更新时间：2021-06-24 14:08:16
coverpage
Title Page
Copyright and Credits
Learning Elastic Stack 7.0 Second Edition
About Packt
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Contributors
About the authors
About the reviewer
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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
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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
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
