View Serializability

• A schedule will view serializable if it is viewed as equivalent to a serial schedule.
• If a schedule is conflict serializable, then it will be view serializable.
• The view serializable which does not conflict with serializable contains blind writes.

View Equivalent

Two schedules S1 and S2 are said to be view equivalent if they satisfy the following conditions:

1. Initial Read

An initial read of both schedules must be the same. Suppose two schedules S1 and S2. In schedule S1, if a transaction T1 is reading the data item A, then in S2, transaction T1 should also read A.

The above two schedules are view equivalent because the Initial read operation in S1 is done by T1 and in S2 it is also done by T1.

2. Updated Read

In schedule S1, if Ti is reading A which is updated by Tj then in S2 also, Ti should read A which is updated by Tj.

The above two schedules are not viewed equal because, in S1, T3 is reading A updated by T2 and in S2, T3 is reading A updated by T1.

3. Final Write

A final write must be the same between both schedules. In schedule S1, if a transaction T1 updates A at last then in S2, final writing operations should also be done by T1.

The above two schedules are view equal because the Final write operation in S1 is done by T3 and in S2, the final write operation is also done by T3.

Example:

Schedule S

With 3 transactions, the total number of possible schedule

1. = 3! = 6  
2. S1 = <T1 T2 T3>  
3. S2 = <T1 T3 T2>  
4. S3 = <T2 T3 T1>  
5. S4 = <T2 T1 T3>  
6. S5 = <T3 T1 T2>  
7. S6 = <T3 T2 T1>  

Taking first schedule S1:

Schedule S1

Step 1: final updation of data items

In both schedules S and S1, there is no read except the initial read that's why we don't need to check that condition.

Step 2: Initial Read

The initial read operation in S is done by T1 and in S1, it is also done by T1.

Step 3: Final Write

The final write operation in S is done by T3 and in S1, it is also done by T3. So, S and S1 are view Equivalent.

The first schedule S1 satisfies all three conditions, so we don't need to check another schedule.

Hence, view equivalent serial schedule is:

1. T1    →      T2    →    T3  

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Conflict Serializable Schedule

• A schedule is called conflict serializability if after swapping of non-conflicting operations, it can transform into a serial schedule.
• The schedule will be a conflict serializable if it is conflict equivalent to a serial schedule.

Conflicting Operations

The two operations become conflicting if all conditions satisfy:

1. Both belong to separate transactions.
2. They have the same data item.
3. They contain at least one write operation.

Example:

Swapping is possible only if S1 and S2 are logically equal.

Here, S1 = S2. That means it is non-conflict.

Here, S1 ≠ S2. That means it is conflict.

Conflict Equivalent

In the conflict equivalent, one can be transformed into another by swapping non-conflicting operations. In the given example, S2 is conflict equivalent to S1 (S1 can be converted to S2 by swapping non-conflicting operations).

Two schedules are said to be conflict equivalent if and only if:

1. They contain the same set of the transaction.
2. If each pair of conflict operations are ordered in the same way.

Example:

Schedule S2 is a serial schedule because, in this, all operations of T1 are performed before starting any operation of T2. Schedule S1 can be transformed into a serial schedule by swapping non-conflicting operations of S1.

After swapping of non-conflict operations, the schedule S1 becomes:

T1	T2
Read(A) Write(A) Read(B) Write(B)	Read(A) Write(A) Read(B) Write(B)

Since, S1 is conflict serializable.

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Testing of Serializability

SerializationA serialization Graph is used to test the Serializability of a schedule.

Assume a schedule S. For S, we construct a graph known as the precedence graph. This graph has a pair G = (V, E), where V consists of a set of vertices, and E consists of a set of edges. The set of vertices is used to contain all the transactions participating in the schedule. The set of edges is used to contain all edges Ti ->Tj for which one of the three conditions holds:

1. Create a node Ti → Tj if Ti executes write (Q) before Tj executes read (Q).
2. Create a node Ti → Tj if Ti executes read (Q) before Tj executes write (Q).
3. Create a node Ti → Tj if Ti executes write (Q) before Tj executes write (Q).

