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Getting to Know the Language

这是专门针对小白的零基础Java教程。

Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.

his guide provides a sampling of how Spring Boot helps you accelerate application development.

The author teaches you how to use Spring Boot from a complete beginner, to building a REST API with a real database, Dockerising it and deploying it to the cloud.

Learn Spring Cloud including concepts, additional libraries and examples for distributed systems.

Microservice applications are composed of small, independently versioned, and scalable customer-focused services that communicate with each other by using standard protocols and well-defined interfaces.

Microservices - also known as the microservice architecture - is an architectural style that structures an application as a collection of two or more services.

Building small, self-contained, ready to run applications can bring great flexibility and added resilience to your code.

Microservices, or microservices architecture, is a cloud-native architectural approach in which a single application is composed of many loosely coupled and independently deployable smaller components or services.

Learn about software system design and microservices.

设计模式，即Design Patterns，是指在软件设计中，被反复使用的一种代码设计经验。使用设计模式的目的是为了可重用代码，提高代码的可扩展性和可维护性。

Design patterns are typical solutions to common problems in software design. Each pattern is like a blueprint that you can customize to solve a particular design problem in your code.

创建型模式、结构型模式和行为模式。

Design Patterns tutorial explained in simple words using real-world examples.

通过阅读本文读者可以初步理解 Istio 流量治理的概念和相关知识框架。

服务治理主要包括服务发现、负载均衡、限流、熔断、超时、重试、服务追踪等。我们今天要讲的，就是服务发现的内容。

大数据处理的主要流程包括数据收集、数据存储、数据处理、数据应用等主要环节。

With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.

Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。

Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.

Apache Spark 是用于大规模数据处理的统一分析引擎。

This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.

Apache Flink 是一个分布式计算框架，它能够对有界和无界的数据流进行高效的处理。

This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.

Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.

In this Apache Kafka fundamentals course, we introduce you to the basic Apache Kafka elements and APIs, as well as the broader Kafka ecosystem.

Hive is a data warehouse infrastructure tool to process structured data in Hadoop. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy.

HBase is a data model that is similar to Google's big table designed to provide quick random access to huge amounts of structured data. This tutorial provides an introduction to HBase, the procedures to set up HBase on Hadoop File Systems, and ways to interact with HBase shell.

The home page of a free online class in distributed systems.

Get all the tutorials, learning paths, and more you need to start building—fast.

REmote DIctionary Server(Redis) 是一个由 Salvatore Sanfilippo 写的 key-value 存储系统，是跨平台的非关系型数据库。

In this video I will be covering Redis in depth from how to install it, what commands you can use, all the way to how to use it in a real world project.

Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.