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ElasticSearch As You Have Never Known It Before

Want to build smarter search and recommendations? This Elasticsearch tutorial teaches you everything you need to know. Enroll today! Read more.

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Course Skill Level
Intermediate
Time Estimate
5h 40m

My name is Sergii Demianchuk. I have over 18 year’s experience as a software engineer. At my work I am mostly using next technologies: PHP, Python, Java, Javascript, Symfony, Flask, Spring, Vue, Docker, AWS Cloud, ML, Ansible, Jenkins, MySQL, Redis, ElasticSeach. I started my IT carrier as Engineer at national telecommunication Ukrainian networks. Than I worked as web full stack developer and IT manager for 10 years. After relocation to Poland at 2012, I continued my carrier path at Clicktran

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About This Course

Who this course is for:

  • Software Engineers and Developers (Looking for an Elasticsearch course)
  • Anyone interested in building advanced search systems (Master Elasticsearch with this comprehensive training)
  • Those wanting to create recommendation systems using Elasticsearch (This Elasticsearch course will teach you how)
  • NoSQL database enthusiasts (Get the most out of Elasticsearch with this course)
  • Current Elasticsearch users seeking to expand their knowledge (Take your Elasticsearch skills to the next level)

What you’ll learn: 

  • Master the core concepts of Elasticsearch (This Elasticsearch tutorial covers everything you need to know!)
  • Build powerful search systems with Elasticsearch (Become an Elasticsearch expert with this in-depth course!)
  • Create effective recommendation systems using Elasticsearch (Learn how to build recommender systems in Elasticsearch!)
  • Integrate Elasticsearch with PHP, Python, and Java libraries (This course teaches you to connect Elasticsearch with popular programming languages!)
  • Production-ready Elasticsearch: Setting up HA clusters and efficient indexing for millions of documents (Learn how to deploy Elasticsearch in production environments!)

Requirements: 

  • Basic knowledge of programming for the 4th section

Welcome to the Complete Elasticsearch Course

My name is Sergii Demianchuk, and I am currently the CTO at Clicktrans, one of the largest transport marketplaces in Europe. With 15 years of experience as a software engineer, Elasticsearch has become one of my favorite technologies. Over the past five years, I have used Elasticsearch in various large-scale projects, and now I am excited to share my practical knowledge with you.

Everybody knows Elasticsearch as a popular full-text search engine or as part of the ELK stack, but I will show you aspects of Elasticsearch that you might not be familiar with. This Elasticsearch tutorial will demonstrate how you can build very advanced search engines or even recommendation modules that are both more effective and simpler than similar systems built on machine learning technologies.

The real geo-power of Elasticsearch can be harnessed to build advanced search filters and aggregations. This course is structured to be beneficial for complete beginners as well as for those already working with Elasticsearch who wish to expand their practical knowledge. It is especially useful for those planning to build recommendation systems or advanced search mechanisms soon.

The course consists of five modules. The first module, designed for beginners, can be skipped by those already familiar with Elasticsearch. In this module, I will cover the basics: how to install and configure Elasticsearch using Docker, how data is organized, the importance of mapping, and the roles of tokenizers and analyzers.

In the second section, we will build an advanced search system step-by-step using a real example of a simplified booking.com version, exploring the geo-power of Elasticsearch. The third section focuses on recommendation systems, discussing their pros and cons, and we will build a real recommendation system for a virtual cleaning houses marketplace.

The fourth section provides real examples of integrating Elasticsearch with PHP, Python, and Java libraries. We will create a real microservice using best programming practices and interesting design patterns like the builder pattern and filter pattern, and address debugging potential issues.

The fifth and final section is about using Elasticsearch in production. Here, I will share my knowledge on setting up a highly available cluster, calculating shard sizes and storage requirements, efficiently indexing millions of documents, and maintaining zero downtime during reindexing.

Thank you for your interest. If you are ready to start, hit the button to start course now or view the test feature videos. See you in the course!

Additional Benefits

Besides the course content, you will receive several bonuses:

  • All course examples are available for free as resources for enrolled students.

Curious to learn more? My courses can unlock your hidden talents. Check them out!

Our Promise to You

By the end of this Elasticsearch training, you will have learned valuable skills in Elasticsearch. 

