Learning Path: The Complete Guide To Elasticsearch 5.X

Perform advanced search and analytics with Elasticsearch 5.x

What you'll learn

Understand how to choose the best Elasticsearch cloud topology to deploy and power it up with external plugins

Learn cluster, node, and its services

Understand and explore replication and sharding

Learn how to map base types, arrays, and objects

Get familiar with basic operations in Elasticsearch such as creating, deleting, and opening/closing

Learn how to use has_child query, has_parent query, and nested query for searching

Explore aggregations and scripting in Elasticsearch

Requirements

Basic JSON knowledge is required.

Understanding of Java and related technologies is also needed.

Description

Elasticsearch is an open-source, broadly-distributable, readily-scalable, and enterprise-grade search engine. Accessible through an extensive and elaborate API, Elasticsearch can power extremely fast searches that support your data discovery applications. If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, then go for this Learning Path.
Packt’s Video Learning Path is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.


With regard to Elasticsearch, we have the following advantages:


Full-text search. Schema free. Built on top of Lucene. Supports Cloud.


This Learning Path is a one-stop guide to master the complete Elasticsearch ecosystem. You will start with learning new features of Elasticsearch 5.x and setting up Elasticsearch on your system. Then, you will learn basic operations of Elasticsearch to perform on your data. Moving ahead, you will learn to create complex queries and analytics, and perform index mapping. Finally, you will learn advanced operations such as searching, working with text, numeric and geo queries, and performing aggregations and scripting.


By the end of this Learning Path, you will gain a deeper understanding of new features and operations of Elasticsearch 5.x to create flexible and scalable search solutions.

About the Author:

Alberto Paro is an engineer, project manager, and software developer. He currently works as freelance trainer/consultant on big data technologies and NoSQL solutions. He loves to study emerging solutions and applications mainly related to big data processing, NoSQL, natural language processing, and neural networks. He began programming in BASIC on a Sinclair Spectrum when he was eight years old, and to date, has collected a lot of experience using different operating systems, applications, and programming languages.

Overview

Section 1: Elasticsearch 5.x Solutions: Getting Started

Lecture 1 The Course Overview

Lecture 2 Understanding Cluster, Node and It's Services

Lecture 3 Managing Data

Lecture 4 Understanding Cluster, Replication, and Sharding

Lecture 5 Communicating with Elasticsearch

Lecture 6 Downloading and Installing Elasticsearch

Lecture 7 Setting Up Networking

Lecture 8 Setting Up a Node

Lecture 9 Setting Up Different Node Types

Lecture 10 Installing and Removing Plugins

Lecture 11 Changing Logging Settings

Lecture 12 Setting Up a Node Via Docker

Lecture 13 Using Explicit Mapping Creation

Lecture 14 Mapping Base Types, Arrays, and Object

Lecture 15 Mapping a Document and Using Dynamic Templates

Lecture 16 Managing Nested Objects, Child Document, and Multiple Mapping

Lecture 17 Mapping GeoPoint Field and GeoShape Field

Lecture 18 Mapping IP Field and Attachment Field

Lecture 19 Adding Metadata, Specifying Analyzer and Mapping Completion Field

Lecture 20 Creating, Deleting, and Opening/Closing an Index

Lecture 21 Putting and Getting a Mapping

Lecture 22 Reindexing, Refreshing, and Flushing

Lecture 23 Force Merge and Shrinking an Index

Lecture 24 Managing Index Settings and Using Index Aliases

Lecture 25 Indexing and Getting a Document

Lecture 26 Deleting and Updating a Document

Section 2: Elasticsearch 5.x Solutions – Mastering Elasticsearch Operations

Lecture 27 The Course Overview

Lecture 28 Searching, Sorting, and Highlighting Results

Lecture 29 Scrolling and Returning Inner Hits

Lecture 30 Suggesting Correct Query and Counting Matched Results

Lecture 31 Query and Query Profiling

Lecture 32 Deleting and Updating by Query

Lecture 33 Matching All Documents and Using a Boolean Query

Lecture 34 Using a Term and Prefix Query

Lecture 35 Using wildcard, regexp, and Span Query

Lecture 36 Using a Match and Query String Query

Lecture 37 Using Range, Common Term, and IDs Query

Lecture 38 Using the Function Score, Exist, and Template Query

Lecture 39 Using the has_child Query

Lecture 40 Using the has_parent Query

Lecture 41 Using the geo_bounding_box Query

Lecture 42 Using the geo_polygon Query

Lecture 43 Using the geo_distance Query

Lecture 44 Executing Stats and Terms Aggregation

Lecture 45 Executing Range and Histogram Aggregations

Lecture 46 Executing Filter Aggregations

Lecture 47 Executing Global, Geo Distance, and Children Aggregation

Lecture 48 Executing Nested, Top Hit, and Matrix Stats Aggregation

Lecture 49 Executing the geo_bound and geo_centroid Aggregation

Lecture 50 Painless Scripting

Lecture 51 Installing Additional Scripts Plugins

This Learning Path is for developers who want to learn Elasticsearch for advanced search and analytics.