Concurrency Control in Database Management Systems: Techniques and Best Practices

Posted on Apr 29, 2024 in Computers

Concurrency Control in Database Management Systems

Introduction

Concurrency control is the process of managing the simultaneous execution of transactions in a shared database to ensure data integrity and consistency. This is crucial to prevent issues like lost updates, uncommitted data, and inconsistent retrievals.

Why Concurrency Control is Needed

Simultaneous execution of transactions can lead to several data integrity and consistency problems, including:

  • Lost Updates: When two transactions try to update the same data simultaneously, one update may overwrite the other, leading to data loss.
  • Uncommitted Data: If a transaction reads data from another transaction that has not yet committed, it may read inconsistent or invalid data.
  • Inconsistent Retrievals: If a transaction reads data from multiple tables, and another transaction updates some of those tables while the first transaction is still reading, the first transaction may retrieve inconsistent data.

Concurrency Control Techniques

There are two main concurrency control techniques:

1. Pessimistic Concurrency Control (Locking)

Pessimistic concurrency control assumes that conflicts are likely to occur and uses locking to prevent them. A lock is a mechanism that prevents other transactions from accessing a data item while it is being used by another transaction.

Advantages of Locking:

  • Ensures data integrity and consistency.
  • Simple to implement.

Disadvantages of Locking:

  • Can lead to performance bottlenecks if locks are held for too long.
  • Can cause deadlocks, where two or more transactions are waiting for each other to release locks.

2. Optimistic Concurrency Control

Optimistic concurrency control assumes that conflicts are rare and allows transactions to proceed without locking data items. Instead, it checks for conflicts just before a transaction commits. If a conflict is detected, the transaction is rolled back and restarted.

Advantages of Optimistic Concurrency Control:

  • Can improve performance by reducing the need for locking.
  • Avoids deadlocks.

Disadvantages of Optimistic Concurrency Control:

  • Can lead to wasted work if transactions are frequently rolled back.
  • More complex to implement than locking.

Optimistic Concurrency Control Phases

Optimistic concurrency control typically involves three phases:

  1. Read Phase: Transactions read data without locking.
  2. Validation Phase: Before committing, transactions check for conflicts with other transactions.
  3. Write Phase: If no conflicts are found, transactions write their changes to the database.

Validation Techniques

Several validation techniques can be used in optimistic concurrency control, such as:

  • Timestamp Ordering: Each transaction is assigned a timestamp, and transactions are executed in timestamp order.
  • Validation by Serialization Graph: A graph is used to track the dependencies between transactions, and conflicts are detected if the graph contains cycles.

Back and Restore Strategy

A robust backup and restore strategy is essential for recovering from data loss or corruption. Factors to consider when developing a backup strategy include:

  • Frequency of backups
  • Types of backups (full, differential, log)
  • Storage location for backups
  • Recovery time objectives

SQL and Stored Procedures

SQL is the standard language for interacting with relational databases. Stored procedures are precompiled collections of SQL statements that can be executed on demand. They offer several benefits, including:

  • Improved performance
  • Code reusability
  • Security

Triggers

Triggers are special stored procedures that are automatically executed in response to specific events, such as INSERT, UPDATE, or DELETE operations on a table. They can be used for various purposes, such as enforcing data integrity, maintaining audit logs, and implementing complex business rules.

Conclusion

Concurrency control is a critical aspect of database management systems. Choosing the right concurrency control technique and implementing a robust backup and restore strategy are essential for ensuring data integrity, consistency, and availability.