Elasticsearch Masterclass For Java Spring Developers [2025] from Udemy

Elasticsearch Masterclass: Building Powerful Search Engine with Java & Spring Boot.

Note: This is NOT a logging/monitoring/analytics course.

As part of this course, we will learn the power of Elasticsearch 8 and build blazing fast, intelligent search solutions. This comprehensive, hands-on course is designed for Java/Spring Boot developers who want to master full-text search, fuzzy matching, powerful aggregations and robust search engine architecture from the fundamentals to advanced topics.

Why Learn Elasticsearch?

Power Modern Applications - Build scalable and intelligent search solutions for e-commerce, enterprise applications, and more.
Unlock Career Growth - Advance your skills and open doors to high-demand roles like Staff and Principal Engineer.
Effortless Scaling - Handle massive datasets and deliver lightning-fast search results.

What You will Learn:

Core Concepts - Grasp essential Elasticsearch concepts like indexing, sharding, replication, and distributed search. How it works behind the scenes with concepts like Inverted Index & Segments.
Full-Text Search Mastery - Master full-text search techniques, including BM25, tokenization, stemming, and boosting for optimal relevance.
Aggregations - Uncover valuable insights with bucket, metric, range, and histogram aggregations.
Data Modeling Excellence: Design efficient and effective data models using mappings, analyzers, and custom tokenizers.
High-Performance Techniques: Optimize indexing and query performance to handle millions of documents efficiently.
Autocomplete & Search Suggestions: Implement real-time search suggestions with completion suggesters and search-as-you-type features.
Spring Boot Integration: Seamlessly integrate Elasticsearch into your Java applications using Spring Boot.
Security & Scalability: Ensure secure and scalable search solutions with authentication, TLS, and best practices.

Hands-On Project

Apply your knowledge by building a Real World Search Engine with 5 Millions Documents using Spring Boot & Elasticsearch—with features like Auto Complete, Filtering & Providing Relevant Search Results.

By the end of this course, you will be confidently designing and deploying large scale, high performance search engines for real-world applications.

Start your Elasticsearch mastery today.

What's inside

Learning objectives

Core elasticsearch concepts - indexing, sharding, replication, and distributed search
Full-text search & relevance tuning - bm25, tokenization, stemming, and boosting
Aggregations - bucket, metric, range and historgram aggregations
Data modeling - mappings, analyzers, and custom tokenizers

Bulk indexing & query optimization - handling millions of documents efficiently
Autocomplete & search suggestions - implementing completion suggesters and search as you type
Spring boot integration - implement elasticsearch-powered search in java applications
Security & scaling - authentication, ssl/tls

Core elasticsearch concepts - indexing, sharding, replication, and distributed search
Full-text search & relevance tuning - bm25, tokenization, stemming, and boosting
Aggregations - bucket, metric, range and historgram aggregations
Data modeling - mappings, analyzers, and custom tokenizers
Bulk indexing & query optimization - handling millions of documents efficiently
Autocomplete & search suggestions - implementing completion suggesters and search as you type
Spring boot integration - implement elasticsearch-powered search in java applications
Security & scaling - authentication, ssl/tls

Syllabus

Introduction

Before You Enroll... The Need For Search - Why Elasticsearch!

Elasticsearch Setup

*** Humble Request & Resource ***

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches Elasticsearch 8, which is a recent version that includes performance improvements and new features, making it relevant for current development practices

Focuses on building search solutions, which is valuable for developers working on e-commerce, enterprise applications, and other data-intensive systems

Covers full-text search, fuzzy matching, and aggregations, which are essential techniques for building effective and user-friendly search experiences

Includes a hands-on project building a real-world search engine with 5 million documents, providing practical experience and portfolio material

Requires prior experience with Java and Spring Boot, so learners without this background may find the course challenging

Does not cover logging, monitoring, or analytics, so learners interested in these topics will need to seek out additional resources

Reviews summary

Elasticsearch search engine for java/spring boot

According to students, this course is a highly practical and well-structured guide for Java and Spring Boot developers looking to implement powerful search capabilities using Elasticsearch. Learners particularly appreciate the focus on building a real-world search engine project with millions of documents, highlighting the hands-on approach. The course covers core Elasticsearch concepts, full-text search relevance, aggregations, and crucial Spring Boot integration, which many find directly applicable to their professional work. While some specific topics might require additional exploration, the consensus is that it provides a solid foundation and equips developers with the necessary skills to confidently design and deploy search solutions.

