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Database Management System
What is mean by schedule in DBMS?
In the context of DBMS (Database Management System), a schedule refers to the chronological order or sequence of operations or transactions in a database. It specifies the order in which the operations are executed and the timing of their execution. A schedule determines how concurrent transactions are interleaved and executed in the system.
A schedule can be represented as a series of actions, such as read and write operations, performed by multiple transactions in the database. It outlines the timeline of these actions and their dependencies. Each action in a schedule is associated with a specific transaction and an item (such as a database object) on which the operation is performed.
Schedules play a crucial role in ensuring the consistency, integrity, and correctness of concurrent transactions in a multi-user database environment. They help maintain the ACID properties (Atomicity, Consistency, Isolation, and Durability) and govern the order in which transactions access and modify the database.
There are different types of schedules, including serial schedules, concurrent schedules, and conflict-serializable schedules. Serial schedules execute transactions in a sequential manner, one after another. Concurrent schedules involve the concurrent execution of multiple transactions. Conflict-serializable schedules ensure that concurrent transactions maintain serializability, meaning the final result is equivalent to some serial execution of the transactions.
Scheduling and concurrency control mechanisms are employed to ensure that transactions are executed in a way that maintains data integrity, prevents conflicts, and allows for efficient and parallel execution of transactions while avoiding anomalies or inconsistencies in the database.
What is write-read conflict?
A write-read conflict, also known as a write followed by a read conflict, is a type of data access conflict that occurs in concurrent execution of transactions or operations in a database system. It happens when one transaction writes data to a certain item (such as a database record) while another transaction reads the same item.
In a write-read conflict scenario:
Transaction A writes to an item: Transaction A performs a write operation that modifies the value of a specific item in the database.
Transaction B reads the same item: Concurrently, Transaction B performs a read operation on the same item, either before or after Transaction A’s write operation.
This write-read conflict creates a potential conflict between the two transactions because Transaction B’s read operation might not reflect the updated value written by Transaction A. The conflict arises from the fact that Transaction B may read the value from the item before Transaction A’s write operation takes effect, leading to inconsistencies or incorrect results.
To maintain data consistency and prevent anomalies caused by write-read conflicts, database systems employ concurrency control mechanisms. These mechanisms, such as locks, isolation levels, or optimistic concurrency control, ensure that conflicting operations are properly ordered, serialized, or coordinated to avoid conflicts and maintain the integrity of the data being accessed by multiple transactions.
What is read-write conflict?
A read-write conflict, also known as a read followed by a write conflict, is a type of data access conflict that occurs in concurrent execution of transactions or operations in a database system. It happens when one transaction reads data from a certain item (such as a database record) while another transaction writes to the same item.
In a read-write conflict scenario:
Transaction A reads the item: Transaction A performs a read operation to retrieve the value of a specific item from the database.
Transaction B writes to the same item: Concurrently, Transaction B performs a write operation that modifies the value of the same item, either before or after Transaction A’s read operation.
This read-write conflict creates a potential conflict between the two transactions because Transaction A’s read operation may not reflect the updated value written by Transaction B. The conflict arises from the fact that Transaction A may read the value from the item before or after Transaction B’s write operation, leading to inconsistencies or incorrect results.
To maintain data consistency and prevent anomalies caused by read-write conflicts, database systems employ concurrency control mechanisms. These mechanisms, such as locks, isolation levels, or optimistic concurrency control, ensure that conflicting operations are properly ordered, serialized, or coordinated to avoid conflicts and maintain the integrity of the data being accessed by multiple transactions.
Explain how we can achieve irrecoverable schedule?
An irrecoverable schedule refers to a situation where a transaction’s changes become permanently visible to other transactions before the committing transaction completes or in the event that the committing transaction fails. This leads to data inconsistencies and violates the durability property of ACID (Atomicity, Consistency, Isolation, Durability) transactions. Achieving an irrecoverable schedule can occur due to the absence of proper transaction control mechanisms. Here’s an explanation of how an irrecoverable schedule can arise:
Transaction T1 writes data: Transaction T1 begins and modifies data items within the database.
Transaction T2 reads the uncommitted data: Concurrently, Transaction T2 reads the data modified by Transaction T1, even though Transaction T1 has not yet committed its changes.
Transaction T1 rolls back or fails: Transaction T1 encounters an error, fails, or explicitly rolls back its changes, making them invalid.