• If a precedence graph contains a single edge Ti → Tj, then all the instructions of Ti are executed before the first instruction of Tj is executed.
• If a precedence graph for schedule S contains a cycle, then S is non-serializable. If the precedence graph has no cycle, then S is known as serializable.

For example:

Explanation:

Read(A): In T1, no subsequent writes to A, so no new edges
Read(B): In T2, no subsequent writes to B, so no new edges
Read(C): In T3, no subsequent writes to C, so no new edges
Write(B): B is subsequently read by T3, so add edge T2 → T3
Write(C): C is subsequently read by T1, so add edge T3 → T1
Write(A): A is subsequently read by T2, so add edge T1 → T2
Write(A): In T2, no subsequent reads to A, so no new edges
Write(C): In T1, no subsequent reads to C, so no new edges
Write(B): In T3, no subsequent reads to B, so no new edges

Precedence graph for schedule S1:

The precedence graph for schedule S1 contains a cycle that's why Schedule S1 is non-serializable.

Explanation:

Read(A): In T4, no subsequent writes to A, so no new edges
Read(C): In T4, no subsequent writes to C, so no new edges
Write(A): A is subsequently read by T5, so add edge T4 → T5
Read(B): In T5, no subsequent writes to B, so no new edges
Write(C): C is subsequently read by T6, so add edge T4 → T6
Write(B): A is subsequently read by T6, so add edge T5 → T6
Write(C): In T6, no subsequent reads to C, so no new edges
Write(A): In T5, no subsequent reads to A, so no new edges
Write(B): In T6, no subsequent reads to B, so no new edges

Precedence graph for schedule S2:

The precedence graph for schedule S2 contains no cycle that's why ScheduleS2 is serializable.

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Schedule

A series of operations from one transaction to another transaction is known as a schedule. It is used to preserve the order of the operation in each individual transaction.

1. Serial Schedule

The serial schedule is a type of schedule where one transaction is executed completely before starting another transaction. In the serial schedule, when the first transaction completes its cycle, then the next transaction is executed.

For example: Suppose there are two transactions T1 and T2 that have some operations. If it has no interleaving of operations, then there are the following two possible outcomes:

1. Execute all the operations of T1 which was followed by all the operations of T2.
2. Execute all the operations of T1 which was followed by all the operations of T2.

• In the given (a) figure, Schedule A shows the serial schedule where T1 is followed by T2.
• In the given (b) figure, Schedule B shows the serial schedule where T2 is followed by T1.

2. Non-serial Schedule

• If interleaving of operations is allowed, then there will be a non-serial schedule.
• It contains many possible orders in which the system can execute the individual operations of the transactions.
• In the given figure (c) and (d), Schedule C and Schedule D are the non-serial schedules. It has interleaving of operations.

3. Serializable schedule

• The serializability of schedules is used to find non-serial schedules that allow the transaction to execute concurrently without interfering with one another.
• It identifies which schedules are correct when executions of the transaction have to interleave their operations.
• A non-serial schedule will be serializable if its result is equal to the result of its transactions executed serially.

Here,

Schedule A and Schedule B are serial schedules.

Schedule C and Schedule D are Non-serial schedules.

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States of Transaction

In a database, the transaction can be in one of the following states -

Active state

• The active state is the first state of every transaction. In this state, the transaction is being executed.
• For example, Insertion or deletion, or updating of a record is done here. But all the records are still not saved to the database.

Partially committed

• In the partially committed state, a transaction executes its final operation, but the data is still not saved to the database.
• In the total mark calculation example, a final display of the total marks step is executed in this state.

Committed

A transaction is said to be in a committed state if it executes all its operations successfully. In this state, all the effects are now permanently saved on the database system.

Failed state

• If any of the checks made by the database recovery system fails, then the transaction is said to be in the failed state.
• In the example of total mark calculation, if the database is not able to fire a query to fetch the marks, then the transaction will fail to execute.

Aborted

• If any of the checks fail and the transaction has reached a failed state then the database recovery system will make sure that the database is in its previous consistent state. If not then it will abort or roll back the transaction to bring the database into a consistent state.
• If the transaction fails in the middle of the transaction then before executing the transaction, all the executed transactions are rolled back to their consistent state.
• After aborting the transaction, the database recovery module will select one of the two operations:
1. Re-start the transaction
2. Kill the transaction

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Transaction property

The transaction has the four properties. These are used to maintain consistency in a database, before and after the transaction.

