Concurrency Control 편집하기

'''Concurrency Control''' is a mechanism in database management systems (DBMS) that ensures correct and consistent transaction execution in a multi-user environment. It prevents issues such as data inconsistencies and anomalies by managing simultaneous access to the database.
==Key Concepts==
*'''Transaction:''' A sequence of database operations that are executed as a single logical unit of work.
*'''Isolation:''' Ensures that each transaction is executed independently without interference.
*'''Consistency:''' Guarantees that the database remains in a consistent state after a transaction, even in the presence of concurrent transactions.
==Problems Addressed by Concurrency Control==
Concurrency control mechanisms resolve the following issues:
*'''Dirty Reads:''' A transaction reads uncommitted changes made by another transaction.
*'''Non-Repeatable Reads:''' A transaction reads the same data twice and gets different results due to concurrent updates.
*'''Phantom Reads:''' A transaction sees a different set of rows in repeated queries due to concurrent inserts or deletes.
*'''Lost Updates:''' Two transactions simultaneously update the same data, and one update overwrites the other.
*'''Write Skew:''' Concurrent updates create an inconsistent database state.
==Techniques for Concurrency Control==
The following techniques are commonly used for concurrency control:
{| class="wikitable"
!Technique!!Description!!Advantages!!Limitations
|-
|'''Lock-Based Protocols'''||Transactions acquire locks on data items to control access.||Prevents conflicts, widely used.||Can lead to deadlocks, reduced concurrency.
|-
|'''Timestamp-Based Protocols'''||Assigns timestamps to transactions to enforce serializability.||No locks, avoids deadlocks.||Requires global timestamp management.
|-
|'''Optimistic Concurrency Control'''||Validates transactions at commit time to ensure no conflicts.||High performance in low-contention systems.||Rollbacks can be expensive in high-contention systems.
|-
|'''Multiversion Concurrency Control (MVCC)'''||Maintains multiple versions of data to provide consistent snapshots.||Supports high concurrency, avoids read-write conflicts.||Storage overhead due to multiple versions.
|}
==Example: Lock-Based Protocol==
Consider two transactions accessing the same account balance:
*'''Transaction A'''
  * Reads account balance.
  * Deducts $100.
  * Updates the balance.
*'''Transaction B'''
  * Reads account balance.
  * Adds $50.
  * Updates the balance.
Without locking, these transactions could overwrite each other's updates. Using locks: 

# Transaction A acquires a write lock on the balance. 
# Transaction B waits until Transaction A releases the lock. 
# Transaction A updates the balance and releases the lock. 
# Transaction B acquires the lock, reads the updated balance, and applies its changes.

==Deadlock Handling==
Lock-based protocols can lead to deadlocks, where two or more transactions wait indefinitely for each other to release locks. Common deadlock handling techniques include:
*'''Timeouts:''' Abort transactions that wait too long.
*'''Deadlock Detection:''' Use wait-for graphs to identify and resolve deadlocks.
*'''Deadlock Prevention:''' Ensure transactions acquire locks in a predefined order.
==Applications of Concurrency Control==
Concurrency control is essential in:
*'''Banking Systems:''' Preventing anomalies in financial transactions.
*'''E-Commerce:''' Ensuring consistency in inventory and orders.
*'''Distributed Databases:''' Managing consistency across multiple nodes.
*'''Real-Time Systems:''' Providing low-latency, conflict-free operations.
==See Also==
*[[Transaction Management]]
*[[Isolation Level (Database)|Isolation Level]]
*[[Lock-Based Protocols]]
*[[Timestamp-Based Protocols]]
*[[Multiversion Concurrency Control]]
*[[Deadlock Detection]]
*[[Database Anomalies]]
[[Category:Database]]
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