction.

Example: Lock (A). Data item A is locked in behalf of the

requesting transaction.

Unlocking is an operation which removes these permissions from the data item.

Example: Unlock (A): Data item A is made available to all other

transactions.

Lock and Unlock are Atomic operations.


Two locks modes:Two locks modes:

1) Shared Mode (read)

2) Exclusive Mode (write). Shared mode: shared lock (S)

More than one transaction can apply share lock on X for reading its value but no write lock can be applied on X by any other transaction.

Exclusive mode: Write lock (X) Only one write lock on X can exist at any time and no

shared lock can be applied by any other transaction on X.


How to add lock and unlock instructionHow to add lock and unlock instruction


How to add lock and Unlock InstructionsHow to add lock and Unlock Instructions T1 :

Lock-X(A);

Read(A)

A=A-50;

Write(A);

Unlock(A); T2:

Lock-X(B) Lock-X(A);

Read(B); Read(A)

B=B+50; Temp=A*0.1;

Write(B); A=A-Temp;

Unlock(B) Write(A)

Lock-X(B)

Read(B);

B=B+Temp;

Write(B);

Unlock(B)


DeadlockDeadlock

When two or more transaction are each waiting for locks to be released that are held by the other.

Thus we have arrived at a state where neither of these transactions can ever proceed with its normal execution. This situation is called deadlock.



Thus we can say that the solution of inconsistency leads to deadlock problem. If we do not use locking or unlock data items as soon as possible after reading or writing them, we may get inconsistent states. On the other hand, if we do not unlock a data item before requesting a lock on another data item deadlocks may occur. There are ways to avoid deadlock in some situations. Deadlocks are definitely preferable to inconsistent states, since they can be handled by rolling back of transactions, where as inconsistent states may lead to real world problems that cannot be handled by the database system.

ConclusionConclusion


Solution Solution

In a multiprogramming environment where more than one transactions can be concurrently executed, there exists a need of protocols to control the concurrency of transaction to ensure atomicity and isolation properties of transactions.


Two-Phase Locking ProtocolTwo-Phase Locking Protocol

This locking protocol is divides transaction execution phase into three parts. In the first part, when transaction starts executing, transaction seeks grant for locks it needs as it executes. Second part is where the transaction acquires all locks and no other lock is required. Transaction keeps executing its operation. As soon as the transaction releases its first lock, the third phase starts. In this phase a transaction cannot demand for any lock but only releases the acquired locks.



Two-Phase Locking ProtocolTwo-Phase Locking Protocol 1) Growing Phase : where all locks(read or write) are being

acquired by transaction desired data items one at a time.

2) Shrinking Phase : where locks held by the transaction are being released i.e A transaction unlocks its locked data items one at a time.

To claim an exclusive (write) lock, a transaction must first acquire a shared (read) lock and then upgrade it to exclusive lock.

Requirement: For a transaction these two phases must be mutually

exclusively, that is, during locking phase unlocking phase must not start and during unlocking phase locking phase must not begin.


Time stamp based protocolsTime stamp based protocols

The most commonly used concurrency protocol is time-stamp based protocol. This protocol uses either system time or logical counter to be used as a time-stamp.

Lock based protocols manage the order between conflicting pairs among transaction at the time of execution whereas time-stamp based protocols start working as soon as transaction is created.


The timestamp-ordering protocol ensures serializability among transaction in their conflicting read and write operations. This is the responsibility of the protocol system that the conflicting pair of tasks should be executed according to the timestamp values of the transactions.

Time-stamp of Transaction Ti is denoted as TS(Ti).

Read time-stamp of data-item X is denoted by R-timestamp(X).

Write time-stamp of data-item X is denoted by W-timestamp(X).


Timestamp ordering protocol works as Timestamp ordering protocol works as follows:follows:

If a transaction Ti issues read(X) operation:

If TS(Ti) < R-timestamp(X)

Operation rejected.

If TS(Ti) >= R-timestamp(X)

Operation executed.

If a transaction Ti issues write(X) operation:

If TS(Ti) < R-timestamp(X)

Operation rejected.

If TS(Ti) < W-timestamp(X)

Operation rejected and Ti rolled back.

Otherwise, operation executed. All data-item Timestamps updated.


PartitionPartition

Dividing the table data across multiple tables or parts is called partitioning the table.The table that is partitined is called partition table and the parts are called partition.

Advantages:

1) The performance of queries against the table improves because oracle has to only search one partition instead of entire table to resolve the query.


2) The table is easier to manage

3) Back up and recovery operations can be performed in better ways.

Types of partition

1)Range Partitioning: In it tables is divide into specified part according to the range given.

2)List Partitioning: It is same as range partitioning ,Instead of using integer list partitioning use character .


Syntax And Example:Syntax And Example:

Syntax: Create table table-name(attr1 datatype 1,attr2 datatype 2…….attr n datatype n)

Partition by range(Attr)

(partition part-name values less than value1,

partition part-name values less than value2);

Example

1) Create table salary(empid integer,salary integer) partition by range(salary)

(partition part1 values less than 20000,partition part2 values(maxvalue));

2) Create table Country(pname varchar(10),country-name varchar(10)) partition by list(country-name)

(partition part1 values (‘UK’ ‘US’),partition part2 values(‘INDIA’));

Documents

©Silberschatz, Korth and Sudarshan14.1Database System Concepts - 6 th Edition UNIT 5 :Transactions Transaction concepts, properties of transactions, serializability