A.I. & Optimization

Advanced Machine Learning, Data Mining, and Online Advertising Services

Top Elasticsearch Books



The AI Optify data team writes about topics that we think software engineers will love. AI Optify has affiliate partnerships so we may get a share of the revenue from your purchase.

Best Elasticsearch Books - For this post, we have scraped various signals (e.g. online ratings and reviews, topics covered, author influence in the field, year of publication, social media mentions, etc.) from web for Elasticsearch books. We have fed all above signals to a Machine Learning algorithm to compute a score and rank the top books.

The readers will love our list because it is Data-Driven & Objective. Enjoy the list:


1. Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine
$40

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.


2. Elasticsearch in Action
$34

Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications.


3. Relevant Search: With applications for Solr and Elasticsearch
$37

Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime.