"Big Talk Architecture" Ali architects share the technical essentials that Java programmers need to break

Source: Internet
Author: User

First, source code analysis

Source analysis is a critical knowledge, mastered this critical knowledge, can not change, source analysis for many people is very dull, jerky difficult to understand.

Source reading, I think the core has three points: technical basis + strong curiosity + patience.

I think it is the most core driving force of Reading source code. I see the vast majority of programmers, the attitude towards learning is basically these levels (very extreme OH):

1, only focus on the project itself, do not understand Baidu a bit.

2, in addition to doing a good project, will also read and project related technical books, see Wikipedia.

3, in addition to reading and project-related books, but also read the IT industry books, such as learning Java, but also to understand the functional language, such as Lisp.

4, find some open source projects to see, a lot of trial third-party framework, will also write a demo.

5, reading the basic framework, Java specification, debug Server Core.

Most programs are 1th, and the 5th requires not only a strong interest, but also courage: can I read it? Actually, you can read it.

Patience, it's really important. Because you rarely see a guide to reading the source of articles or books, and no one asked or suggested that you read. You often get stuck in the process of reading, and one card owner may be trapped in a maze. At this point, you need to do, may be temporarily interrupted, and then look at it from the periphery: such as the API structure, the framework of the design diagram.

I summed up the current most should learn the source of knowledge points:

Second, distributed architecture

Distributed system is an old and broad topic, and in recent years, because of the rise of the concept of "big data", new youth and vitality have been rejuvenated. In addition, distributed system is also a theoretical model and engineering techniques to both the subject content. Compared to the research direction of machine learning, students who study distributed systems tend to feel: "Easy to get started, deep and difficult". Indeed, learning a distributed system hardly requires much mathematical knowledge.

Distributed systems are a complex and broad field of study, learning one or two online courses, and reading one or two books may not completely cover all of their content.

In general, the task of a distributed system is to combine multiple machines organically, connect them together, and make them work together to accomplish a task, which can be a computational task or a storage task. If we must make a classification of distributed system Research in recent years, I personally think that probably can include three parts:

1. Distributed Storage System

2. Distributed Computing Systems

3. Distributed Management System

I summarize the current distributed most mainstream technology in recent years:

Third, micro-services

The current microservices are hot and everyone claims to be using a microservices architecture, but what exactly is a microservices architecture? is the micro-service architecture a development trend? We all lack a clear understanding of these issues.

In order to solve the various problems under the single structure, the micro-service architecture emerges. Rather than building a bloated, hard-to-tame monster, you might as well split the service early. The core idea of microservices is service splitting and decoupling, reducing complexity. MicroServices emphasize the rational dismantling of functions, as far as possible to ensure that each service is functionally single, in accordance with the single responsibility principle (Responsibility Principle) clear role. The services are light, flexible and reusable, and can be individually scaled up according to the individual resource requirements of each service.

I summed up the micro-service needs to learn the point of knowledge:

Four, performance optimization

Whether you're dealing with front-end interviews or improving your product experience, performance optimization is a topic that can't be avoided.

The goal of optimization is to let users feel "fast", how to make users feel fast?

Loading speed really quickly, the user opens the input URL press ENTER to immediately see the page

Loading speed does not change fast, but users feel that your site is fast

Performance optimization depends on several factors, including garbage collection, virtual machines, and underlying operating system (OS) settings. There are several tools for developers to use when analyzing and optimizing, and you can learn and use them by reading Java tools for Source Code optimization and analyses.

It is important to understand that no two applications can use the same optimizations, and there is no perfect reference path for optimizing Java applications. Use best practices and stick with the right way to handle performance optimizations. To achieve true maximum performance optimization, you, as a Java developer, need to have a proper understanding of the Java Virtual Machine (JVM) and the underlying operating system.

Is that I summarize the performance optimization should learn to understand a few knowledge system:


工欲善其事, its prerequisite, whether small white, or senior development, all need to choose a good tool first. Improve the efficiency of development and team collaboration. Let yourself have more time to think.

The above five knowledge system is my experience for many years to summarize, are the most mainstream technology at present. Friends who want to learn these techniques can add a group: 685167672. The group will share these technical knowledge points for everyone to learn free download

"Big Talk Architecture" Ali architects share the technical essentials that Java programmers need to break

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