What is the purpose of the ElasticsearchTemplate class in Spring Boot?

Table of Contents

• Introduction
• 1. Purpose of ElasticsearchTemplate (Deprecated)
  • Common Operations with ElasticsearchTemplate
• 2. Transition to ElasticsearchRestTemplate
  • Key Features of ElasticsearchRestTemplate:
• 3. Using ElasticsearchRestTemplate in Spring Boot
  • Example: Indexing Documents with ElasticsearchRestTemplate
  • Example: Searching Documents with ElasticsearchRestTemplate
• 4. Conclusion

Introduction

In Spring Boot applications that use Elasticsearch, the ElasticsearchTemplate class was previously an important component used for interacting with Elasticsearch indices. However, starting from Spring Data Elasticsearch 4.x, the ElasticsearchTemplate class has been deprecated in favor of using the ElasticsearchRestTemplate class. This change was made to simplify the integration with Elasticsearch and provide a more intuitive API for interacting with Elasticsearch in Spring Boot.

In this guide, we will discuss the purpose of the ElasticsearchTemplate class and its replacement, the ElasticsearchRestTemplate, in Spring Boot.

1. Purpose of ElasticsearchTemplate (Deprecated)

Before the introduction of ElasticsearchRestTemplate, the ElasticsearchTemplate class was used for managing Elasticsearch operations, including indexing documents, searching, and deleting. It offered a high-level abstraction over Elasticsearch's operations, making it easier for developers to interact with Elasticsearch without needing to write raw queries.

Common Operations with ElasticsearchTemplate

1. Indexing Documents: The ElasticsearchTemplate allowed developers to index documents in Elasticsearch by using methods like index().
2. Search Operations: It provided methods for querying Elasticsearch, including searching for documents using query builders.
3. Bulk Operations: The template facilitated bulk indexing and deleting of documents in Elasticsearch.

Example usage of the ElasticsearchTemplate for indexing:

2. Transition to ElasticsearchRestTemplate

As of Spring Data Elasticsearch 4.x, the ElasticsearchTemplate class was deprecated and replaced with ElasticsearchRestTemplate. The new ElasticsearchRestTemplate is a more modern, streamlined, and flexible approach for interacting with Elasticsearch.

The ElasticsearchRestTemplate leverages the RESTful client (RestHighLevelClient) and provides an easy-to-use API for Elasticsearch operations while integrating seamlessly into the Spring ecosystem. It simplifies operations like indexing, searching, and managing documents in Elasticsearch.

Key Features of ElasticsearchRestTemplate:

• Simplified API: Offers easy-to-use methods for Elasticsearch CRUD operations.
• Search Operations: Provides a simple interface to perform search operations using Elasticsearch’s query DSL.
• Integration with Spring Data: Works seamlessly with Spring Data repositories, making it easy to integrate with Spring Boot applications.

3. Using ElasticsearchRestTemplate in Spring Boot

Here's an example of how you would use ElasticsearchRestTemplate to perform operations like indexing documents and searching in a Spring Boot application:

Example: Indexing Documents with ElasticsearchRestTemplate

Example: Searching Documents with ElasticsearchRestTemplate

In this example, the ElasticsearchRestTemplate is used to search for products based on a keyword. The query is constructed using the Elasticsearch query DSL and executed via the search() method.

4. Conclusion

The ElasticsearchTemplate class was an important part of earlier versions of Spring Data Elasticsearch, providing a convenient abstraction for interacting with Elasticsearch. However, with the release of Spring Data Elasticsearch 4.x, it has been deprecated in favor of the ElasticsearchRestTemplate, which offers a more modern and flexible approach for interacting with Elasticsearch in Spring Boot applications. By using ElasticsearchRestTemplate, you can perform Elasticsearch CRUD operations, searches, and other complex tasks with ease, while keeping your Spring Boot application up to date with the latest Elasticsearch features.