Enhancing Database Concurrency: The Concurrency Control Mechanism of Doris Database

# Enhancing Database Concurrency: Doris Database's Concurrency Control Mechanism

## 1. Overview of Database Concurrency Control

Database concurrency control is a critical technology in database management systems, aimed at managing and coordinating multiple users accessing and modifying data in a database simultaneously. It ensures data consistency, integrity, and isolation, preventing data errors and chaos from concurrent access.

Concurrency control mechanisms are implemented through locking and transaction mechanisms. Locking prevents other users from modifying or deleting data by locking data objects. Transactions ensure the correctness and integrity of database operations through the Atomicity, Consistency, Isolation, and Durability (ACID) properties.

## 2. Doris Database's Concurrency Control Mechanism

### 2.1 Doris Database's Locking Mechanism

#### 2.1.1 Optimistic and Pessimistic Locking

Optimistic and pessimistic locking are two different concurrency control mechanisms designed to solve potential data consistency issues when accessing data concurrently.

***Optimistic Locking:** Assumes that during concurrent access, data will not be modified by other transactions. It checks the data only when the transaction commits, and if the data is found to have been modified, the transaction is rolled back. The advantage of optimistic locking is high concurrency, but there is a risk of data inconsistency.
***Pessimistic Locking:** Assumes that during concurrent access, data might be modified by other transactions. It locks the data at the beginning of the transaction, preventing other transactions from modifying the data. The advantage of pessimistic locking is high data consistency, but it might reduce concurrency.

#### 2.1.2 Doris Database's Lock Types and Granularity

Doris database supports various lock types and granularities to meet different concurrency control needs.

**Lock Types:**

***Shared Lock (S-lock):** Allows other transactions to read data simultaneously but not modify it.
***Exclusive Lock (X-lock):** Does not allow other transactions to read or modify data simultaneously.

**Lock Granularity:**

***Table Lock:** Locks the entire table, offering the maximum granularity and lowest concurrency.
***Partition Lock:** Locks one or more partitions within a table, with smaller granularity and higher concurrency than table locks.
***Row Lock:** Locks specific rows within a table, offering the finest granularity and highest concurrency.

Doris database defaults to row locks to maximize concurrency.

### 2.2 Doris Database's Transaction Mechanism

#### 2.2.1 Transaction Characteristics and Isolation Levels

A transaction is a set of atomic operations in a database that either succeed entirely or fail entirely. Transactions have the following characteristics:

***Atomicity:** All operations within a transaction must either all succeed or all fail.
***Consistency:** After a transaction executes, the database must be in a consistent state.
***Isolation:** Concurrently executed transactions are independent of each other and do not affect each other.
***Durability:** Once a transaction is committed, its modifications to the database are permanently saved.

Doris database supports various isolation levels to meet different data consistency needs:

***Read Uncommitted (READ UNCOMMITTED):** A transaction can read data that other transactions have not yet committed, with the lowest data consistency.
***Read Committed (READ COMMITTED):** A transaction can only read data that other transactions have committed, with higher data consistency.
***Repeatable Read (REPEATABLE READ):** During a transaction's execution, other transactions cannot modify the data the transaction reads, with the highest data consistency.
***Serializable (SERIALIZABLE):** The execution order of transactions is the same as if they were executed serially, with the highest data consistency but lowest concurrency.

#### 2.2.2 Doris Database's Transaction Implementation

Doris database utilizes the Multiversion Concurrency Control (MVCC) mechanism to implement transactions. MVCC solves potential data consistency issues during concurrent data access by maintaining historical versions of data.

When a transaction reads data, it reads a historical version of the data, which is a snapshot of the data at the start of the transaction. Even if other transactions modify the data after the transaction has read it, the transaction can still read the version before the modification, ensuring data consistency.

### 2.3 Doris Database's Concurrency Control Optimization

#### 2.3.1 Index Optimization

Indexes are a data structure in a database used for quick data retrieval. Creating appropriate indexes can significantly improve the performance of concurrent queries.

Doris database supports multiple index types, including:

***B+ tree index:** A balanced tree index for quick data retrieval.
***Bitmap index:** An index for quick retrieval of columns with specific values.
***Bloom filter index:** An index for quick filtering of non-matching data.

#### 2.3.2 Partition Optimization

Partitioning is the process of dividing a data table into smaller parts. By partitioning, concurrent access to data can be distributed across different servers, improving concurrency.

Doris database supports two types of partitioning:

***Range Partitioning:** Divides a data table into multiple partitions based on