Integrating Elasticsearch with Spring Boot

Spring Data Elasticsearch provides repository-style integration with Elasticsearch through the Elasticsearch REST client, with support for derived query methods, @Query annotations, and the native client for full query control.

Setup

• Add spring-boot-starter-data-elasticsearch; configure spring.elasticsearch.uris=http://localhost:9200; the auto-configuration wires the ElasticsearchClient and ElasticsearchRestTemplate
• Annotate your model with @Document(indexName = "products") and field-level mappings with @Field(type = FieldType.Text) or @Field(type = FieldType.Keyword); Spring Data creates the index with the declared mapping on startup if it doesn't exist

Repository layer

• Extend ElasticsearchRepository — you get save(), findById(), deleteById(), and derived query methods for free
• findByNameAndStatus(String name, String status) generates a bool.must query with match on name and term on status — Spring Data infers the query from the method name

`ElasticsearchRestTemplate` for complex queries

• When derived methods can't express the query — bool with filter, nested aggregations, script score — use ElasticsearchRestTemplate.search(NativeSearchQuery, Class)
• Build the query with NativeSearchQueryBuilder: new NativeSearchQueryBuilder().withQuery(QueryBuilders.boolQuery().must(matchQuery("name", name)).filter(termQuery("status", "active"))).build()

Managing index lifecycle

• Use @Setting to configure the analyzer at the index level — define a custom analyzer with edge n-gram tokenizer for autocomplete queries
• Re-indexing: create a new index with the updated mapping, use _reindex to copy documents, then update the alias; Spring Data's IndexOperations.reindex() wraps this flow