Best suited for developers with prior experience.

"Definitely requires a good understanding of Java and Spring Boot beforehand."

"As a non-Java developer, I found the Spring Boot parts challenging, but the Elasticsearch content was still valuable."

"The pace assumes you are comfortable with the Spring ecosystem."

Covers recent Elasticsearch versions.

"Using Elasticsearch 8 was important for me, glad the course wasn't stuck on older versions."

"The content feels current and relevant to the latest developments in Elasticsearch."

"Good to see the course uses modern approaches compatible with recent releases."

Explanations are easy to follow.

"Instructor explains complex topics in a simple and understandable way."

"The course is well-paced and the lectures are concise, avoiding unnecessary jargon."

"I found the content delivery to be very clear, which helped me stay engaged."

Covers fundamental Elasticsearch topics well.

"The explanations of core concepts like indexing, sharding, and analyzers were clear and easy to grasp."

"Provides a solid understanding of how Elasticsearch works under the hood, which is essential."

"I finally understand the difference between term and match queries and how relevance scoring works."

Building a large-scale search engine is a key takeaway.

"Building the search engine with 5 million documents was challenging but incredibly rewarding and cemented my understanding."

"The hands-on project simulates a real-world scenario and provides invaluable experience."

"Applying the concepts learned in the project module made everything click for me. Great practical exercise."

Strong focus on integrating Elasticsearch with Java.

"The integration with Spring Boot was seamless and easy to follow, making it super practical for my job."

"Finally a course that shows how to properly use Elasticsearch *with* Spring Boot in a real project context."

"I learned exactly how to connect Elasticsearch to my Java application using the Spring Data Elasticsearch module."

Some advanced topics could be explored further.

"Could use more in-depth coverage on complex topics like optimization techniques for very specific query types."

"While it covers aggregations, I wish there were more advanced examples beyond the basics."

"A deeper dive into performance tuning for massive clusters would be a great addition."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Elasticsearch Masterclass For Java Spring Developers [2025] with these activities:

Review Core Java and Spring Boot Concepts

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Strengthen your understanding of Java and Spring Boot fundamentals to better grasp the Elasticsearch integration aspects of the course.

Browse courses on Spring Boot

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Review Java collections, data structures, and object-oriented principles.
Study Spring Boot's dependency injection and auto-configuration features.
Practice building simple REST APIs with Spring Boot.

Read 'Elasticsearch: The Definitive Guide'

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Gain a deeper understanding of Elasticsearch architecture and functionalities by studying this definitive guide.

View Elasticsearch: The Definitive Guide on Amazon

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Read the chapters on indexing, search, and data modeling.
Experiment with the examples provided in the book.

Experiment with Elasticsearch Queries using Kibana Dev Tools

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Practice writing and executing various Elasticsearch queries to become proficient in searching and filtering data.

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Set up a local Elasticsearch instance and Kibana.
Index sample data into Elasticsearch.
Write and execute different types of queries using Kibana Dev Tools.
Analyze the query results and optimize query performance.

Four other activities

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Write a Blog Post on Elasticsearch Analyzers

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Solidify your understanding of Elasticsearch analyzers by explaining their components and customization options in a blog post.

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Research different types of Elasticsearch analyzers.
Explain the components of an analyzer: character filters, tokenizers, and token filters.
Provide examples of custom analyzer configurations.
Publish the blog post on a platform like Medium or your personal blog.

Build a Simple Search Application with Spring Boot and Elasticsearch

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Apply your knowledge by building a search application that integrates Spring Boot and Elasticsearch.

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Set up a Spring Boot project with Elasticsearch dependencies.
Create an Elasticsearch index and map data fields.
Implement search functionality using Spring Data Elasticsearch.
Deploy the application to a local or cloud environment.

Read 'Elasticsearch in Action, Second Edition'

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Explore real-world applications of Elasticsearch and learn how to solve common search-related problems.

View Elasticsearch in Action on Amazon

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Read the chapters on data analysis and real-time analytics.
Implement the examples provided in the book using your own data.

