Book Image

Learning Elastic Stack 6.0

By : Pranav Shukla, Sharath Kumar M N
Book Image

Learning Elastic Stack 6.0

By: Pranav Shukla, Sharath Kumar M N

Overview of this book

The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. After a quick overview of the newly introduced features in Elastic Stack 6.0, you’ll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You’ll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments. On completing this book, you’ll have a solid foundational knowledge of the basic Elastic Stack functionalities. You’ll also have a good understanding of the role of each component in the stack to solve different data processing problems.
Table of Contents (19 chapters)
Title Page
Credits
Disclaimer
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Core concepts


Relational databases have concepts such as rows, columns, tables, and schema. Elasticsearch and other document-oriented stores are based on different abstractions. Elasticsearch is a document-oriented store. JSON documents are first class citizens in Elasticsearch. These JSON documents are organized within different types and indexes. We will look at the following core abstractions of Elasticsearch:

  • Index
  • Type
  • Document
  • Cluster
  • Node
  • Shards and replicas
  • Mappings and types
  • Inverted index

Let us start learning these with an example:

PUT /catalog/product/1
{
    "sku": "SP000001",
    "title": "Elasticsearch for Hadoop",
    "description": "Elasticsearch for Hadoop",
    "author": "Vishal Shukla",
    "ISBN": "1785288997",
    "price": 26.99
}

Copy and paste this example into the editor of your Kibana Console UI and execute it. This will index a document which represents a product in the product catalog of a system. All examples written for the Kibana Console UI can be very easily converted...