Elasticsearch: Build, Query & Optimize with ELK

This course is part of Elastic Stack Mastery with Elasticsearch & AWS Specialization

Instructor: EDUCBA

Access provided by NMIMS Indore

5 modules

Gain insight into a topic and learn the fundamentals.

11 reviews

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

11 reviews

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Configure clusters and manage data with Elasticsearch APIs.
Build custom analyzers and execute advanced geo queries.
Integrate Elasticsearch with Logstash and Kibana for analytics.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

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This course is part of the Elastic Stack Mastery with Elasticsearch & AWS Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 5 modules in this course

By completing this course, learners will be able to design data models, configure clusters, build custom analyzers, and construct powerful queries in Elasticsearch. They will also master the use of Cluster, Indices, and Document APIs to manage distributed data efficiently. The course provides practical skills in configuring analyzers, avoiding split-brain issues, translating SQL queries into Elasticsearch DSL, and implementing advanced queries such as geo_point and geo_shape searches.

This course benefits learners by bridging the gap between theory and hands-on application, enabling them to use Elasticsearch with Logstash and Kibana for real-time data ingestion, indexing, and visualization. Unlike traditional database training, this course emphasizes distributed architecture, near real-time search, and practical troubleshooting strategies. What makes this course unique is its comprehensive coverage of Elasticsearch fundamentals through to advanced APIs, combined with real-world scenarios that highlight scalability, performance optimization, and query precision. Whether you are a beginner in NoSQL systems or an IT professional aiming to go beyond basics, this course equips you with the knowledge and confidence to apply Elasticsearch effectively in modern data-driven environments.

This module introduces learners to the ELK Stack, the basics of NoSQL, and the fundamental building blocks of Elasticsearch. Students will explore core concepts such as clusters, nodes, mappings, and data types, while also practicing with developer tools for real-time interaction.

What's included

10 videos4 assignments

10 videosTotal 84 minutes

Introduction to Comprehensive Elastic Stack (Elk Stack) Training11 minutes
Introduction to Nosql8 minutes
Installation of Elastic Search9 minutes
Important Key Definitions9 minutes
Cluster of of Elastic Search7 minutes
Mappings7 minutes
Mappings Continues6 minutes
Types of Datatable Elastic Search11 minutes
IP Keyword Date and Nested8 minutes
Dev Tools8 minutes

4 assignmentsTotal 60 minutes

Graded - Foundations of Elasticsearch and NoSQL30 minutes
Introduction to ELK Stack and NoSQL10 minutes
Core Concepts and Cluster Basics10 minutes
Data Types and Developer Tools10 minutes

This module explores how analyzers process text for search, the importance of tokenizers and filters, and Elasticsearch’s approach to transactions. It also covers cluster settings, discovery configuration, and techniques to prevent the split-brain problem.

What's included

12 videos4 assignments

12 videosTotal 112 minutes

Elasticsearch Analyzers11 minutes
Analyzers Consists of 3 Components12 minutes
Tokenized Inverted Index7 minutes
Token Filter7 minutes
Transactions12 minutes
Edge Gram and Synoym Analyzer10 minutes
Cluster Dot Name11 minutes
Discovery Configuration7 minutes
Gateway Configuration9 minutes
Field Data7 minutes
Split Brain9 minutes
How to Avoid the Split-Brain Problem12 minutes

4 assignmentsTotal 60 minutes

Graded - Analyzers, Transactions, and Cluster Configuration30 minutes
Understanding Analyzers10 minutes
Advanced Analyzer Techniques10 minutes
Cluster Configurations and Split-Brain Problem10 minutes

This module teaches learners to build and optimize queries in Elasticsearch. Topics include query vs. filter contexts, full-text queries, term-level queries, range queries, and advanced geospatial queries for real-world applications.

