Book reading: Elasticsearch The definitive guide - A distributed real-time search and analytics engine

Oct. 1, 2021

Introduction

I spent a day to read the book called Elasticsearch The definitive guide. I went over the book page by page, read something if I like, and then look for some good presentation through the book. 

My reading time | Highlights | What to do to be a better reader

I like to spend time to work on more reading related to the book. 

1. Authors: Clinto Gormley & Zachary Tong.
2. First few hours are very important. Once I understand the basics from the book, I will go back to read the book again and again. 
3. I should become a best book reader in my early ages, for example, in my 20s, or in my 30s. 

Whether you need full-text search or real-time analytics of structured data or both—the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.

If you’re a newcomer to both search and distributed systems, you’ll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you’ll follow a problem-based approach to learn why, when, and how to use Elasticsearch features.

1. Understand how Elasticsearch interprets data in your documents    <- Focus on this part first
2. Index and query your data to take advantage of search concepts such as relevance and word proximity
3. Handle human language through the effective use of analyzers and queries
4. Summarize and group data to show overall trends, with aggregations and analytics
5. Use geo-points and geo-shapes—Elasticsearch’s approaches to geolocation
6. Model your data to take advantage of Elasticsearch’s horizontal scalability
7. Learn how to configure and monitor your cluster in production