Tag: Transactions

ACID Properties | ACID Properties in DBMS

Transaction in DBMS-

 

Before you go through this article, make sure that you have gone through the previous article on Transactions in DBMS.

 

We have discussed-

  • A transaction is a set of logically related operations.
  • A transaction goes through different states throughout its life cycle.
  • The life cycle of a transaction is-

 

 

In this article, we will discuss ACID properties of a transaction.

 

ACID Properties-

 

  • It is important to ensure that the database remains consistent before and after the transaction.
  • To ensure the consistency of database, certain properties are followed by all the transactions occurring in the system.
  • These properties are called as ACID Properties of a transaction.

 

 

1. Atomicity-

 

  • This property ensures that either the transaction occurs completely or it does not occur at all.
  • In other words, it ensures that no transaction occurs partially.
  • That is why, it is also referred to as “All or nothing rule“.
  • It is the responsibility of Transaction Control Manager to ensure atomicity of the transactions.

 

2. Consistency-

 

  • This property ensures that integrity constraints are maintained.
  • In other words, it ensures that the database remains consistent before and after the transaction.
  • It is the responsibility of DBMS and application programmer to ensure consistency of the database.

 

3. Isolation-

 

  • This property ensures that multiple transactions can occur simultaneously without causing any inconsistency.
  • During execution, each transaction feels as if it is getting executed alone in the system.
  • A transaction does not realize that there are other transactions as well getting executed parallely.
  • Changes made by a transaction becomes visible to other transactions only after they are written in the memory.
  • The resultant state of the system after executing all the transactions is same as the state that would be achieved if the transactions were executed serially one after the other.
  • It is the responsibility of concurrency control manager to ensure isolation for all the transactions.

 

4. Durability-

 

  • This property ensures that all the changes made by a transaction after its successful execution are written successfully to the disk.
  • It also ensures that these changes exist permanently and are never lost even if there occurs a failure of any kind.
  • It is the responsibility of recovery manager to ensure durability in the database.

 

Next Article- Concurrency Problems in DBMS

 

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Transaction States in DBMS

Transaction in DBMS-

 

“Transaction is a set of operations which are all logically related.”

OR

“Transaction is a single logical unit of work formed by a set of operations.”

 

Operations in Transaction-

 

The main operations in a transaction are-

  1. Read Operation
  2. Write Operation

 

1. Read Operation-

 

  • Read operation reads the data from the database and then stores it in the buffer in main memory.
  • For example- Read(A) instruction will read the value of A from the database and will store it in the buffer in main memory.

 

2. Write Operation-

 

  • Write operation writes the updated data value back to the database from the buffer.
  • For example- Write(A) will write the updated value of A from the buffer to the database.

 

Transaction States-

 

A transaction goes through many different states throughout its life cycle.

These states are called as transaction states.

Transaction states are as follows-

  1. Active state
  2. Partially committed state
  3. Committed state
  4. Failed state
  5. Aborted state
  6. Terminated state

 

 

1. Active State-

 

  • This is the first state in the life cycle of a transaction.
  • A transaction is called in an active state as long as its instructions are getting executed.
  • All the changes made by the transaction now are stored in the buffer in main memory.

 

2. Partially Committed State-

 

  • After the last instruction of transaction has executed, it enters into a partially committed state.
  • After entering this state, the transaction is considered to be partially committed.
  • It is not considered fully committed because all the changes made by the transaction are still stored in the buffer in main memory.

 

3. Committed State-

 

  • After all the changes made by the transaction have been successfully stored into the database, it enters into a committed state.
  • Now, the transaction is considered to be fully committed.

 

NOTE-

 

  • After a transaction has entered the committed state, it is not possible to roll back the transaction.
  • In other words, it is not possible to undo the changes that has been made by the transaction.
  • This is because the system is updated into a new consistent state.
  • The only way to undo the changes is by carrying out another transaction called as compensating transaction that performs the reverse operations.

 

4. Failed State-

 

  • When a transaction is getting executed in the active state or partially committed state and some failure occurs due to which it becomes impossible to continue the execution, it enters into a failed state.