Contribute to an Open Source Elasticsearch Project

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Deepen your understanding of Elasticsearch by contributing to an open-source project related to Elasticsearch or its integrations.

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Identify an open-source project related to Elasticsearch.
Explore the project's codebase and documentation.
Identify a bug or feature to work on.
Submit a pull request with your changes.

Career center

Learners who complete Elasticsearch Masterclass For Java Spring Developers [2025] will develop knowledge and skills that may be useful to these careers:

Search Engineer

A Search Engineer specializes in designing, implementing, and maintaining search engine technologies. The work involves optimizing search algorithms, indexing strategies, and query processing to deliver relevant and efficient search results. This Elasticsearch course helps Search Engineers understand the core concepts of Elasticsearch, which is a popular search engine. Through instruction on inverted indexes, sharding, and replication, the course helps build a foundation for designing scalable search solutions. Furthermore, the course teaches full-text search techniques, data modeling, and high-performance tuning. The project involving the creation of a search engine with millions of documents is especially useful for those seeking to become a Search Engineer.

See salaries and explore the career path for Search Engineer

Elasticsearch Developer

Elasticsearch Developers work specifically with the Elasticsearch search engine, building and maintaining search solutions. Their work includes configuring Elasticsearch clusters, designing data models, and developing queries. This Elasticsearch course helps Elasticsearch Developers to understand the core concepts of Elasticsearch, which is a popular search engine. Through instruction on inverted indexes, sharding, and replication, the course helps build a foundation for designing scalable search solutions. Furthermore, the course teaches full-text search techniques, data modeling, and high-performance tuning.

See salaries and explore the career path for Elasticsearch Developer

Search Specialist

Search Specialists are experts in search engine optimization and information retrieval. The work includes optimizing search algorithms, indexing strategies, and query processing to deliver relevant and efficient search results. This Elasticsearch course provides Search Specialists with a solid understanding of Elasticsearch. By mastering core concepts, techniques, data modeling, and high-performance tuning, Search Specialists enhance the search capabilities. The project involving the creation of a search engine with millions of documents may also be helpful for those seeking to become a Search Specialist.

See salaries and explore the career path for Search Specialist

Software Engineer

Software Engineers often integrate search functionalities into various applications. Their work includes designing and developing software solutions, writing code, and testing and debugging applications. This course equips Software Engineers with the skills to integrate Elasticsearch into Java applications using Spring Boot. By learning data modeling, indexing, query optimization, and autocomplete implementation, Software Engineers enhance the search capabilities of their applications. The hands-on project in this course, that involves building a search engine with autocomplete, filtering, and relevant results, may also be helpful for a Software Engineer. The course offers insights into building high-performance search engines, making it relevant and useful.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that allows data to be used effectively within an organization. This includes data pipelines, data warehousing, and data processing systems. Elasticsearch is often a key component in these systems, particularly for indexing and searching large volumes of data. This masterclass helps Data Engineers understand how to ingest, process, and index data into Elasticsearch. The course's coverage of data modeling, bulk indexing, and query optimization helps Data Engineers design efficient and scalable data solutions. Furthermore, the discussion of clustering, sharding, and replication may be useful for a Data Engineer.

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Backend Developer

Backend Developers focus on server-side logic, databases, and APIs. Their work includes building and maintaining the systems that support the functionality of web and mobile applications. This course provides Backend Developers with the skills to implement powerful search capabilities using Elasticsearch. The course's emphasis on Spring Boot integration, full-text search, and aggregations helps Backend Developers create robust and scalable search solutions. The project of building a real-world search engine, may also be useful to Backend Developers, as it offers practical experience in integrating Elasticsearch into backend systems.

See salaries and explore the career path for Backend Developer

Principal Engineer

Principal Engineers are technical leaders who provide guidance and mentorship to engineering teams. The work involves setting technical direction, driving innovation, and ensuring the quality and scalability of software systems. This course helps Principal Engineers deepen their understanding of Elasticsearch and its capabilities. By mastering core concepts, performance tuning, and security best practices, Principal Engineers can lead their teams in building high-performance search solutions. The course's hands-on project may be useful for evaluating new technologies and approaches.

