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Learning Elastic Stack 6.0
Learning Elastic Stack 6.0

Learning Elastic Stack 6.0: A beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana

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Profile Icon Pranav Shukla Profile Icon Sharath Kumar
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (10 Ratings)
Paperback Dec 2017 434 pages 1st Edition
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Profile Icon Pranav Shukla Profile Icon Sharath Kumar
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (10 Ratings)
Paperback Dec 2017 434 pages 1st Edition
eBook
€8.99 €23.99
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Learning Elastic Stack 6.0

Getting Started with Elasticsearch

In the first chapter we looked at the reasons for learning about and using Elastic Stack, and the use cases of Elastic Stack.
In this chapter, we will start our journey of learning about Elastic Stack, starting at the core of Elastic Stack—Elasticsearch. Elasticsearch is the search and analytics engine behind Elastic Stack. We will learn the core concepts of Elasticsearch while doing some hands-on practice; we will learn about querying, filtering, and searching.

We will cover the following topics in this chapter:

  • Using the Kibana Console UI
  • Core concepts
  • CRUD (Create, Read, Update, Delete) operations
  • Creating indexes and taking control of mapping
  • REST API overview

Using the Kibana Console UI

Before we start writing our first queries to interact with Elasticsearch, we should familiarize ourselves with a very important tool: Kibana Console. This is important because Elasticsearch has a very rich REST API, allowing you to do all possible operations with Elasticsearch. Kibana Console has an editor which is very capable and aware of the REST API. It allows for auto-completion, and for the formatting of queries as you write them.

What is a REST API? REST stands for Representational State Transfer. It is an architectural style to make systems inter-operate and interact with each other. REST has evolved along with the HTTP protocol, and almost all REST-based systems use HTTP as their protocol. HTTP supports different methods including GET, POST, PUT, DELETE, HEAD, and so onwhich are used for different semantics. For example...

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...

CRUD operations

In this section we will look at how to perform basic CRUD operations, which are the most fundamental operations required by any data store. Elasticsearch has a very well designed REST API, and the CRUD operations are targeted at documents. 

To understand how to perform CRUD operations, we will cover the following APIs. These APIs fall under the category of Document APIs that deal with documents:

  • Index API
  • Get API
  • Update API
  • Delete API

Index API

In Elasticsearch terminology, adding (or creating) a document into a type within an index of Elasticsearch is called an indexing operation. Essentially, it involves adding the document to the index by parsing all fields within the document...

Creating indexes and taking control of mapping

In the previous section, we learnt how to perform CRUD operations with Elasticsearch. In the process, we saw how indexing the first document to an index which doesn't yet exist results in the creation of the new index and the mapping of the type.

Usually, you wouldn't want to let things happen automatically, as you would want to control how indices are created and also how mapping is created. We will see how you can take control of this process in this section and look at the following:

  • Creating an index
  • Create a mapping
  • Updating a mapping

Creating an index

You can create an index and specify the number of shards and replicas to create:

PUT /catalog
{
"settings...

REST API overview

We just looked at how to perform basic CRUD operations. Elasticsearch supports a wide variety of operation types. Some operations deal with documents, that is, creating, reading, updating, deleting, and so on. Some operations provide search and aggregations, while other operations are for providing cluster related operations, such as monitoring health. Broadly, the APIs that deal with Elasticsearch are categorized into the following types of APIs:

  • Document APIs
  • Search APIs
  • Aggregations APIs
  • Indices APIs
  • Cluster APIs
  • cat APIs

The Elasticsearch reference documentation has documented these APIs very nicely. In this book, we will not go into the APIs down to the last detail. We will conceptually understand, with examples, how the APIs can be leveraged to get the best out of Elasticsearch and other components of Elastic Stack.

We will look at the search and...

