One, source code analysis

Source code analysis is a kind of critical knowledge, master this critical knowledge, can be invariable should change, source code analysis for many people is very boring, difficult to understand.

Read the source code, I think there are three core points: technical basis + strong thirst for knowledge + patience.

I think is the core driver of reading source code. The majority of programmers I’ve seen have this kind of attitude toward learning:

  • 1, only focus on the project itself, baidu if you don’t understand.
  • 2. In addition to working on projects, I also read technical books about projects and read Wikipedia.
  • 3. Besides reading books related to the project, I will also read books about the IT industry. For example, when LEARNING Java, I will also learn functional languages, such as LISP.
  • 4. Look for open source projects, try out a lot of third-party frameworks, and write demos.
  • 5. Read the basic framework, J2EE specification and Debug server kernel.

Most programs are type 1. Getting to type 5 requires not only intense interest, but courage: Can I read it? In fact, you can read it

Patience is really important. Because you rarely see instructional articles or books reading the source code, you are not required or advised to read it. You’ll often get stuck, and a reader can get stuck in a maze. What you need to do, perhaps, is to pause for a moment and look at it from the outside: the API structure, the framework design.

The following is my summary of the current most should learn source knowledge:

Distributed architecture

Distributed system is an old and broad topic, but in recent years because of the rise of the concept of “big data”, it is full of new youth and vitality. In addition, distributed systems is a discipline that places equal emphasis on theoretical models and engineering techniques. Compared with the research direction of machine learning, students studying distributed systems often feel that “it is easy to get started, but difficult to get deep”. Indeed, learning distributed systems requires almost no mathematical knowledge.

Distributed systems are a complex and broad field of study, and a course or two online, or a book or two, may not cover all of it.

In general, the task of distributed system is to combine and connect multiple machines organically, so that they can cooperate to complete a task, which can be a computing task, or a storage task. If I have to make a classification of distributed system research in recent years, I think it can probably be divided into three parts:

  • Distributed storage system
  • Distributed computing system
  • Distributed management system

Here is my summary of the most mainstream distributed technologies in recent years:

Third, micro services

Microservices are hot right now, and everyone claims to be using microservices architecture, but what exactly is microservices architecture? Is microservices architecture a trend? We all lack a clear understanding of these issues.

In order to solve the problems under the single architecture, the microservice architecture came into being. Better to break up services sooner rather than build a bloated monster that is hard to tame. The core idea of microservices is to split and decouple services to reduce complexity. Microservices emphasize the reasonable disassembling of functions, as far as possible to ensure the Single function of each service, and clear roles according to the Single Responsibility Principle. Make each service light, so as to be flexible and reusable, and also according to the needs of each service’s own resources, separate deployment, separate horizontal expansion.

The following is a summary of the knowledge points I need to learn about microservices:

Fourth, performance optimization

Whether it’s dealing with a front-end interview or improving the product experience, performance optimization is a topic that can’t be avoided.

The purpose of optimization is to make users feel “fast”, so how to make users feel fast?

The loading speed is really fast, the user opens and enters the URL, hits Enter and immediately sees the page loading speed is not faster, but the user feels that your site is fast performance optimization depends on a number of factors, including garbage collection, virtual machine and underlying operating system (OS) Settings. There are several Tools available to developers for Analysis and Optimization, and you can learn and use them by reading Java Tools for Source Code Optimization and Analysis.

It is important to understand that no two applications can be optimized the same way, and there is no perfect reference path for optimizing Java applications. Use best practices and insist on handling performance optimizations in an appropriate manner. To achieve the true highest performance optimization, you as a Java developer need to have a correct understanding of the Java Virtual Machine (JVM) and the underlying operating system.

The above five knowledge systems are the most mainstream technologies that I have summed up for many years. Friends who want to learn these techniques can add group: 478030634. The group will share these technical knowledge points for everyone to learn free download

The following is a summary of what I should learn and understand about performance optimization:

Five, Java engineering

To do a good job, you must first sharpen its tools, whether it is small white, or senior development, need to choose a good tool first. Improve development efficiency and teamwork efficiency. Give yourself more time to think.

“Big Talk Architecture” Ali architects share technical essentials Java programmers need to break through