Book Image

Building Enterprise JavaScript Applications

By : Daniel Li
Book Image

Building Enterprise JavaScript Applications

By: Daniel Li

Overview of this book

With the over-abundance of tools in the JavaScript ecosystem, it's easy to feel lost. Build tools, package managers, loaders, bundlers, linters, compilers, transpilers, typecheckers - how do you make sense of it all? In this book, we will build a simple API and React application from scratch. We begin by setting up our development environment using Git, yarn, Babel, and ESLint. Then, we will use Express, Elasticsearch and JSON Web Tokens (JWTs) to build a stateless API service. For the front-end, we will use React, Redux, and Webpack. A central theme in the book is maintaining code quality. As such, we will enforce a Test-Driven Development (TDD) process using Selenium, Cucumber, Mocha, Sinon, and Istanbul. As we progress through the book, the focus will shift towards automation and infrastructure. You will learn to work with Continuous Integration (CI) servers like Jenkins, deploying services inside Docker containers, and run them on Kubernetes. By following this book, you would gain the skills needed to build robust, production-ready applications.
Table of Contents (26 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
1
The Importance of Good Code
Index

Understanding key concepts in Elasticsearch


We will be sending queries to Elasticsearch very shortly, but it helps if we understand a few basic concepts.

 

 

Elasticsearch is a JSON document store

As you might have noticed from the response body of our API call, Elasticsearch stores data in JavaScript Object Notation (JSON) format. This allows developers to store objects with more complex (often nested) structures when compared to relational databases that impose a flat structure with rows and tables.

That's not to say document databases are better than relational databases, or vice versa; they are different and their suitability depends on their use.

Document vs. relationship data storage

For example, your application may be a school directory, storing information about schools, users (including teachers, staff, parents, and students), exams, classrooms, classes, and their relations with each other. Given that the data structure can be kept relatively flat (that is, mostly simple key-value entries...