Improving Query Performance: Query Optimization Tips for Doris Database

# Enhancing Query Performance: Query Optimization Techniques for Doris Database

## 1. Introduction to Doris Database Query Optimization

### 1.1 Overview of Doris Database Query Optimization

Doris database query optimization refers to the process of improving the query performance of the Doris database through various techniques and methods. It involves several aspects, including query statement optimization, data model optimization, and system configuration optimization.

### 1.2 Objectives of Doris Database Query Optimization

The objectives of Doris database query optimization are:

- To reduce query response time
- To decrease resource consumption (such as CPU and memory)
- To enhance query concurrency
- To improve user experience

## 2. Theoretical Foundations of Doris Database Query Optimization

### 2.1 Doris Database Architecture and Query Execution Process

**Doris Database Architecture**

The Doris database adopts an MPP (Massive Parallel Processing) architecture, consisting of two parts: FE (Frontend) and BE (Backend):

- **FE (Frontend)**: Responsible for receiving client queries, parsing SQL, generating execution plans, and coordinating BE to execute queries.
- **BE (Backend)**: Responsible for data storage, query execution, and returning query results.

**Query Execution Process**

The Doris database query execution process is as follows:

1. **Client sends a query**: The client sends an SQL query to FE.
2. **FE parses SQL**: FE parses the SQL and generates a query plan.
3. **FE coordinates BE to execute the query**: FE distributes the query plan to BE and coordinates BE to execute the query.
4. **BE executes the query**: BE executes the query according to the plan and returns the results.
5. **FE returns the results**: FE collects the results from BE and returns them to the client.

### 2.2 Objectives and Principles of Doris Database Query Optimization

**Objectives of Query Optimization**

The objectives of Doris database query optimization are:

- To reduce query latency
- To improve query throughput
- To decrease resource consumption

**Principles of Query Optimization**

The principles that Doris database query optimization follows are:

- **Cost-based optimization**: Selects the optimal execution plan based on the execution cost of the query plan.
- **Predicate pushdown**: Pushes filtering conditions down to BE to reduce the data volume that BE needs to process.
- **Index utilization**: Uses indexes to accelerate queries and reduce the data volume that BE needs to scan.
- **Data partitioning**: Partitions data according to certain rules to reduce the data volume that BE needs to scan.
- **Parallel execution**: Utilizes the MPP architecture to execute queries in parallel, improving query throughput.

**Code Block:**

# Example code for generating a query plan
query_plan = fe.generate_query_plan(sql)

# Example code for executing a query plan
fe.execute_query_plan(query_plan)

**Logical Analysi