Spring and Elasticsearch — Building Search Functionality into Your Application

3 min readMay 26, 2023

Introduction

In an era where data is increasingly growing, the ability to efficiently search and filter this data becomes critical. This post will discuss how to use Elasticsearch along with Spring, a powerful framework in Java, to build strong search functionality into your applications.

Elasticsearch is a distributed, open-source search and analytics engine built on Apache Lucene. It’s known for its speed, scalability, and ease of use, providing powerful, full-text search capabilities and real-time analytics in a distributed environment.

Spring is a popular framework in the Java ecosystem that makes it easy to build enterprise-grade applications. With Spring Data Elasticsearch, a sub-project of Spring Data, we can easily integrate Elasticsearch into a Spring application.

Setting Up Elasticsearch

Before integrating Elasticsearch into your Spring application, you need to install Elasticsearch. Once installed, you can start Elasticsearch on your local machine by navigating to the bin directory of the Elasticsearch distribution and running the following command:

./elasticsearch

Integrating Elasticsearch with Spring

With Elasticsearch running, we can now start integrating it with a Spring application. Add the Spring Data Elasticsearch dependency in your Maven pom.xml file.

<dependencies>
    ...
    <dependency>
        <groupId>org.springframework.data</groupId>
        <artifactId>spring-data-elasticsearch</artifactId>
        <version>4.2.2</version>
    </dependency>
    ...
</dependencies>

Configuring Elasticsearch in Spring

Spring Boot simplifies configuration but to set up Elasticsearch, you will need to configure a RestHighLevelClient bean that Spring Data Elasticsearch uses to connect to the Elasticsearch server. You can do this in your application's configuration file:

@Configuration
public class ElasticsearchConfig extends AbstractElasticsearchConfiguration {
 
    @Override
    @Bean
    public RestHighLevelClient elasticsearchClient() {
 
        final ClientConfiguration clientConfiguration = ClientConfiguration.builder()
            .connectedTo("localhost:9200")
            .build();
 
        return RestClients.create(clientConfiguration).rest();
    }
}

Creating an Elasticsearch Repository

Spring Data Elasticsearch uses the Repository pattern for data access. To use this, create an interface that extends ElasticsearchRepository. For instance:

public interface BookRepository extends ElasticsearchRepository<Book, String> {
    List<Book> findByTitle(String title);
}

Here, Book is an entity class that should be annotated with @Document to be recognized by Elasticsearch, and findByTitle is a derived query method.

Searching with Elasticsearch

With everything set up, you can now use Elasticsearch to search your data. Use the BookRepository to search for books:

List<Book> books = bookRepository.findByTitle("Spring and Elasticsearch");

This code will return all books with “Spring and Elasticsearch” in their title. Elasticsearch also supports more complex queries, including fuzzy search, wildcard, range, and more.

Conclusion

Integrating Elasticsearch with a Spring application can greatly enhance its search functionality. With the convenience provided by Spring Data Elasticsearch, this integration becomes straightforward, simplifying the data access layer and empowering you to build scalable applications with fast and powerful search capabilities, perfect for today’s data-driven world. While the examples provided offer a basic integration and use case, it’s worth noting that Elasticsearch hosts a wide array of advanced features such as filters, analyzers, and aggregators, which you can leverage as your application’s search requirements grow. With the combined strengths of Spring and Elasticsearch, you are well-equipped to handle the challenges of efficiently searching through large amounts of data and providing real-time analytics, thereby enhancing user experience.