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424 lines
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424 lines
16 KiB
Plaintext
image:https://jenkins.spring.io/buildStatus/icon?job=spring-data-elasticsearch%2Fmaster&subject=Moore%20(master)[link=https://jenkins.spring.io/view/SpringData/job/spring-data-elasticsearch/]
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image:https://jenkins.spring.io/buildStatus/icon?job=spring-data-elasticsearch%2F3.1.x&subject=Lovelace%20(3.1.x)[link=https://jenkins.spring.io/view/SpringData/job/spring-data-elasticsearch/]
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image:https://jenkins.spring.io/buildStatus/icon?job=spring-data-elasticsearch%2F2.1.x&subject=Ingalls%20(2.1.x)[link=https://jenkins.spring.io/view/SpringData/job/spring-data-elasticsearch/]
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= Spring Data Elasticsearch
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Spring Data implementation for ElasticSearch
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Spring Data makes it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud based data services as well as provide improved support for relational database technologies.
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The Spring Data Elasticsearch project provides integration with the https://www.elastic.co/[elasticsearch] search engine.
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== Guide
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* https://spring.io/projects/spring-data-elasticsearch#learn[Reference Documentation]
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* https://docs.spring.io/spring-data/elasticsearch/docs/current/api/[API Documentation]
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* https://spring.io/projects/spring-data[Spring Data Project]
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* https://jira.springsource.org/browse/DATAES[Issues (Spring Jira)]
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* https://stackoverflow.com/questions/tagged/spring-data-elasticsearch[Questions (Stack Overflow)]
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* https://github.com/BioMedCentralLtd/spring-data-elasticsearch-sample-application[Sample Test Application]
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== Quick Start
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This section is just short introduction, for more information refer to the https://spring.io/projects/spring-data-elasticsearch#learn[reference documentation].
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=== Versions
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The following table shows the Elasticsearch versions that are used by Spring Data Elasticsearch:
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[cols="^,^"]
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|===
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|Spring Data Elasticsearch |Elasticsearch
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|3.2.x |6.7.2
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|3.1.x |6.2.2
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|3.0.x |5.5.0
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|2.1.x |2.4.0
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|2.0.x |2.2.0
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|1.3.x |1.5.2
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|===
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=== Maven configuration
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Add the Maven dependency:
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[source,xml]
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----
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<dependency>
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<groupId>org.springframework.data</groupId>
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<artifactId>spring-data-elasticsearch</artifactId>
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<version>x.y.z.RELEASE</version>
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</dependency>
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----
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If you'd rather like the latest snapshots of the upcoming major version, use our Maven snapshot repository and declare
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the appropriate dependency version.
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[source,xml]
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----
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<dependency>
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<groupId>org.springframework.data</groupId>
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<artifactId>spring-data-elasticsearch</artifactId>
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<version>x.y.z.BUILD-SNAPSHOT</version>
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</dependency>
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<repository>
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<id>spring-libs-snapshot</id>
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<name>Spring Snapshot Repository</name>
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<url>https://repo.spring.io/libs-snapshot</url>
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</repository>
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----
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=== ElasticsearchRepository
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A default implementation of `ElasticsearchRepository`, aligning to the generic `Repository` Interfaces, is provided. Spring can do the `Repository` implementation for you depending on method names in the interface definition.
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For a detailed information about Spring Data, repositories and the supported query methods check the https://spring.io/projects/spring-data-elasticsearch#learn[reference documentation].
