Ensuring Data Consistency: Transaction Processing Mechanism of Doris Database

# 1. The Importance of Data Consistency: Doris Database's Transaction Processing Mechanism

Data consistency is a crucial concept in database systems, ensuring the accuracy and integrity of data within a database. Data consistency demands that the data within a database is always in a valid state and adheres to expected business rules. Without data consistency, there may be data corruption, loss, or inaccuracies, which can severely impact business operations.

Data consistency is essential for the following aspects:

- **Data Integrity:** Ensures that data within the database is accurate and adheres to business rules and constraints.
- **Data Reliability:** Guarantees that data will not be lost or corrupted due to accidental events (such as hardware failures or software errors).
- **Data Availability:** Ensures users can access accurate and up-to-date data at any time.

# 2. Fundamental Principles of Transaction Processing

### 2.1 ACID Properties of Transactions

The ACID properties of transaction processing are the fundamental principles of transaction management in database management systems (DBMS), ensuring the reliability and consistency of database operations. ACID properties include:

- **Atomicity:** A transaction is an indivisible unit that either completely succeeds or fails entirely.
- **Consistency:** The database must be in a consistent state before and after the transaction, meaning it satisfies all business rules and constraints.
- **Isolation:** Concurrent transactions are independent of each other and do not affect one another.
- **Durability:** Once a transaction is committed successfully, its changes to the database are permanently saved, even if a system failure occurs.

### 2.2 Isolation Levels of Transactions

Isolation levels define the degree of visibility between concurrent transactions, ***mon isolation levels include:

- **Read Uncommitted:** Transactions can read data from other transactions that have not yet been committed, potentially leading to dirty reads.
- **Read Committed:** Transactions can only read data from other transactions that have been committed, avoiding dirty reads.
- **Repeatable Read:** Transactions can read the same data multiple times during execution, and the result will be consistent each time, avoiding phantom reads.
- **Serializable:** The order of transaction execution is the same as if they were executed serially, completely avoiding concurrency issues.

**Code Block:**

# Set transaction isolation level to Repeatable Read
session.set_isolation_level(IsolationLevel.REPEATABLE_READ)

**Logical Analysis:**

The `set_isolation_level()` method is used to set the isolation level of a transaction. `REPEATABLE_READ` indicates that a transaction can read the same data multiple times during execution, and the result will be consistent each time.

**Parameter Description:**

- `IsolationLevel.REPEATABLE_READ`: Repeatable Read isolation level.

### 2.3 Concurrency Control Mechanisms of Transactions

Concurrency control mechanisms are used to manage the interaction between concurrent transactions, ***mon concurrency control mechanisms include:

- **Locking Mechanism:** Prevents other transactions from modifying a data object by locking it.
- **Optimistic Concurrency Control (OCC):** Does not use locks but solves concurrency issues through version control and conflict detection.
- **Multiversion Concurrency Control (MVCC):** Maintains multiple versions of a data object, allowing concurrent transactions to read different versions of the data.

**Table:**

| Concurrency Control Mechanism | Advantages | Disadvantages |
|---|---|---|
| Locking Mechanism | Ensures data consistency | May lead to deadlocks |
| OCC | High performance | May lead to dirty writes |
| MVCC | High performance, avoids deadlocks | Implementation complexity, high space overhead |

**Flowchart:**

graph LR
subgraph Locking Mechanism
     A[Acquire Lock] --> B[Modify Data]
     B[Release Lock] --> C[Commit Transaction]
end
subgraph OCC
     A[Read Data] --> B[Modify Data]
     B[Commit Transaction] --> C[Detect Conflicts]
     C[Conflict] --> D[Rollback Transaction]
     C[No Con