Briefly explain concurrency control with locking methods

Concurrency control and locking is the mechanism used by DBMSs for the sharing of data. Atomicity, consistency, and isolation are achieved through concurrency control and locking. See ACID Properties.

When many people may be reading the same data item at the same time, it is usually necessary to ensure that only one application at a time can change a data item. Locking is a way to do this. Because of locking, all changes to a particular data item will be made in the correct order in a transaction. See isolation. 

The amount of data that can be locked with the single instance or groups of instances defines the granularity of the lock. The types of granularity are illustrated here are:

Additional information on this subject along with examples of multi-user considerations can be found in the Object Database Handbook.

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In a multiprogramming environment where multiple transactions can be executed simultaneously, it is highly important to control the concurrency of transactions. We have concurrency control protocols to ensure atomicity, isolation, and serializability of concurrent transactions. Concurrency control protocols can be broadly divided into two categories −

• Lock based protocols
• Time stamp based protocols

Lock-based Protocols

Database systems equipped with lock-based protocols use a mechanism by which any transaction cannot read or write data until it acquires an appropriate lock on it. Locks are of two kinds −

• Binary Locks − A lock on a data item can be in two states; it is either locked or unlocked.

• Shared/exclusive − This type of locking mechanism differentiates the locks based on their uses. If a lock is acquired on a data item to perform a write operation, it is an exclusive lock. Allowing more than one transaction to write on the same data item would lead the database into an inconsistent state. Read locks are shared because no data value is being changed.

There are four types of lock protocols available −

Simplistic Lock Protocol

Simplistic lock-based protocols allow transactions to obtain a lock on every object before a 'write' operation is performed. Transactions may unlock the data item after completing the ‘write’ operation.

Pre-claiming Lock Protocol

Pre-claiming protocols evaluate their operations and create a list of data items on which they need locks. Before initiating an execution, the transaction requests the system for all the locks it needs beforehand. If all the locks are granted, the transaction executes and releases all the locks when all its operations are over. If all the locks are not granted, the transaction rolls back and waits until all the locks are granted.

Two-Phase Locking 2PL

This locking protocol divides the execution phase of a transaction into three parts. In the first part, when the transaction starts executing, it seeks permission for the locks it requires. The second part is where the transaction acquires all the locks. As soon as the transaction releases its first lock, the third phase starts. In this phase, the transaction cannot demand any new locks; it only releases the acquired locks.

Two-phase locking has two phases, one is growing, where all the locks are being acquired by the transaction; and the second phase is shrinking, where the locks held by the transaction are being released.

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

Strict Two-Phase Locking

The first phase of Strict-2PL is same as 2PL. After acquiring all the locks in the first phase, the transaction continues to execute normally. But in contrast to 2PL, Strict-2PL does not release a lock after using it. Strict-2PL holds all the locks until the commit point and releases all the locks at a time.

Strict-2PL does not have cascading abort as 2PL does.

Timestamp-based Protocols

The most commonly used concurrency protocol is the timestamp based protocol. This protocol uses either system time or logical counter as a timestamp.

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

Every transaction has a timestamp associated with it, and the ordering is determined by the age of the transaction. A transaction created at 0002 clock time would be older than all other transactions that come after it. For example, any transaction 'y' entering the system at 0004 is two seconds younger and the priority would be given to the older one.

In addition, every data item is given the latest read and write-timestamp. This lets the system know when the last ‘read and write’ operation was performed on the data item.

Timestamp Ordering Protocol

The timestamp-ordering protocol ensures serializability among transactions 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.

• The timestamp 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 follows −

• If a transaction Ti issues a read(X) operation −

• If TS(Ti) < W-timestamp(X)
• If TS(Ti) >= W-timestamp(X)
• All data-item timestamps updated.

• If a transaction Ti issues a write(X) operation −

• If TS(Ti) < R-timestamp(X)
• If TS(Ti) < W-timestamp(X)
• Operation rejected and Ti rolled back.
• Otherwise, operation executed.

Thomas' Write Rule

This rule states if TS(Ti) < W-timestamp(X), then the operation is rejected and Ti is rolled back.

Time-stamp ordering rules can be modified to make the schedule view serializable.

Instead of making Ti rolled back, the 'write' operation itself is ignored.

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Concurrency control is provided in a database to:

• (i) enforce isolation among transactions.
• (ii) preserve database consistency through consistency preserving execution of transactions.
• (iii) resolve read-write and write-read conflicts.

Various concurrency control techniques are:

These are briefly explained below. 1. Two-Phase Locking Protocol: Locking is an operation which secures: permission to read, OR permission to write a data item. Two phase locking is a process used to gain ownership of shared resources without creating the possibility of deadlock. The 3 activities taking place in the two phase update algorithm are:

Two phase locking prevents deadlock from occurring in distributed systems by releasing all the resources it has acquired, if it is not possible to acquire all the resources required without waiting for another process to finish using a lock. This means that no process is ever in a state where it is holding some shared resources, and waiting for another process to release a shared resource which it requires. This means that deadlock cannot occur due to resource contention. A transaction in the Two Phase Locking Protocol can assume one of the 2 phases:

• (i) Growing Phase: In this phase a transaction can only acquire locks but cannot release any lock. The point when a transaction acquires all the locks it needs is called the Lock Point.
• (ii) Shrinking Phase: In this phase a transaction can only release locks but cannot acquire any.

2. Time Stamp Ordering Protocol: A timestamp is a tag that can be attached to any transaction or any data item, which denotes a specific time on which the transaction or the data item had been used in any way. A timestamp can be implemented in 2 ways. One is to directly assign the current value of the clock to the transaction or data item. The other is to attach the value of a logical counter that keeps increment as new timestamps are required. The timestamp of a data item can be of 2 types:

• (i) W-timestamp(X): This means the latest time when the data item X has been written into.
• (ii) R-timestamp(X): This means the latest time when the data item X has been read from. These 2 timestamps are updated each time a successful read/write operation is performed on the data item X.

3. Multiversion Concurrency Control: Multiversion schemes keep old versions of data item to increase concurrency. Multiversion 2 phase locking: Each successful write results in the creation of a new version of the data item written. Timestamps are used to label the versions. When a read(X) operation is issued, select an appropriate version of X based on the timestamp of the transaction. 4. Validation Concurrency Control: The optimistic approach is based on the assumption that the majority of the database operations do not conflict. The optimistic approach requires neither locking nor time stamping techniques. Instead, a transaction is executed without restrictions until it is committed. Using an optimistic approach, each transaction moves through 2 or 3 phases, referred to as read, validation and write.

• (i) During read phase, the transaction reads the database, executes the needed computations and makes the updates to a private copy of  the database values. All update operations of the transactions are recorded in a temporary update file, which is not accessed by the remaining transactions.
• (ii) During the validation phase, the transaction is validated to ensure that the changes made will not affect the integrity and consistency of the database. If the validation test is positive, the transaction goes to a write phase. If the validation test is negative, he transaction is restarted and the changes are discarded.
• (iii) During the write phase, the changes are permanently applied to the database.