Probing Into Database Performance: Performance Analysis and Tuning of Doris Database

# 1. Overview of Doris Database Performance Analysis

Doris database is a distributed MPP (Massively Parallel Processing) database designed for large-scale data analytics. Its high-performance characteristics enable it to process massive amounts of data swiftly and provide real-time query responses to users. To ensure optimal performance of the Doris database, a comprehensive performance analysis is crucial.

This chapter will introduce an overview of Doris database performance analysis, including its importance, key performance indicators, and performance analysis tools. By understanding these basic concepts, readers can lay the foundation for in-depth performance analysis and tuning in subsequent chapters.

# 2. Doris Database Performance Analysis in Practice

### 2.1 Doris Database Architecture and Performance Metrics

#### 2.1.1 Doris Database Architecture

The Doris database employs an MPP (Massively Parallel Processing) architecture, consisting of two main components: FE (Frontend) and BE (Backend). The FE is responsible for metadata management, query parsing, and optimization, while the BE handles data storage and computation.

#### 2.1.2 Key Performance Indicators

The key performance indicators for the Doris database include:

- **Query Latency:** The time required to execute a query.
- **Throughput:** The number of queries processed per second.
- **Concurrency:** The number of queries processed simultaneously.
- **Resource Utilization:** The utilization rates of CPU, memory, and storage.

### 2.2 Doris Database Performance Analysis Tools

#### 2.2.1 Doris Database Built-in Analysis Tools

Doris database offers a variety of built-in analysis tools, including:

- **EXPLAIN:** Displays the query execution plan and statistical information.
- **PROFILE:** Provides detailed time and resource consumption for query execution.
- **Slow Query Log:** Records queries that exceed a certain execution time threshold.

#### 2.2.2 Third-party Analysis Tools

In addition to built-in tools, third-party tools can also be utilized for performance analysis, such as:

- **Grafana:** Visualizes and monitors Doris database performance metrics.
- **Prometheus:** Collects and stores Doris database performance data.
- **Jaeger:** Tracks query execution flow to identify performance bottlenecks.

### 2.3 Doris Database Performance Analysis Methods

#### 2.3.1 SQL Query Analysis

Analyzing SQL queries is a key step in performance analysis. Tools like EXPLAIN and PROFILE can be used to view the query execution plan and statistical information. By analyzing the logic of the queries, potential performance bottlenecks can be identified, such as:

- **Unnecessary Full Table Scans:** Using indexes can avoid full table scans and improve query efficiency.
- **Inappropriate Join Methods:** Employing correct join methods (e.g., INNER JOIN or OUTER JOIN) can optimize query performance.
- **Unreasonable Sorting or Grouping:** When using ORDER BY or GROUP BY clauses, consider the data volume and the distribution of sorting/grouping fields.

#### 2.3.2 System Resource Monitoring

Monitoring system resources such as CPU, memory, and storage can help identify performance bottlene