Learning Elastic Stack 7.0（Second Edition）

coverpage

Title Page

Copyright and Credits

Learning Elastic Stack 7.0 Second Edition

About Packt

Why subscribe?

Packt.com

Contributors

About the authors

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Section 1: Introduction to Elastic Stack and Elasticsearch

Introducing Elastic Stack

What is Elasticsearch and why use it?

Schemaless and document-oriented

Searching capability

Analytics

Rich client library support and the REST API

Easy to operate and easy to scale

Near real-time capable

Lightning–fast

Fault-tolerant

Exploring the components of the Elastic Stack

Elasticsearch

Logstash

Beats

Kibana

X-Pack

Security

Monitoring

Reporting

Alerting

Graph

Machine learning

Elastic Cloud

Use cases of Elastic Stack

Log and security analytics

Product search

Metrics analytics

Web search and website search

Downloading and installing

Installing Elasticsearch

Installing Kibana

Summary

Getting Started with Elasticsearch

Using the Kibana Console UI

Core concepts of Elasticsearch

Indexes

Types

Documents

Nodes

Clusters

Shards and replicas

Mappings and datatypes

Datatypes

Core datatypes

Complex datatypes

Other datatypes

Mappings

Creating an index with the name catalog

Defining the mappings for the type of product

Inverted indexes

CRUD operations

Index API

Indexing a document by providing an ID

Indexing a document without providing an ID

Get API

Update API

Delete API

Creating indexes and taking control of mapping

Creating an index

Creating type mapping in an existing index

Updating a mapping

REST API overview

Common API conventions

Formatting the JSON response

Dealing with multiple indexes

Searching all documents in one index

Searching all documents in multiple indexes

Searching all the documents of a particular type in all indexes

Summary

Section 2: Analytics and Visualizing Data

Searching - What is Relevant

The basics of text analysis

Understanding Elasticsearch analyzers

Character filters

Tokenizer

Standard tokenizer

Token filters

Using built-in analyzers

Standard analyzer