Elasticsearch and Spring Boot: Build High-Performance Search Engines

In today's data-driven world, users expect search bars to be fast, smart, and highly relevant. Building these capabilities from scratch requires a solid understanding of full-text search concepts and how to integrate them seamlessly into your backend services. This text-based course guides you through the process of building robust, production-ready search engines using Spring Boot and Elasticsearch. You will start with core search theory and fundamental concepts before moving on to writing clean, modern Java code to index, query, and aggregate large datasets with low latency. What you'll learn: - Understand foundational search theory, including inverted indexes, tokenization, and document analysis. - Configure Elasticsearch mappings, custom analyzers, and sharding strategies for optimal performance. - Build complex search queries using full-text search, fuzzy matching, and relevance boosting. - Implement advanced search features like autocomplete, search-as-you-type, and real-time suggestions. - Integrate Elasticsearch with Spring Boot applications using the modern Java API Client. - Design aggregations to extract meaningful metrics, histograms, and buckets from search results. - Apply security best practices, including authentication and secure connections, to your search cluster. The course begins with essential terminology and the mechanics of search indexing, ensuring you have a strong theoretical foundation. As you progress through the written explanations and structured code examples, you will learn to build a scalable search service step-by-step. This course is designed for beginner to intermediate Java developers who want to add powerful search capabilities to their applications. No prior experience with Elasticsearch is required, though a basic understanding of Java and Spring Boot is helpful. Start reading today to master the art of building high-performance search engines.