Explore how different transaction isolation levels affect concurrency phenomena using specific scenarios.
In database systems, isolation is one of the ACID (Atomicity, Consistency, Isolation, Durability) transaction properties. It determines how transaction integrity is visible to other users and systems. A lower isolation level increases the ability of many users to access the same data at the same time, but also increases the number of concurrency effects (such as dirty reads or lost updates) users might encounter. Conversely, a higher isolation level reduces the types of concurrency effects that users may encounter, but requires more system resources and increases the chances that one transaction will block another.
Concurrency control comprises the underlying mechanisms in a DBMS which handle isolation and guarantee related correctness. It is heavily used by the database and storage engines both to guarantee the correct execution of concurrent transactions, and (via different mechanisms) the correctness of other DBMS processes. The transaction-related mechanisms typically constrain the database data access operations' timing (transaction schedules) to certain orders characterized as serializability and recoverability schedule properties. Constraining database access operation execution typically means reduced performance (measured by rates of execution), and thus concurrency control mechanisms are typically designed to provide the best performance possible under the constraints. Often, when possible without harming correctness, the serializability property is compromised for better performance. However, recoverability cannot be compromised, since such typically results in a database integrity violation.
Two-phase locking (2PL) is the most common transaction concurrency control method in DBMSs, used to provide both serializability and recoverability for correctness. In order to access a database object, a transaction first needs to acquire a lock for this object. Depending on the access operation type (e.g., reading or writing an object) and on the lock type, acquiring the lock may be blocked and postponed if another transaction is holding a lock for that object.
Isolation is typically enforced at the database level. However, various client-side systems can also be used. It can be controlled in application frameworks or runtime containers such as J2EE Entity Beans. On older systems, it may be implemented systemically (by the application developers), for example through the use of temporary tables. In two-tier, three-tier, or n-tier web applications a transaction manager can be used to maintain isolation. A transaction manager is middleware which sits between an app service (back-end application service) and the operating system. A transaction manager can provide global isolation and atomicity. It tracks when new servers join a transaction and coordinates an atomic commit protocol among the servers. The details are abstracted from the app, making transactions simpler and easier to code. A transaction processing monitor (TPM) is a collection of middleware including a transaction manager. A TPM might provide local isolation to an app with a lock manager.
Reference : Wikipedia - Isolation (database systems)
| Isolation Level | Dirty Read | Non-Repeatable Read | Phantom Read |
|---|---|---|---|
| Read Uncommitted | ❌ Allowed | ❌ Allowed | ❌ Allowed |
| Read Committed | ✅ Prevented | ❌ Allowed | ❌ Allowed |
| Repeatable Read | ✅ Prevented | ✅ Prevented | ❌ Allowed* |
| Serializable | ✅ Prevented | ✅ Prevented | ✅ Prevented |
*Standard SQL allows Phantom Reads in Repeatable Read, though some databases prevent them via specific implementations (e.g., locking).
Select a scenario and isolation level, then click 'Reset'. Use 'Step Forward' to execute operations.