See salaries and explore the career path for Principal Engineer

Application Architect

Application Architects design the structure and behavior of software applications. The work includes making high-level design choices and dictating technical standards, including platforms, coding standards, and tools. This course provides Application Architects with a comprehensive understanding of Elasticsearch and its integration with Java and Spring Boot. By learning about core concepts, data modeling, and performance tuning, Application Architects can design efficient and scalable search architectures. The discussion of security and scaling best practices is particularly valuable for ensuring the reliability and performance of applications.

See salaries and explore the career path for Application Architect

Search Consultant

Search Consultants advise organizations on how to improve their search capabilities. The work involves assessing current search systems, identifying areas for improvement, and recommending solutions. This course provides Search Consultants with a solid understanding of Elasticsearch and its capabilities. By mastering core concepts, performance tuning, and security best practices, Search Consultants can offer informed recommendations to their clients. The hands-on project building a search engine may also be useful for demonstrating the potential of Elasticsearch.

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Solutions Architect

Solutions Architects design and implement technology solutions for complex business problems. This work involves understanding business requirements, evaluating technology options, and creating architectural blueprints. This course may help Solutions Architects understand how Elasticsearch can be used to address search-related challenges. The course's coverage of Elasticsearch concepts, Spring Boot integration, and security best practices provides a foundation for designing effective search solutions. Additionally, the hands-on project building a search engine may be useful in evaluating the feasibility and performance of Elasticsearch in real-world scenarios.

See salaries and explore the career path for Solutions Architect

Technical Lead

Technical Leads oversee development teams and guide technical decisions. The work includes providing mentorship, ensuring code quality, and driving project delivery. This course may be useful for Technical Leads seeking to incorporate Elasticsearch into their projects. By understanding the core concepts, Spring Boot integration, and best practices, Technical Leads can guide their teams in building efficient and scalable search solutions. The course's hands-on project building a real-world search engine may also be useful for evaluating the feasibility and performance of Elasticsearch.

See salaries and explore the career path for Technical Lead

Data Scientist

Data Scientists analyze data to extract insights and inform decision-making. The work includes using statistical techniques, machine learning algorithms, and data visualization tools. While this course focuses on Elasticsearch for search engine implementation, Data Scientists may also find it useful for indexing and searching large datasets. The course's coverage of aggregations provides techniques for summarizing and analyzing data stored in Elasticsearch. Furthermore, the skills learned in data modeling and query optimization may be beneficial for improving the performance of data analysis tasks.

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Site Reliability Engineer

Site Reliability Engineers (SREs) ensure the reliability, performance, and scalability of software systems. This includes monitoring system health, automating tasks, and responding to incidents. Elasticsearch is often used for logging and monitoring applications, making it a key component of many SRE toolchains. While this course does not focus specifically on logging and monitoring, it does provide a solid foundation in Elasticsearch concepts and administration. SREs can use this knowledge to configure, optimize, and troubleshoot Elasticsearch clusters. The course's coverage of security and scaling is also highly relevant.

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Database Administrator

Database Administrators (DBAs) manage and maintain database systems. This includes tasks such as installation, configuration, performance monitoring, security, and backup/recovery. While Elasticsearch is not a traditional relational database, it is often used as a specialized data store for search and analytics. This course may help DBAs expand their skill set to include Elasticsearch administration. Learning about indexing, sharding, replication, and query optimization can help DBAs effectively manage Elasticsearch clusters. The course's coverage of security and scaling best practices is particularly valuable.

See salaries and explore the career path for Database Administrator

Quality Assurance Engineer

Quality Assurance Engineers are involved in evaluating the quality of software projects. The work involves testing and debugging applications. Understanding how Elasticsearch works may be useful for a Quality Assurance Engineer who tests search functionality in applications. The course offers insights into building high-performance search engines, making it relevant and useful. By learning data modeling, indexing, query optimization, and autocomplete implementation, Quality Assurance Engineers enhance the search capabilities of the applications they test.

See salaries and explore the career path for Quality Assurance Engineer

Elasticsearch Masterclass For Java Spring Developers [2025]

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What's inside

Learning objectives

Syllabus

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Reviews summary

Elasticsearch search engine for java/spring boot

Activities

Career center

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