The main goal of concurrency control is to ensure that transactions execute in an isolated manner and that their results are consistent with the order in which they were executed. The following are some of the most common concurrency control techniques used in DBMS:
- Locking: Locking is a technique that restricts access to a shared resource such as a data item or a database object to only one transaction at a time. Locks are acquired before a transaction performs a write operation and are released after the operation is completed. The two most common types of locks are shared locks and exclusive locks. Shared locks allow multiple transactions to read a shared resource simultaneously, while exclusive locks only allow one transaction to access the resource at a time.
- Timestamp ordering: Timestamp ordering is a technique that assigns a unique timestamp to each transaction as it enters the system. Transactions are then ordered based on their timestamps, and conflicts are resolved based on the order in which the transactions were executed. This technique ensures that transactions are executed in a consistent and correct order.
- Optimistic concurrency control: Optimistic concurrency control is a technique that assumes that conflicts between transactions are rare. In this approach, each transaction reads the database and records a version number for each data item. If two transactions try to write to the same data item, only one transaction can succeed, and the other transaction is rolled back.
- Multi-version concurrency control (MVCC): MVCC is a technique that allows multiple versions of the same data item to exist simultaneously. When a transaction reads a data item, it reads the version of the data item that was valid at the time the transaction started. If a transaction tries to write to a data item, a new version of the data item is created, and the transaction writes to the new version.
In conclusion, concurrency control is an important aspect of DBMS that ensures the correct and consistent execution of multiple transactions simultaneously. The most common techniques used for concurrency control include locking, timestamp ordering, optimistic concurrency control, and MVCC. Each of these techniques has its own strengths and weaknesses, and the choice of technique depends on the specific requirements of the application and the characteristics of the database system.
Lock-based Protocols
There are two main types of locks used in lock-based protocols:
- Shared locks: A shared lock is used to restrict access to a shared resource to read-only operations. Multiple transactions can hold shared locks on the same resource simultaneously. Shared locks allow transactions to read a shared resource without interfering with other transactions.
- Exclusive locks: An exclusive lock is used to restrict access to a shared resource to a single transaction for write operations. Only one transaction can hold an exclusive lock on a resource at a time. Exclusive locks ensure that transactions do not interfere with each other when performing write operations on the same resource.
Lock-based protocols use a set of rules to ensure that locks are acquired and released in a correct and consistent manner. These rules include the following:
- Two-phase locking: In two-phase locking, transactions must acquire all necessary locks before performing any write operations. Transactions are not allowed to release any locks until they have either committed or aborted. Two-phase locking ensures that transactions do not interfere with each other during execution.
- Deadlock prevention: Deadlocks occur when two or more transactions are waiting for each other to release a lock, causing them to enter a circular waiting state. Lock-based protocols use various techniques to prevent deadlocks, such as timeout mechanisms, lock ordering, and deadlock detection.
- Cascading rollback prevention: Cascading rollback occurs when a transaction is rolled back, causing other transactions that depend on it to also be rolled back. Lock-based protocols prevent cascading rollback by ensuring that transactions release all locks before they are rolled back.
Lock-based protocols are widely used in DBMS because they are simple and effective. However, they also have some disadvantages, such as the possibility of deadlocks and the potential for performance degradation due to lock contention. Therefore, it is important to carefully consider the specific requirements of the application and the characteristics of the database system before choosing a lock-based protocol.
Timestamp-based Protocols
There are two main types of timestamp-based protocols:
- Timestamp ordering: In timestamp ordering, transactions are ordered based on their timestamps. If transaction T1 has a lower timestamp than transaction T2, then T1 is executed before T2. If two transactions have the same timestamp, then conflict resolution rules are used to determine the order of execution.
- Thomas’ Write Rule: Thomas’ Write Rule is an extension of timestamp ordering that allows a transaction to write to a data item only if the transaction’s timestamp is greater than the timestamp of the last transaction that wrote to the same data item. This ensures that a transaction writes to a data item only if it has the most recent version of the data item.
Timestamp-based protocols have several advantages over lock-based protocols. They are non-blocking, which means that transactions do not need to wait for locks to be released before executing. They are also efficient and do not require the overhead of acquiring and releasing locks. However, they are more complex than lock-based protocols and require careful implementation to ensure correctness.
One disadvantage of timestamp-based protocols is that they can lead to the creation of cascading rollbacks. If a transaction is rolled back, then all transactions with a higher timestamp must also be rolled back. This can lead to a large number of transactions being rolled back, which can negatively impact performance.
In conclusion, timestamp-based protocols are an important type of concurrency control mechanism used in DBMS to ensure data consistency and correctness when multiple transactions are executed concurrently. They have several advantages over lock-based protocols, but they also have some disadvantages. The choice of protocol depends on the specific requirements of the application and the characteristics of the database system.
Timestamp Ordering Protocol
When a transaction enters the system, it is assigned a unique timestamp. The timestamp can be a simple integer value or a more complex value that includes information such as the transaction’s start time and a unique transaction identifier. The timestamp reflects the order in which the transaction entered the system.
Transactions are then executed based on their timestamps. If transaction T1 has a lower timestamp than transaction T2, then T1 is executed before T2. If two transactions have the same timestamp, then conflict resolution rules are used to determine the order of execution.
The timestamp ordering protocol uses two conflict resolution rules:
- Read-Write Conflicts: If a transaction T1 reads a data item that was written by a transaction T2, then T1 must wait until T2 has committed or aborted before continuing.
- Write-Write Conflicts: If a transaction T1 writes to a data item that was previously written by a transaction T2, then T1 must wait until T2 has committed or aborted before continuing.
In both cases, the transaction with the lower timestamp must wait until the transaction with the higher timestamp has finished executing. This ensures that the transactions are executed in the correct order, and data consistency is maintained.
One advantage of the timestamp ordering protocol is that it is non-blocking, which means that transactions do not need to wait for locks to be released before executing. This can improve performance in high-concurrency environments. However, the protocol requires careful implementation to ensure correctness. In particular, it must handle situations where transactions have the same timestamp or where transactions are rolled back.
In conclusion, the timestamp ordering protocol is an important type of concurrency control mechanism used in DBMS to ensure data consistency and correctness when multiple transactions are executed concurrently. It is efficient and non-blocking, but it requires careful implementation to ensure correctness. The choice of protocol depends on the specific requirements of the application and the characteristics of the database system.
