Understanding Database Transactions and Data Consistency
Database Transactions and Data Consistency
Transaction Issues
Lost Updates
When two transactions access the same database and their operations are interleaved, it can result in incorrect data. For example, if User1 reads value X, then User2 reads X, User1 updates X, and finally User2 updates X, User1’s update is lost.
Temporary Updates
If a transaction updates a database item and then fails, the updated item might be accessed by other transactions before it’s reverted to its original value.
Incorrect Summary
When a transaction calculates an aggregate function on records while other transactions are updating those records, the aggregate function might include outdated values.
ACID Properties of Transactions
ACID properties ensure reliable database transactions:
- Atomicity: Each transaction is treated as a single unit; it either completes entirely or fails entirely, leaving the database unchanged.
- Consistency: A successful transaction must take the database from one valid state to another, adhering to all defined rules and constraints.
- Isolation: Each transaction is isolated from others, as if it were running alone. This prevents issues like temporary updates.
- Durability: Once a transaction is committed, its changes are permanent and will persist even in case of power loss or system crashes.
Transaction Isolation Levels
- Read Uncommitted: Allows reading uncommitted data, leading to dirty reads.
- Read Committed: Prevents dirty reads but allows non-repeatable reads and phantom reads.
- Repeatable Read: Ensures consistent reads within a transaction but may still allow phantom reads.
- Snapshot: Provides a consistent view of data as of the transaction’s start time.
- Serializable: The highest isolation level, preventing all concurrency issues.
Database Triggers
Triggers are database objects that automatically execute in response to specific events (e.g., INSERT, UPDATE, DELETE). They consist of three components:
- Event: The action that activates the trigger.
- Condition (optional): A test to determine if the trigger should run.
- Action: The code executed when the trigger fires.
SQL Cursors
Cursors allow you to iterate over a result set row by row. They are useful for tasks that require sequential processing of data.
Impedance Mismatch
The impedance mismatch problem arises when mapping relational data to object-oriented models. Cursors can help bridge this gap by providing sequential access to data.
Stored Procedures and User-Defined Functions
Stored procedures and user-defined functions offer more flexibility and efficiency for complex database operations. However, they also introduce potential security risks and require careful implementation.
XPath for Semi-Structured Data
XPath is a query language for navigating and selecting nodes in XML documents. It’s a powerful tool for working with semi-structured data, which may have irregular or incomplete structure.
Semi-Structured Data
Semi-structured data offers flexibility for data exchange and integration, allowing information from diverse sources to be combined easily.