How to use Elasticsearch in Spring Boot

Posted By :Rozi Ali |30th April 2021




Elasticsearch is an open, free and distributed search engine and an analytical tool built on top of Apache Lucene.

It first stores documents in an index. It uses powerful queries to search the index and runs its analytical functions on the data. Elasticsearch uses REST APIs to perform operations.


To use Elasticsearch in spring-boot, an interface is implemented as an alternative to its REST APIs. In this blog, we'll learn how to use Elasticsearch in Spring-boot.


Let's take a look using a step by step guide with an example.



1. Add Maven dependency



2. Connection with Elasticsearch Instance

To connect with Elasticsearch server, Spring data Elasticsearch uses JHLC(Java High Level REST Client)

public class ElasticsearchClientConfig extends AbstractElasticsearchConfiguration {
  public RestHighLevelClient elasticsearchClient() {

  final ClientConfiguration clientConfiguration = 

  return RestClients.create(clientConfiguration).rest();


3. Create a document 

@Document(indexName = "studentindex")
public class Student {
  private String id;
  private String name;
  private String course;
  private Integer semester;


Here, Studentindex is the index name for Elasticsearch, provided using @Document annotation.


There are two ways to access Elasticsearch using Springboot:

1. ElasticSearchRestTemplate: It is an implementation of the ElasticSearchOperations interface. Here, you can write your own queries.
2. ElasticSearchRepository Interface: ElasticSearch queries can be generated using repository's methods. It is easier and fast but problematic for writing complex queries.


1. ElasticSearchRepository for indexing and searching

We need to create a repository interface by extending ElasticSearchRepository interface.

public interface StudentRepository extends ElasticsearchRepository<Student, String> {

	List<Student> findByName(String name);
  	List<Student> findByCourseContaining(String course);


Now, StudentRepository inherits ElasticsearchRepository's methods. So, Whenever a save() or saveAll() methods invoke, data gets also inserted in index.
We can perform our searching using methods we defined in our StudentRepository.


2. ElasticSearchRestTemplate for indexing and searching

ElasticsearchRestTemplate implements the ElasticsearchOperations interface, which does the heavy lifting for low-level search and cluster actions.

This interface has the method index() for adding a single document and bulkIndex() for adding multiple documents to the index. Here i'm using index() method in this example.

public class StudentSearchService {

  private ElasticsearchOperations elasticsearchOperations;

  private static final String STUDENT_INDEX = "studentindex";

  public String createStudentIndex(Student student) {

    IndexQuery indexQuery = new IndexQueryBuilder()

    String documentId = elasticsearchOperations
     .index(indexQuery, IndexCoordinates.of(STUDENT_INDEX));

    return documentId;


now, to search documents, ElasticsearchRestTemplate has a search() method 

public class StudentSearchService {

  private ElasticsearchOperations elasticsearchOperations;

  private static final String STUDENT_INDEX = "studentindex";

  public void findStudentsByCourse(final String course) {

    QueryBuilder queryBuilder = 
      .matchQuery("course", course);

    Query searchQuery = new NativeSearchQueryBuilder()

    SearchHits<Student> studentHits = 

About Author

Rozi Ali

Rozi Ali is an accomplished software developer with extensive experience in the field of JAVA. She possesses a solid grasp of programming languages such as Java/Spring-boot, Python, and Typescript/Nodejs/GraphQL. Rozi has a strong background in Object-oriented programming (OOP) and is skilled in working with both relational databases like MySql, PostgreSQL and non-relational databases like MongoDb. She is proficient in REST APIs, Microservices, and code deployment, along with the development tools such as Jira, Git, and Bash. Additionally, Rozi has experience working with Cloud providers such as AWS and Azure. She has contributed significantly to a number of projects, including Konfer, VNS, Influsoft, VN Platform, QuickDialog, and Oodles-Dashboard.

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