Using the Kibana Console UI


Before we start writing our first queries to interact with Elasticsearch, we should familiarize ourselves with a very important tool: Kibana Console. This is important because Elasticsearch has a very rich REST API, allowing you to do all possible operations with Elasticsearch. Kibana Console has an editor which is very capable and aware of the REST API. It allows for auto-completion, and for the formatting of queries as you write them.

Note

What is a REST API? REST stands for Representational State Transfer. It is an architectural style to make systems inter-operate and interact with each other. REST has evolved along with the HTTP protocol, and almost all REST-based systems use HTTP as their protocol. HTTP supports different methods including GET, POST, PUT, DELETE, HEAD, and so onwhich are used for different semantics. For example, GET is used for getting or searching for something. POST is used for creating a new resource, PUT may be used for creating or updating...

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Key benefits

  • - Get to grips with the new features introduced in Elastic Stack 6.0
  • - Get valuable insights from your data by working with the different components of the Elastic stack such as Elasticsearch, Logstash, Kibana, X-Pack, and Beats
  • - Includes handy tips and techniques to build, deploy and manage your Elastic applications efficiently on-premise or on the cloud

Description

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.

Who is this book for?

This book is for data professionals who want to get amazing insights and business metrics from their data sources. If you want to get a fundamental understanding of the Elastic Stack for distributed, real-time processing of data, this book will help you. A fundamental knowledge of JSON would be useful, but is not mandatory. No previous experience with the Elastic Stack is required.

What you will learn

  • - Familiarize yourself with the different components of the Elastic Stack
  • - Get to know the new functionalities introduced in Elastic Stack 6.0
  • - Effectively build your data pipeline to get data from terabytes or petabytes of data into Elasticsearch and Logstash for searching and logging
  • - Use Kibana to visualize data and tell data stories in real-time
  • - Secure, monitor, and use the alerting and reporting capabilities of Elastic Stack
  • - Take your Elastic application to an on-premise or cloud-based production environment

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 22, 2017
Length: 434 pages
Edition : 1st
Language : English
ISBN-13 : 9781787281868
Vendor :
Elastic
Category :

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Product Details

Publication date : Dec 22, 2017
Length: 434 pages
Edition : 1st
Language : English
ISBN-13 : 9781787281868
Vendor :
Elastic
Category :

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Table of Contents

11 Chapters
Introducing Elastic Stack Chevron down icon Chevron up icon
Getting Started with Elasticsearch Chevron down icon Chevron up icon
Searching-What is Relevant Chevron down icon Chevron up icon
Analytics with Elasticsearch Chevron down icon Chevron up icon
Analyzing Log Data Chevron down icon Chevron up icon
Building Data Pipelines with Logstash Chevron down icon Chevron up icon
Visualizing data with Kibana Chevron down icon Chevron up icon
Elastic X-Pack Chevron down icon Chevron up icon
Running Elastic Stack in Production Chevron down icon Chevron up icon
Building a Sensor Data Analytics Application Chevron down icon Chevron up icon
Monitoring Server Infrastructure Chevron down icon Chevron up icon

Customer reviews

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5 star 80%
4 star 10%
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Joe 21 Apr 21, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great intro to the Elastic Stack.
Amazon Verified review Amazon
Ra Feb 24, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
El libro está muy bien, y puedes aprender a implantar y usar ELK desde 0, además el lenguaje es sencillo y está muy actualizado
Amazon Verified review Amazon
Paolo Eusebi Feb 08, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really liked the way the authors guide through the required steps for working with Elasticsearch stack!
Amazon Verified review Amazon
Amazon Customer Jan 22, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As Elasticsearch has become number one search engine and with the rapid adoption of elastic stack for various analytics use cases I was looking for a book which is simple yet covers the required details and help me learn and implement things fast. Thankfully I stumbled upon this book which met my needs and also this book covers the latest version which is very helpful.
Amazon Verified review Amazon
Garrett Pickering Jul 18, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book was great. Read it on a flight. 10 out of 10, would read again.
Amazon Verified review Amazon
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