Detailed Explanation of Database Transaction Isolation Levels

Topic Description:
Database transaction isolation levels are a crucial mechanism in Database Management Systems (DBMS) for controlling the degree of interaction between multiple concurrent transactions. They define how a transaction is isolated from other concurrent transactions when accessing data and what modifications from other transactions it is allowed to see. Different isolation levels represent trade-offs between data consistency and concurrency performance, addressing concurrency issues such as dirty reads, non-repeatable reads, and phantom reads.

Knowledge Explanation:

1. Potential Problems Caused by Concurrent Transactions

When multiple transactions execute simultaneously without proper isolation control, the following issues may arise:

• Dirty Read: A transaction reads data that has been modified by another uncommitted transaction. If that uncommitted transaction is later rolled back, the data read by the first transaction becomes invalid "dirty" data.

  • Example: Transaction A changes an account balance from 100 to 200 (not yet committed). At this point, Transaction B reads the balance and gets 200. Subsequently, Transaction A is rolled back, restoring the balance to 100. The 200 used by Transaction B is dirty data.

• Non-repeatable Read: Within the same transaction, multiple reads of the same piece of data yield inconsistent results. This usually occurs because another committed transaction modified the data between the two reads.

  • Example: Transaction A reads the account balance for the first time and gets 100. At this time, Transaction B commits a change, updating the balance to 150. Transaction A reads the balance again and gets 150. Two reads within the same transaction produced different results.

• Phantom Read: Within the same transaction, multiple queries based on the same conditions return inconsistent result set row counts. This typically happens because another committed transaction inserted or deleted records that satisfy the conditions between the two queries.

  • Example: Transaction A queries for employees under 30 years old and gets 10 records. At this time, Transaction B commits a new operation, inserting a record for a new 25-year-old employee. Transaction A queries again with the same conditions and gets 11 records. It's as if a "phantom" record appeared.

Key Difference: Non-repeatable reads concern the value of existing data being modified, while phantom reads concern the insertion or deletion of new data rows.

2. Standard Transaction Isolation Levels

To address the above problems, the SQL standard defines 4 isolation levels, listed from most lenient to most strict:

• Read Uncommitted: This is the lowest isolation level. It allows a transaction to read modifications made by another uncommitted transaction.

  • Problems Solved: None. It cannot prevent dirty reads, non-repeatable reads, or phantom reads.
  • Applicable Scenarios: Scenarios with extremely low data consistency requirements but pursuing the highest concurrency performance. Rarely used in practical applications.

• Read Committed: A transaction can only read modifications made by another committed transaction. This is the default level for many databases (e.g., Oracle, PostgreSQL).

  • Problems Solved: Dirty Read.
  • Problems Not Solved: Non-repeatable read, phantom read.

• Repeatable Read: Ensures that within the same transaction, multiple reads of the same data yield consistent results. Even if other transactions modify and commit that data, the current transaction sees a snapshot of the data as it was at the start of the transaction.

  • Problems Solved: Dirty Read, Non-repeatable Read.
  • Problems Not Solved: Phantom Read (though some databases like MySQL's InnoDB engine also solve phantom reads through concurrency control mechanisms).

• Serializable: This is the highest isolation level. It forces all transactions to execute serially, not concurrently. It ensures no concurrency problems occur through methods like locking.

  • Problems Solved: Dirty Read, Non-repeatable Read, Phantom Read. All concurrency problems are resolved.
  • Disadvantage: Worst concurrency performance, as most operations require locking, leading to many transactions waiting.

3. Implementation and Problem Comparison Table for Each Level

Different databases implement these levels in various ways, typically based on locking mechanisms or Multi-Version Concurrency Control (MVCC).

4. How to Choose an Isolation Level

Choosing an isolation level is a classic trade-off process:

• High data consistency requirements (e.g., financial trading systems): Should choose Repeatable Read or Serializable. Prioritize ensuring data accuracy.
• High concurrency performance requirements (e.g., highly concurrent web applications): Can choose Read Committed. Achieves better concurrency performance while guaranteeing no dirty reads.
• Avoid using Read Uncommitted unless there is a specific need, as it can cause severe data inconsistency.
• Use Serializable with caution, unless business logic strictly requires absolute isolation, because its performance overhead is the greatest and it can become a system bottleneck.

Summary:
Transaction isolation levels are the cornerstone of database concurrency control. Understanding the three core problems—dirty read, non-repeatable read, and phantom read—is key to distinguishing between different isolation levels. From "Read Uncommitted" to "Serializable," isolation gradually increases, and data consistency is better guaranteed, but this comes at the cost of sacrificing concurrency performance. In practical development, the most appropriate isolation level should be chosen based on specific business scenarios.