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© 2013-2014 The original author(s)
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Preface
The Spring Data Elasticsearch project applies core Spring concepts to the development of solutions using the Elasticsearch Search Engine. We have povided a "template" as a high-level abstraction for storing,querying,sorting and faceting documents. You will notice similarities to the Spring data solr and mongodb support in the Spring Framework.
Project Metadata
-
Version Control -
git://github.com/BioMedCentralLtd/spring-data-elasticsearch.git
Requirements
Requires Elasticsearch 0.20.2 and above or optional dependency or not even that if you are using Embedded Node Client
Reference Documentation
Elasticsearch Repositories
This chapter includes details of the Elasticsearch repository implementation.
Introduction
Spring Namespace
The Spring Data Elasticsearch module contains a custom namespace allowing definition of repository beans as well as elements for instantiating a ElasticsearchServer .
Using the repositories element looks up Spring Data repositories as described in [repositories.create-instances] .
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans-3.1.xsd
http://www.springframework.org/schema/data/elasticsearch
http://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch-1.0.xsd">
<elasticsearch:repositories base-package="com.acme.repositories" />
</beans>Using the Transport Client or Node Client element registers an instance of Elasticsearch Server in the context.
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans-3.1.xsd
http://www.springframework.org/schema/data/elasticsearch
http://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch-1.0.xsd">
<elasticsearch:transport-client id="client" cluster-nodes="localhost:9300,someip:9300" />
</beans><?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans-3.1.xsd
http://www.springframework.org/schema/data/elasticsearch
http://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch-1.0.xsd">
<elasticsearch:node-client id="client" local="true"" />
</beans>Annotation based configuration
The Spring Data Elasticsearch repositories support cannot only be activated through an XML namespace but also using an annotation through JavaConfig.
@Configuration
@EnableElasticsearchRepositories(basePackages = "org/springframework/data/elasticsearch/repositories")
static class Config {
@Bean
public ElasticsearchOperations elasticsearchTemplate() {
return new ElasticsearchTemplate(nodeBuilder().local(true).node().client());
}
}The configuration above sets up an Embedded Elasticsearch Server which is used by the ElasticsearchTemplate . Spring Data Elasticsearch Repositories are activated using the @EnableElasticsearchRepositories annotation, which essentially carries the same attributes as the XML namespace does. If no base package is configured, it will use the one the configuration class resides in.
Elasticsearch Repositores using CDI
The Spring Data Elasticsearch repositories can also be set up using CDI functionality.
class ElasticsearchTemplateProducer {
@Produces
@ApplicationScoped
public ElasticsearchOperations createElasticsearchTemplate() {
return new ElasticsearchTemplate(nodeBuilder().local(true).node().client());
}
}
class ProductService {
private ProductRepository repository;
public Page<Product> findAvailableBookByName(String name, Pageable pageable) {
return repository.findByAvailableTrueAndNameStartingWith(name, pageable);
}
@Inject
public void setRepository(ProductRepository repository) {
this.repository = repository;
}
}Query methods
Query lookup strategies
The Elasticsearch module supports all basic query building feature as String,Abstract,Criteria or have it being derived from the method name.
Declared queries
Deriving the query from the method name is not always sufficient and/or may result in unreadable method names. In this case one might make either use of @Query annotation (see Using @Query Annotation ).
Query creation
Generally the query creation mechanism for Elasticsearch works as described in [repositories.query-methods] . Here’s a short example of what a Elasticsearch query method translates into:
public interface BookRepository extends Repository<Book, String>
{
List<Book> findByNameAndPrice(String name, Integer price);
}The method name above will be translated into the following Elasticsearch json query
{ "bool" :
{ "must" :
[
{ "field" : {"name" : "?"} },
{ "field" : {"price" : "?"} }
]
}
}A list of supported keywords for Elasticsearch is shown below.
| Keyword | Sample | Elasticsearch Query String |
|---|---|---|
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Using @Query Annotation
@Query annotation.public interface BookRepository extends ElasticsearchRepository<Book, String> {
@Query("{"bool" : {"must" : {"field" : {"name" : "?0"}}}}")
Page<Book> findByName(String name,Pageable pageable);
}Miscellaneous Elasticsearch Operation Support
This chapter covers additional support for Elasticsearch operations that cannot be directly accessed via the repository interface. It is recommended to add those operations as custom implementation as described in [repositories.custom-implementations] .
Filter Builder
Filter Builder improves query speed.
private ElasticsearchTemplate elasticsearchTemplate;
SearchQuery searchQuery = new NativeSearchQueryBuilder()
.withQuery(matchAllQuery())
.withFilter(boolFilter().must(termFilter("id", documentId)))
.build();
Page<SampleEntity> sampleEntities =
elasticsearchTemplate.queryForPage(searchQuery,SampleEntity.class);Using Scan And Scroll For Big Result Set
Elasticsearch has scan and scroll feature for getting big result set in chunks. ElasticsearchTemplate has scan and scroll methods that can be used as below.
SearchQuery searchQuery = new NativeSearchQueryBuilder()
.withQuery(matchAllQuery())
.withIndices("test-index")
.withTypes("test-type")
.withPageable(new PageRequest(0,1))
.build();
String scrollId = elasticsearchTemplate.scan(searchQuery,1000,false);
List<SampleEntity> sampleEntities = new ArrayList<SampleEntity>();
boolean hasRecords = true;
while (hasRecords){
Page<SampleEntity> page = elasticsearchTemplate.scroll(scrollId, 5000L , new ResultsMapper<SampleEntity>()
{
@Override
public Page<SampleEntity> mapResults(SearchResponse response) {
List<SampleEntity> chunk = new ArrayList<SampleEntity>();
for(SearchHit searchHit : response.getHits()){
if(response.getHits().getHits().length <= 0) {
return null;
}
SampleEntity user = new SampleEntity();
user.setId(searchHit.getId());
user.setMessage((String)searchHit.getSource().get("message"));
chunk.add(user);
}
return new PageImpl<SampleEntity>(chunk);
}
});
if(page != null) {
sampleEntities.addAll(page.getContent());
hasRecords = page.hasNextPage();
}
else{
hasRecords = false;
}
}
}