 

5. Aborted State-

 

  • After the transaction has failed and entered into a failed state, all the changes made by it have to be undone.
  • To undo the changes made by the transaction, it becomes necessary to roll back the transaction.
  • After the transaction has rolled back completely, it enters into an aborted state.

 

6. Terminated State-

 

  • This is the last state in the life cycle of a transaction.
  • After entering the committed state or aborted state, the transaction finally enters into a terminated state where its life cycle finally comes to an end.

 

Next Article- ACID Properties of Transaction

 

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Concurrency Problems | DBMS

Transactions in DBMS-

 

Before you go through this article, make sure that you have gone through the previous article on Transactions in DBMS.

 

We have discussed-

  • A transaction is a set of logically related operations.
  • A transaction goes through different states throughout its life cycle.
  • ACID Properties are followed by each transaction to ensure the consistency of database.

 

In this article, we will discuss about concurrency problems of transactions.

 

Concurrency Problems in DBMS-

 

  • When multiple transactions execute concurrently in an uncontrolled or unrestricted manner, then it might lead to several problems.
  • Such problems are called as concurrency problems.

 

The concurrency problems are-

 

 

  1. Dirty Read Problem
  2. Unrepeatable Read Problem
  3. Lost Update Problem
  4. Phantom Read Problem

 

1. Dirty Read Problem-

 

Reading the data written by an uncommitted transaction is called as dirty read.

 

This read is called as dirty read because-

  • There is always a chance that the uncommitted transaction might roll back later.
  • Thus, uncommitted transaction might make other transactions read a value that does not even exist.
  • This leads to inconsistency of the database.

 

NOTE-

 

  • Dirty read does not lead to inconsistency always.
  • It becomes problematic only when the uncommitted transaction fails and roll backs later due to some reason.

 

Example-

 

 

Here,

  1. T1 reads the value of A.
  2. T1 updates the value of A in the buffer.
  3. T2 reads the value of A from the buffer.
  4. T2 writes the updated the value of A.
  5. T2 commits.
  6. T1 fails in later stages and rolls back.

 

In this example,

  • T2 reads the dirty value of A written by the uncommitted transaction T1.
  • T1 fails in later stages and roll backs.
  • Thus, the value that T2 read now stands to be incorrect.
  • Therefore, database becomes inconsistent.

 

2. Unrepeatable Read Problem-

 

This problem occurs when a transaction gets to read unrepeated i.e. different values of the same variable in its different read operations even when it has not updated its value.

 

Example-

 

 

Here,

  1. T1 reads the value of X (= 10 say).
  2. T2 reads the value of X (= 10).
  3. T1 updates the value of X (from 10 to 15 say) in the buffer.
  4. T2 again reads the value of X (but = 15).

 

In this example,

  • T2 gets to read a different value of X in its second reading.
  • T2 wonders how the value of X got changed because according to it, it is running in isolation.

 

3. Lost Update Problem-

 

This problem occurs when multiple transactions execute concurrently and updates from one or more transactions get lost.

 

Example-

 

 

Here,

  1. T1 reads the value of A (= 10 say).
  2. T2 updates the value to A (= 15 say) in the buffer.
  3. T2 does blind write A = 25 (write without read) in the buffer.
  4. T2 commits.
  5. When T1 commits, it writes A = 25 in the database.

 

In this example,

  • T1 writes the over written value of X in the database.
  • Thus, update from T1 gets lost.

 

NOTE-

 

  • This problem occurs whenever there is a write-write conflict.
  • In write-write conflict, there are two writes one by each transaction on the same data item without any read in the middle.

 

4. Phantom Read Problem-

 

This problem occurs when a transaction reads some variable from the buffer and when it reads the same variable later, it finds that the variable does not exist.

 

Example-

 

 

Here,

  1. T1 reads X.
  2. T2 reads X.
  3. T1 deletes X.
  4. T2 tries reading X but does not find it.

 

In this example,

  • T2 finds that there does not exist any variable X when it tries reading X again.
  • T2 wonders who deleted the variable X because according to it, it is running in isolation.

 

Avoiding Concurrency Problems-

 

  • To ensure consistency of the database, it is very important to prevent the occurrence of above problems.
  • Concurrency Control Protocols help to prevent the occurrence of above problems and maintain the consistency of the database.

 

Next Article- Schedules in DBMS

 

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