Implementing a high-performance, scalable real-time data collection system: application and practice of go-zero

With the rapid development of Internet technology, data collection has received more and more attention and has become an important means for enterprises to obtain business value. In practical applications, we often face challenges such as large amounts of data, high concurrency, high system response speed requirements, and stress testing. How to implement a high-performance, scalable real-time data collection system? This article will introduce an emerging Go language framework - go-zero, and analyze its application and practice in real-time data collection systems.

1. Introduction to go-zero

go-zero is a high-performance software that integrates rpc, api gateway, data storage, message queue, cache, scheduled tasks, distributed locks and other functions , extensible framework. Its goal is to help developers build microservice applications quickly with minimal code.

The design concept of go-zero is to provide a highly available, high-concurrency, and low-latency application framework based on business needs. It also provides reliable data storage and caching solutions, supports various third-party integrations, and is convenient and fast. to build complex applications.

2. Application scenarios

In real-time data collection systems, we need to process massive amounts of data, and require fast system response, strong processing capabilities, and high system availability. As an emerging framework, go-zero can provide the following advantages:

1. High performance

In the process of collecting large amounts of data, performance is very critical, and The design concept of go-zero is to pursue the ultimate performance. Its underlying network framework uses Zero Copy technology, which does not require multiple memory copy operations, which can greatly improve the performance of the system. It also uses thread pool technology to effectively reduce thread context switching. The overhead increases the concurrency of the system.

2. Scalable

In a data collection system, it is inevitable to encounter problems such as system crashes and rapid growth in data volume. Therefore, high availability and scalability are also very important. of. In this regard, go-zero provides powerful expansion capabilities, which can split data horizontally and offload through load balancing mechanisms, allowing horizontal expansion at any time to meet rapid growth and fault tolerance when the system crashes.

3. Strong reliability

In real-time data collection systems, data accuracy and security are the most basic requirements. go-zero provides a complete set of data storage and caching solutions, such as MySQL, Redis, MongoDB, etc. These storage solutions have been verified in practice and can support multiple fault-tolerant mechanisms. Data can be effectively protected and durable. change.

3. Practical Application

Below we use a simple practical case to demonstrate the application of go-zero in real-time data collection systems.

Let’s take the advertising delivery system of an e-commerce platform as an example. This system needs to collect user behavior data on the site in a short period of time, and judge and match ads in real time, thereby improving the efficiency of advertising delivery.

1. Building go-zero

During the construction process, we can use the goctl tool to generate a unified code template, and use MySQL and Redis as data storage and caching solutions. The code framework is as follows:

• /ad

  • rpc

    • ad.proto
    • advertiser .proto
  • ##service
    ##ad-in-service

    • internal

      • config.go
        • logic.go
        • svc.go
        ad.go
      • go .mod
      • main.go
    Dockerfile
  • docker-compose.yml
  • go.mod
  • README.md

Code implementation

2. In the code implementation, we collect user data through HTTP protocol Access behavior on the e-commerce platform and write data into the Redis cache. At the same time, the data in the cache is synchronized to MySQL for persistent storage through scheduled tasks.

Performance Test

3. After the test is completed, we can use tools such as Jmeter to conduct performance testing, using the common QPS (query rate per second) as the main indicator. . Using the data collection system built by go-zero, the QPS can reach hundreds or thousands, and the performance is also very stable.

4. Summary

In real-time data collection systems, high performance, scalability and reliability are the three most important characteristics. Starting from a design concept, go-zero helps developers build a microservice application framework with minimal code and extremely fast speed. It can effectively improve the performance, fault tolerance and scalability of the system, and greatly facilitates the development of real-time data collection for enterprises.

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