Building a high-concurrency, high-reliability distributed data storage system: application and practice of go-zero

With the rapid development of the Internet, massive data storage and processing have become important issues in the development of enterprises and organizations. In the process of storing big data, traditional stand-alone storage technology can no longer meet actual needs such as high concurrency, high reliability, low latency, and easy expansion. Therefore, distributed storage technology emerged as the times require.

Go-zero is a distributed application framework developed by Ant Financial based on the Go language. It has the characteristics of high concurrency, high reliability, low latency, and easy expansion. Go-zero includes RPC framework, Web framework, data storage and other infrastructure, providing a solution to quickly build distributed applications. This article will introduce the application and practice of Go-zero and discuss how to build a high-concurrency and high-reliability distributed data storage system.

1. Overview of Go-zero

Go-zero, as a distributed application framework based on Go language, was officially open sourced in May 2020. Go-zero provides a complete set of distributed application solutions, including RPC framework, Web framework, data storage and other infrastructure.

1. Go-zero's RPC framework

Go-zero's RPC framework uses Protobuf as the serialization protocol, Jwt as the authentication protocol and Etcd as the service discovery and configuration center. The RPC framework has the following characteristics:

(1) Goroutine reuse: The built-in Goroutine feature of the Go language achieves high concurrency effects. Go-zero's RPC framework also provides a reuse mechanism for Goroutine. This reduces Goroutine overhead and increases concurrency.

(2) Service circuit breaker: In a high-concurrency environment, service exceptions or delays can cause the entire application to become unavailable. Go-zero's RPC framework provides circuit breakers, which can automatically detect service anomalies or delays and immediately downgrade or switch services, thereby improving service availability.

(3) Load balancing: Go-zero's RPC framework uses Etcd as the service discovery and configuration center, and automatically selects appropriate service nodes through the load balancing algorithm to achieve high availability and high performance service access.

2. Go-zero's Web framework

Go-zero's Web framework adopts byte cloud native technology and utilizes coroutine pool technology and zero-copy technology to achieve high concurrency, low latency, High-performance Web services have the following characteristics:

(1) Automatic routing: Go-zero's Web framework adopts the REST architectural style and supports automatic routing and parameter parsing, which greatly simplifies the difficulty of route definition.

(2) Middleware mechanism: Go-zero's Web framework supports the middleware mechanism, which can implement the interception and processing of requests and responses, and facilitate the expansion of user authentication, security control, logging and other functions.

(3) Template engine: Go-zero's Web framework uses a high-performance template engine that supports data rendering in HTML, JSON, XML, and MARKDOWN formats, providing a better display effect for business logic.

3. Go-zero’s data storage

Go-zero provides support based on MySQL, Redis, ES and other data storage technologies, and adopts DDD domain-driven design ideas to achieve high-level Data storage solution with high performance, high reliability and easy scalability. Go-zero's data storage module has the following characteristics:

(1) ORM framework: Go-zero's ORM framework supports automatic generation of table structures, support for read-write separation, support for transaction operations, support for caching, and support for batch processing , greatly improving development efficiency and code quality.

(2) NoSQL access: Go-zero’s data storage also supports access to NoSQL storage technologies such as Redis and ES, providing high-performance, high-reliability, and high-concurrency services.

2. Build a high-concurrency, high-reliability distributed data storage system

Based on Go-zero’s RPC framework and data storage module, we can quickly build a high-concurrency, high-reliability distributed data storage system. , an easily scalable distributed data storage system. The following are the main technical selection and practical steps to build the solution.

1. Technology Selection

In the process of building a distributed data storage system, it is necessary to consider how to achieve data read and write consistency, data high availability, replica data synchronization and other issues. . Therefore, we can use the following technology selection:

(1) MySQL database: As the core component of data storage, use the MySQL database as the main database, and then use the open source MaxWell component to implement Binlog-based data synchronization, so that Achieve data reading and writing separation and high data availability.

(2) Redis database: The Redis database is used to cache and synchronize copy data, which improves the performance and reliability of data reading.

(3) Etcd service discovery and configuration center: Using Etcd as the service discovery and configuration center can realize automatic discovery of services, load balancing, service circuit breaker and other functions.

(4) Go-zero’s RPC framework and data storage module: Using Go-zero’s RPC framework and data storage module, it achieves high-performance, high-concurrency, and high-reliability services and provides distributed data Storage provides security.

2. Practical steps

(1) Design the database architecture: Determine the data table structure, data relationships, indexes, etc. to ensure that the data can be stored and queried quickly and effectively.

(2) Build MySQL master-slave architecture: Through the MySQL master-slave architecture, read-write separation and high data availability are achieved.

(3) Integrate MaxWell components: According to business needs, integrate MaxWell components to achieve data synchronization based on Binlog to ensure data consistency when reading from sub-databases.

(4) Use Redis cache: cache some commonly used data (such as user information) through Redis to improve data reading performance and reliability.

(5) Write data access layer code: Use Go-zero's ORM framework to write data access layer code to ensure data reliability and high performance.

(6) Write business logic code: Write business logic code according to business needs, and implement distributed services through Go-zero's RPC framework.

(7) Use Etcd to realize service registration and discovery: Register distributed services in Etcd, and use Etcd to realize automatic discovery of services, load balancing, service circuit breaker and other functions.

3. Summary

Go-zero, as a distributed application framework based on Go language, has the characteristics of high concurrency, high reliability, low latency, easy expansion, etc., and can quickly build distribution formula system. This article introduces the application and practice of Go-zero and discusses how to build a high-concurrency and high-reliability distributed data storage system. In actual applications, we can use different technology selections and practical solutions according to specific business needs to achieve high-performance distributed applications.

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