Property of Transaction

1. Atomicity
2. Consistency
3. Isolation
4. Durability

Atomicity

• It states that all operations of the transaction take place at once if not, the transaction is aborted.
• There is no midway, i.e., the transaction cannot occur partially. Each transaction is treated as one unit and either run to completion or is not executed at all.

Atomicity involves the following two operations:

Abort: If a transaction aborts then all the changes made are not visible.

Commit: If a transaction commits then all the changes made are visible.

Example: Let's assume that following transaction T consisting of T1 and T2. A consists of Rs 600 and B consists of Rs 300. Transfer Rs 100 from account A to account B.

T1	T2
Read(A) A:= A-100 Write(A)	Read(B) Y:= Y+100 Write(B)

After completion of the transaction, A consists of Rs 500 and B consists of Rs 400.

If the transaction T fails after the completion of transaction T1 but before completion of transaction T2, then the amount will be deducted from A but not added to B. This shows the inconsistent database state. In order to ensure correctness of database state, the transaction must be executed in entirety.

Consistency

• The integrity constraints are maintained so that the database is consistent before and after the transaction.
• The execution of a transaction will leave a database in either its prior stable state or a new stable state.
• The consistent property of database states that every transaction sees a consistent database instance.
• The transaction is used to transform the database from one consistent state to another consistent state.

For example: The total amount must be maintained before or after the transaction.

1. Total before T occurs = 600+300=900  
2. Total after T occurs= 500+400=900  

Therefore, the database is consistent. In the case when T1 is completed but T2 fails, then inconsistency will occur.

Isolation

• It shows that the data which is used at the time of execution of a transaction cannot be used by the second transaction until the first one is completed.
• In isolation, if the transaction T1 is being executed and using the data item X, then that data item can't be accessed by any other transaction T2 until the transaction T1 ends.
• The concurrency control subsystem of the DBMS enforced the isolation property.

Durability

• The durability property is used to indicate the performance of the database's consistent state. It states that the transaction made the permanent changes.
• They cannot be lost by the erroneous operation of a faulty transaction or by the system failure. When a transaction is completed, then the database reaches a state known as the consistent state. That consistent state cannot be lost, even in the event of a system's failure.
• The recovery subsystem of the DBMS has the responsibility of Durability property.

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Transaction

• The transaction is a set of logically related operations. It contains a group of tasks.
• A transaction is an action or series of actions. It is performed by a single user to perform operations for accessing the contents of the database.

Example: Suppose an employee of a bank transfers Rs 800 from X's account to Y's account. This small transaction contains several low-level tasks:

X's Account

1. Open_Account(X)  
2. Old_Balance = X.balance  
3. New_Balance = Old_Balance - 800  
4. X.balance = New_Balance  
5. Close_Account(X)  

Y's Account

1. Open_Account(Y)  
2. Old_Balance = Y.balance  
3. New_Balance = Old_Balance + 800  
4. Y.balance = New_Balance  
5. Close_Account(Y)  

Operations of Transaction:

Following are the main operations of transaction:

Read(X): Read operation is used to read the value of X from the database and store it in a buffer in the main memory.

Write(X): Write operation is used to write the value back to the database from the buffer.

Let's take an example of debit transaction from an account that consists of the following operations:

1. 1.  R(X);  
2. 2.  X = X - 500;  
3. 3.  W(X);  

Let's assume the value of X before starting o the transaction is 4000.

• The first operation reads X's value from the database and stores it in a buffer.
• The second operation will decrease the value of X by 500. So the buffer will contain 3500.
• The third operation will write the buffer's value to the database. So X's final value will be 3500.

But it may be possible that because of the failure of hardware, software or power, etc. that transaction may fail before finished all the operations in the set.

For example: If in the above transaction, the debit transaction fails after executing operation 2 then X's value will remain at 4000 in the database which is not acceptable by the bank.

To solve this problem, we have two important operations:

Commit: It is used to save the work done permanently.

Rollback: It is used to undo the work done.

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