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - Introduction
Introduction 00:00:00
Essential Notice: How To Work With Postman 00:00:00
!!! Elasticsearch And Framework Upgrades – How To Use It Properly 00:00:00
Section 2 - ElasticSearch Basics
Lab Environment: Docker-Overview 00:00:00
Lab Environment: Install Docker At Linux 00:00:00
Lab Environment: Install Docker Windows 00:00:00
Lab Environment: Install Docker Mac OS 00:00:00
Lab Environment: Run Elasticsearch 7 Using Docker 00:00:00
Part 1 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Part 2 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Part 3 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Elasticsearch Basics: Theory 00:00:00
Elasticsearch Basics: Practice 00:00:00
DSL Queries And Mapping: Part 1 00:00:00
DSL Queries And Mapping: Part 2 00:00:00
Analyzers 00:00:00
DSL Combined Queries 00:00:00
Section 3 - Advanced Search Systems
Problem Definition And Requirements 00:00:00
Data Modeling 00:00:00
Mapping 00:00:00
Basic Search Query 00:00:00
Nested Query And Aggregation 00:00:00
Geo Power 00:00:00
Section 4 - Recommendation System
Theory And Task Definition 00:00:00
Mapping And Test Data 00:00:00
Constant Score And Function Score 00:00:00
Elasticsearch Solution 00:00:00
Section 5 - ElasticSearch And Programming Languages
Microservice: Task Definition And Architecture 00:00:00
Section 6 - PHP + Symfony + ElasticSearch
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
ElasticSearch ONGR Bundle And Model Data Layer 00:00:00
Prepare Test Data, Indexer Command 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Php 8, Symfony 5.4 00:00:00
Upgrade – ElasticSearch 8, Security Disabled 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 7 - Python + Flask + ElasticSearch
Fixes For Mac 00:00:00
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
Data Layer And Indexing Of Test Data 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Python 3.11, Flask 2.3 00:00:00
Upgrade – ElasticSearch 8, Security Disabled 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 8 - Java + Spring Boot + ElasticSearch
Essential Notice At Building Docker Application Image At First Time 00:00:00
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
Data Layer And Indexing Of Test Data 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Java 17, Spring Boot 3.0, ElasticSearch 8 With Disabled Security 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 9 - ElasticSearch At Production
!!! Elasticsearch At Aws With Terraform And Ansible 00:00:00
Inside A Cluster 00:00:00
Elasticsearch – Shards And Performance 00:00:00
Indexing Secrets 00:00:00
Section 10 - Additional Useful Information
Additional Useful Information 00:00:00

About This Course

Who this course is for:

  • Software Engineers and Developers (Looking for an Elasticsearch course)
  • Anyone interested in building advanced search systems (Master Elasticsearch with this comprehensive training)
  • Those wanting to create recommendation systems using Elasticsearch (This Elasticsearch course will teach you how)
  • NoSQL database enthusiasts (Get the most out of Elasticsearch with this course)
  • Current Elasticsearch users seeking to expand their knowledge (Take your Elasticsearch skills to the next level)

What you’ll learn: 

  • Master the core concepts of Elasticsearch (This Elasticsearch tutorial covers everything you need to know!)
  • Build powerful search systems with Elasticsearch (Become an Elasticsearch expert with this in-depth course!)
  • Create effective recommendation systems using Elasticsearch (Learn how to build recommender systems in Elasticsearch!)
  • Integrate Elasticsearch with PHP, Python, and Java libraries (This course teaches you to connect Elasticsearch with popular programming languages!)
  • Production-ready Elasticsearch: Setting up HA clusters and efficient indexing for millions of documents (Learn how to deploy Elasticsearch in production environments!)

Requirements: 

  • Basic knowledge of programming for the 4th section

Welcome to the Complete Elasticsearch Course

My name is Sergii Demianchuk, and I am currently the CTO at Clicktrans, one of the largest transport marketplaces in Europe. With 15 years of experience as a software engineer, Elasticsearch has become one of my favorite technologies. Over the past five years, I have used Elasticsearch in various large-scale projects, and now I am excited to share my practical knowledge with you.

Everybody knows Elasticsearch as a popular full-text search engine or as part of the ELK stack, but I will show you aspects of Elasticsearch that you might not be familiar with. This Elasticsearch tutorial will demonstrate how you can build very advanced search engines or even recommendation modules that are both more effective and simpler than similar systems built on machine learning technologies.

The real geo-power of Elasticsearch can be harnessed to build advanced search filters and aggregations. This course is structured to be beneficial for complete beginners as well as for those already working with Elasticsearch who wish to expand their practical knowledge. It is especially useful for those planning to build recommendation systems or advanced search mechanisms soon.