What's included

16 videos4 assignments

16 videosTotal 133 minutes

Query Context9 minutes
Filter Context8 minutes
Match Phrase Query11 minutes
Text and Title Query10 minutes
Term Level Query8 minutes
Term Level Query Continue7 minutes
More on Term Level Query7 minutes
Range Query9 minutes
Range Query Continue8 minutes
Prefix Exists Query11 minutes
Geo Shape Data Shape12 minutes
Geo Shape Data Shape Example5 minutes
Geo Point Sort Query and its Example8 minutes
Geo Distance Query Filter and its Example6 minutes
Geo Polygon Query6 minutes
Geo Polygon Query Continues8 minutes

4 assignmentsTotal 60 minutes

Graded - Querying in Elasticsearch30 minutes
Query and Filter Contexts10 minutes
Match, Term, and Range Queries10 minutes
Advanced Query Types10 minutes

This module focuses on effective data modeling and designing custom analyzers. Learners will explore SQL-to-DSL translation, dynamic templates, and strategies for managing multiple custom analyzers to improve indexing and search accuracy.

What's included

17 videos4 assignments

17 videosTotal 159 minutes

Working on Behaviour of Keywords12 minutes
Convert SQL Query to Elasticsearch Queries11 minutes
Convert SQL Query to Elasticsearch Queries Continues8 minutes
Working with Data Model9 minutes
More on Data Model11 minutes
Example of Data Model10 minutes
Example of Data Model Continues8 minutes
Working with Multiple Custom Analyzers8 minutes
Solution Multiple Custom Analyzers7 minutes
More on Multiple Custom Analyzers7 minutes
Dynamic Templates in Elastic Search Queries9 minutes
Example of Dynamic Templates11 minutes
Path and Pattern Dynamic Templates11 minutes
Example of Path and Pattern5 minutes
Working with Attributes Mapping in Dynamic Template12 minutes
Working with Attributes Mapping in Dynamic Template Continues9 minutes
Creating Mapped Attribute Area Object10 minutes

4 assignmentsTotal 60 minutes

Graded - Data Modeling and Custom Analyzers30 minutes
Keywords, SQL Conversion, and Data Models10 minutes
Custom Analyzers10 minutes
Dynamic Templates10 minutes

This module introduces Elasticsearch APIs for managing clusters, indices, and documents. Students will learn how to monitor cluster health, manage indices with aliases, and perform CRUD operations with Document APIs and the Bulk API.

What's included

13 videos4 assignments

13 videosTotal 143 minutes

Cluster APIs in Elasticsearch Queries13 minutes
Example of Cluster APIs11 minutes
Cluster Reroutes10 minutes
Example of Cluster Reroutes12 minutes
Indices APIs in Elastic Search Queries12 minutes
Example of Creating a Slot Index12 minutes
Open and Index APIs10 minutes
Get and Put Mapped in Index APIs11 minutes
Working Indices Aliases using Index APIs10 minutes
Document APIs in Elastic Search Queries11 minutes
Working with Get APIs in Document APIs8 minutes
Working with Delete APIs in Document APIs11 minutes
Working with Update and Bulk APIs in Document APIs12 minutes

4 assignmentsTotal 60 minutes

Graded - Elasticsearch APIs and Document Management30 minutes
Cluster APIs10 minutes
Indices APIs10 minutes
Document APIs10 minutes

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Instructor

Instructor ratings

(6 ratings)

EDUCBA

1,057 Courses265,158 learners

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EDUCBA

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Showing 3 of 11

Reviewed on Apr 4, 2026

A highly informative course that explains distributed search and data indexing clearly. The integration with Logstash and Kibana adds great practical value.

Reviewed on Apr 5, 2026

The course does a great job of simplifying Elasticsearch DSL and translating SQL queries into it. This makes it very useful for professionals transitioning from traditional databases.

Reviewed on Apr 6, 2026

An excellent course for understanding how to design scalable and high-performance search systems. The real-world scenarios enhance learning significantly.

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