Alibaba architect of "big talk architecture" shares the technical points that Java Programmers need to break through. Alibaba java

Alibaba architect of "big talk architecture" shares the technical points that Java Programmers need to break through. Alibaba java
I. Source Code Analysis

Source code analysis is a critical knowledge that can remain unchanged. source code analysis is boring and difficult for many people.

I think there are three core points in the source code reading: technical foundation + strong curiosity + patience.

I think it is the core driving force for reading source code. I have seen a vast majority of programmers and their attitudes towards learning are basically at these levels (very extreme ):

1. Pay attention to the project itself. If you don't understand it, just click baidu.

2. In addition to doing a good job in projects, you will also read technical books related to projects and wikipedia.

3. Besides reading project-related books, you can also read books in the IT industry. For example, when learning Java, you can also learn about function languages, such as LISP.

4. Find some open-source projects and try out a large number of third-party frameworks and write a demo.

5. Read the basic framework, J2EE specifications, and Debug server kernel.

Most programs are 1st types. to 5th types require not only strong interest, but also courage: Can I understand them? Actually, what you can understand

Patience is really important. Because you seldom read guidance articles or books on source code, and no one asks or recommends you read them. You often get stuck during reading, and a card master may be stuck in the maze. At this time, what you need to do may be a temporary interruption, and then look at it from the periphery: such as the API structure, framework design diagram.

I have summarized the source code knowledge points that should be learned at present:

Ii. distributed architecture

Distributed systems are an old and broad topic. In recent years, thanks to the rise of the concept of "Big Data", new youth and vitality have emerged. In addition, distributed systems are also a subject that emphasizes both theoretical models and engineering techniques. Compared with machine learning, those who study distributed systems often feel "Easy to get started and hard to get into depth ". Indeed, learning distributed systems requires almost no mathematical knowledge.

Distributed systems are a complex and broad field of research. When I study one or two online courses, reading one or two books may not cover all of their contents.

In general, the task of a distributed system is to organically combine and connect multiple machines to complete a task, which can be a computing task or a storage task. If we need to classify distributed system research in recent years, I personally think it may include three parts:

1. Distributed Storage System

2. Distributed Computing System

3. Distributed Management System

I have summarized the most popular distributed technologies in recent years:

Iii. microservices

At present, microservices are very popular and everyone claims to be using the microservice architecture. But what is the microservice architecture? Is microservice architecture a development trend? We lack a clear understanding of these issues.

To solve various problems in a single architecture, the microservice architecture came into being. It is better to split services as early as possible than to build a bloated, huge, and difficult-to-Tame monster. The core idea of microservices is service splitting and decoupling to reduce complexity. Microservices emphasize the rational dismantling of functions, ensure that each service has a Single function as much as possible, and clarify roles according to the Single Responsibility Principle. Services are lightweight, so that they are flexible and reusable. They can also be separately deployed and horizontally expanded based on the resource requirements of each service.

I have summarized the knowledge points to learn about microservices:

Iv. Performance Optimization

Performance optimization is an unavoidable topic for both front-end interviews and product experience improvement.

The purpose of optimization is to make users feel "fast". How can they feel "fast?

1. Loading Speed is really fast. the user opens the URL and press enter to immediately see the page

2. Loading speed is not getting faster, but users feel that your website is very fast.

Performance Optimization depends on multiple factors, including garbage collection, virtual machines, and underlying operating system (OS) settings. There are multiple Tools for developers to use for Analysis and Optimization. You can learn and use them by reading Java Tools for Source Code Optimization and Analysis.

It must be understood that no two applications can use the same optimization method, and there is no perfect reference path for optimizing java applications. Use best practices and stick to appropriate methods for performance optimization. To achieve the best performance optimization, as a Java developer, you must have a correct understanding of the Java Virtual Machine (JVM) and underlying operating systems.

The above five knowledge systems are the most mainstream technologies I have learned over the years. Friends who want to learn these technologies can join the group: 619881427. These technical knowledge points will be shared in the group for free download.

I have summarized several knowledge systems that should be learned and understood in performance optimization:

V. Java Engineering

To do this, you must first choose a good tool, whether it is a little white or a senior developer. Improve development efficiency and team collaboration efficiency. Let yourself have more time to think.