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Advanced Elasticsearch 7.0, by Packt

HTML 6.76% Shell 0.09% Java 0.15% Python 90.91% Roff 0.01% CSS 0.01% JavaScript 0.06% Jupyter Notebook 0.04% C++ 0.12% C 1.38% Fortran 0.03% Makefile 0.10% MATLAB 0.01% TeX 0.04% Batchfile 0.05% Smarty 0.01% Dockerfile 0.01% Cython 0.27%

advanced-elasticsearch-7.0's Introduction

Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0

This is the code repository for Advanced Elasticsearch 7.0, published by Packt.

Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana

What is this book about?

Advanced Elasticsearch 7.0, will help the readers to leverage new features and Core APIs of Elasticsearch to perform advanced search operations. This book covers data modeling, aggregations, pipeline processing, and data Analytics using Elasticsearch

This book covers the following exciting features:

  • Pre-process documents before indexing in ingest pipelines
  • Learn how to model your data in the real world
  • Get to grips with using Elasticsearch for exploratory data analysis
  • Understand how to build analytics and RESTful services
  • Use Kibana, Logstash, and Beats for dashboard applications
  • Get up to speed with Spark and Elasticsearch for real-time analytics
  • Explore the basics of Spring Data Elasticsearch, and understand how to index, search, and query in a Spring application

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

html, body, #map {
 height: 100%; 
 margin: 0;
 padding: 0
}

Following is what you need for this book: This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and understand how the real-time processing and search engine works for business analytics and enterprise search applications. Experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.

With the following software and hardware list you can run all code files present in the book (Chapter 1-18).

Software and Hardware List

Chapter Software required OS required
All Elasticsearch (7.0.0), Postman (6.6.1) Windows, Mac OS X, and Linux (Any)
11 JDK (8) Windows, Mac OS X, and Linux (Any)
12 Python (3.6) Windows, Mac OS X, and Linux (Any)
13 Kibana (7.0.0), Logstash, Filebeat, Docker, Elastic Stack Docker image Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Related products

Get to Know the Author

Wai Tak Wong is a faculty member in the Department of Computer Science at Kean University, NJ, USA. He has more than 15 years professional experience in cloud software design and development. His PhD in computer science was obtained at NJIT, NJ, USA. Wai Tak has served as an associate professor in the Information Management Department of Chung Hua University, Taiwan. A co-founder of Shanghai Shellshellfish Information Technology, Wai Tak acted as the Chief Scientist of the R&D team, and he has published more than a dozen algorithms in prestigious journals and conferences. Wai Tak began his search and analytics technology career with Elasticsearch in the real estate market and later applied this to data management and FinTech data services.

Suggestions and Feedback

Click here if you have any feedback or suggestions.

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781789957754

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