Transaction T2 has read uncommitted data: Transaction T2 has already read and potentially utilized the uncommitted data from Transaction T1, which is now deemed invalid.
In this scenario, an irrecoverable schedule arises because Transaction T2 has read and potentially acted upon the uncommitted changes made by Transaction T1. If Transaction T1 fails or rolls back, there is no way to recover the impact of Transaction T2’s actions based on the invalid data.
To prevent an irrecoverable schedule and ensure data consistency, database systems implement transaction control mechanisms, such as isolation levels and concurrency control protocols. These mechanisms enforce proper transaction boundaries, isolation, and commit protocols to guarantee that transactions observe the ACID properties. By properly coordinating transactions, ensuring proper locking, and providing appropriate isolation levels, irrecoverable schedules can be avoided, and data integrity can be maintained.
Explain how cascading schedule creates a problem in performance.
A cascading schedule in a database refers to a situation where a single transaction failure or rollback triggers a series of subsequent rollbacks in dependent or related transactions. While cascading rollbacks ensure data consistency, they can create performance problems due to their impact on system resources and the overhead involved. Here’s how cascading schedules can affect performance:
Increased Rollback Overhead: Cascading rollbacks can lead to increased overhead in terms of system resources, processing time, and disk I/O. Each subsequent rollback requires the database system to undo the changes made by the rolled-back transactions, which can be time-consuming and resource-intensive.
Lock Contention: Cascading rollbacks may result in increased lock contention. When a transaction is rolled back, any locks acquired during the transaction need to be released. This release of locks can cause delays and contention with other transactions trying to acquire the same locks, impacting concurrency and overall system performance.
Transaction Reversal: Cascading rollbacks involve reversing the effects of multiple transactions, potentially affecting a large number of data items and records. This reversal process may require extensive disk I/O and data manipulation, which can lead to performance degradation, especially when dealing with large datasets.
Reduced Concurrency: Cascading rollbacks can reduce concurrency in the system. As dependent transactions are rolled back, other transactions that were waiting for resources or locks held by those transactions may also need to wait or be rolled back. This cascading effect can limit the parallelism and concurrency of transactions, impacting system throughput and response time.
Increased Recovery Time: Recovering from cascading rollbacks may take longer due to the need to undo multiple sets of changes. The system must ensure that the database is restored to a consistent state by undoing the changes made by the rolled-back transactions. This recovery process can lengthen the time required to restore the database and resume normal operation.
To mitigate the performance impact of cascading rollbacks, database systems employ techniques such as careful transaction design, proper use of transaction boundaries, efficient concurrency control mechanisms, and optimized recovery procedures. By minimizing cascading effects and optimizing the rollback and recovery processes, the performance impact of cascading schedules can be mitigated to a certain extent.
What is serializability?
Serializability is a concept in database management systems (DBMS) that ensures that the execution of concurrent transactions is equivalent to executing them in a serialized (sequential) manner. It guarantees that the final state of the database is the same as if the transactions had been executed one after another, in some sequential order.
In other words, serializability provides the illusion that the transactions are executed in isolation, even though they may be executed concurrently. It allows multiple transactions to execute concurrently while maintaining the same end result as if they were executed sequentially.
There are two main types of serializability:
Conflict Serializability: Conflict serializability ensures that the outcome of concurrent transactions is the same as if the transactions were executed in some serial order without any conflicts. Conflicts occur when two or more transactions access the same data item, and at least one of them performs a write operation. The conflicts are categorized as:
Read-Write (RW) conflict: A transaction reads data that is subsequently modified by another transaction.
Write-Read (WR) conflict: A transaction modifies data that is subsequently read by another transaction.
Write-Write (WW) conflict: Two transactions attempt to modify the same data item.
View Serializability: View serializability ensures that the outcome of concurrent transactions is the same as if the transactions were executed in some serial order without violating the visibility of data. The visibility of data refers to the values that transactions see during their execution. A view serializable schedule ensures that every transaction sees a consistent and valid snapshot of the database during its execution.
To achieve serializability, DBMS uses concurrency control mechanisms such as locking, timestamp ordering, optimistic concurrency control, or two-phase locking. These mechanisms manage access to data and ensure that conflicts are resolved or avoided, maintaining the ACID properties (Atomicity, Consistency, Isolation, Durability) of transactions and data integrity.
Serializability is essential in multi-user environments where multiple transactions are executed concurrently. It allows for efficient and parallel execution of transactions while preserving the consistency and correctness of the database.
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