The course consists of five modules. The first module, designed for beginners, can be skipped by those already familiar with Elasticsearch. In this module, I will cover the basics: how to install and configure Elasticsearch using Docker, how data is organized, the importance of mapping, and the roles of tokenizers and analyzers.

In the second section, we will build an advanced search system step-by-step using a real example of a simplified booking.com version, exploring the geo-power of Elasticsearch. The third section focuses on recommendation systems, discussing their pros and cons, and we will build a real recommendation system for a virtual cleaning houses marketplace.

The fourth section provides real examples of integrating Elasticsearch with PHP, Python, and Java libraries. We will create a real microservice using best programming practices and interesting design patterns like the builder pattern and filter pattern, and address debugging potential issues.

The fifth and final section is about using Elasticsearch in production. Here, I will share my knowledge on setting up a highly available cluster, calculating shard sizes and storage requirements, efficiently indexing millions of documents, and maintaining zero downtime during reindexing.

Thank you for your interest. If you are ready to start, hit the button to start course now or view the test feature videos. See you in the course!

Additional Benefits

Besides the course content, you will receive several bonuses:

  • All course examples are available for free as resources for enrolled students.

Curious to learn more? My courses can unlock your hidden talents. Check them out!

Our Promise to You

By the end of this Elasticsearch training, you will have learned valuable skills in Elasticsearch. 

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - Introduction
Introduction 00:00:00
Essential Notice: How To Work With Postman 00:00:00
!!! Elasticsearch And Framework Upgrades – How To Use It Properly 00:00:00
Section 2 - ElasticSearch Basics
Lab Environment: Docker-Overview 00:00:00
Lab Environment: Install Docker At Linux 00:00:00
Lab Environment: Install Docker Windows 00:00:00
Lab Environment: Install Docker Mac OS 00:00:00
Lab Environment: Run Elasticsearch 7 Using Docker 00:00:00
Part 1 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Part 2 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Part 3 – Lab Environment: Run Elasticsearch 8 Using Docker 00:00:00
Elasticsearch Basics: Theory 00:00:00
Elasticsearch Basics: Practice 00:00:00
DSL Queries And Mapping: Part 1 00:00:00
DSL Queries And Mapping: Part 2 00:00:00
Analyzers 00:00:00
DSL Combined Queries 00:00:00
Section 3 - Advanced Search Systems
Problem Definition And Requirements 00:00:00
Data Modeling 00:00:00
Mapping 00:00:00
Basic Search Query 00:00:00
Nested Query And Aggregation 00:00:00
Geo Power 00:00:00
Section 4 - Recommendation System
Theory And Task Definition 00:00:00
Mapping And Test Data 00:00:00
Constant Score And Function Score 00:00:00
Elasticsearch Solution 00:00:00
Section 5 - ElasticSearch And Programming Languages
Microservice: Task Definition And Architecture 00:00:00
Section 6 - PHP + Symfony + ElasticSearch
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
ElasticSearch ONGR Bundle And Model Data Layer 00:00:00
Prepare Test Data, Indexer Command 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Php 8, Symfony 5.4 00:00:00
Upgrade – ElasticSearch 8, Security Disabled 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 7 - Python + Flask + ElasticSearch
Fixes For Mac 00:00:00
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
Data Layer And Indexing Of Test Data 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Python 3.11, Flask 2.3 00:00:00
Upgrade – ElasticSearch 8, Security Disabled 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 8 - Java + Spring Boot + ElasticSearch
Essential Notice At Building Docker Application Image At First Time 00:00:00
Local Environment 00:00:00
Front Controller And API Documentation 00:00:00
Search Criteria DTO Object 00:00:00
Data Layer And Indexing Of Test Data 00:00:00
Search Service And Query Builder 00:00:00
Upgrade – Java 17, Spring Boot 3.0, ElasticSearch 8 With Disabled Security 00:00:00
Upgrade – ElasticSearch 8, Turn On Security 00:00:00
Section 9 - ElasticSearch At Production
!!! Elasticsearch At Aws With Terraform And Ansible 00:00:00
Inside A Cluster 00:00:00
Elasticsearch – Shards And Performance 00:00:00
Indexing Secrets 00:00:00
Section 10 - Additional Useful Information
Additional Useful Information 00:00:00

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