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[source,java]
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----
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@NoRepositoryBean
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public interface ElasticsearchRepository<T, ID> extends ElasticsearchCrudRepository<T, ID> {
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<S extends T> S index(S entity);
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Iterable<T> search(QueryBuilder query);
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Page<T> search(QueryBuilder query, Pageable pageable);
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Page<T> search(SearchQuery searchQuery);
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Page<T> searchSimilar(T entity, String[] fields, Pageable pageable);
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void refresh();
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Class<T> getEntityClass();
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}
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@NoRepositoryBean
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public interface ElasticsearchCrudRepository<T, ID> extends PagingAndSortingRepository<T, ID> {
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}
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----
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.Extending `ElasticsearchRepository` with custom methods:
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[source,java]
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----
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public interface BookRepository extends ElasticsearchRepository<Book, String> {
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List<Book> findByNameAndPrice(String name, Integer price);
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List<Book> findByNameOrPrice(String name, Integer price);
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Page<Book> findByName(String name, Pageable page);
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Page<Book> findByNameNot(String name, Pageable page);
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Page<Book> findByPriceBetween(int fromPrice, int toPrice, Pageable page);
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Page<Book> findByNameLike(String name, Pageable page);
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@Query("{\"bool\" : {\"must\" : {\"term\" : {\"message\" : \"?0\"}}}}")
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Page<Book> findByMessage(String message, Pageable pageable);
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}
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----
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.Indexing a single document using a `Repository`:
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[source,java]
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----
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@Autowired
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private SampleElasticsearchRepository repository;
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String documentId = "123456";
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SampleEntity sampleEntity = new SampleEntity();
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sampleEntity.setId(documentId);
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sampleEntity.setMessage("some message");
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repository.save(sampleEntity);
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----
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.Indexing multiple documents (bulk index) using a `Repository`:
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[source,java]
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----
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@Autowired
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private SampleElasticsearchRepository repository;
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String documentId = "123456";
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SampleEntity sampleEntity1 = new SampleEntity();
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sampleEntity1.setId(documentId);
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sampleEntity1.setMessage("some message");
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String documentId2 = "123457"
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SampleEntity sampleEntity2 = new SampleEntity();
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sampleEntity2.setId(documentId2);
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sampleEntity2.setMessage("test message");
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List<SampleEntity> sampleEntities = Arrays.asList(sampleEntity1, sampleEntity2);
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//bulk index
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repository.save(sampleEntities);
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----
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=== ElasticsearchTemplate and ElasticsearchRestTemplate
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`ElasticsearchTemplate` and `ElasticsearchRestTemplate` are the central support classes for Elasticsearch operations, both implement the `ElasticsearchOperations` interface that defines the methods to operate on an Elasticsearch cluster.
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`ElasticsearchTemplate` uses a `TransportClient`, whereas `ElasticsearchRestTemplate` uses the `RestHighLevelClient`. The `TransportClient` is deprecated in Elasticsearch 7, but until it is removed from Elasticsearch, the `ElasticsearchTemplate` will be supported as well.
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.Indexing a single document using `ElasticsearchTemplate`:
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[source,java]
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----
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String documentId = "123456";
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SampleEntity sampleEntity = new SampleEntity();
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sampleEntity.setId(documentId);
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sampleEntity.setMessage("some message");
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IndexQuery indexQuery = new IndexQueryBuilder().withId(sampleEntity.getId()).withObject(sampleEntity).build();
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elasticsearchTemplate.index(indexQuery);
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----
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.Indexing multiple documents (bulk index) using `ElasticsearchTemplate`:
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[source,java]
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----
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@Autowired
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private ElasticsearchTemplate elasticsearchTemplate;
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List<IndexQuery> indexQueries = new ArrayList<IndexQuery>();
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//first document
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String documentId = "123456";
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SampleEntity sampleEntity1 = new SampleEntity();
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sampleEntity1.setId(documentId);
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sampleEntity1.setMessage("some message");
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IndexQuery indexQuery1 = new IndexQueryBuilder().withId(sampleEntity1.getId()).withObject(sampleEntity1).build();
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indexQueries.add(indexQuery1);
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//second document
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String documentId2 = "123457";
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SampleEntity sampleEntity2 = new SampleEntity();
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sampleEntity2.setId(documentId2);
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sampleEntity2.setMessage("some message");
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IndexQuery indexQuery2 = new IndexQueryBuilder().withId(sampleEntity2.getId()).withObject(sampleEntity2).build()
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indexQueries.add(indexQuery2);
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//bulk index
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elasticsearchTemplate.bulkIndex(indexQueries);
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----
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.Searching entities using `ElasticsearchTemplate`:
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[source,java]
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----
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@Autowired
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private ElasticsearchTemplate elasticsearchTemplate;
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SearchQuery searchQuery = new NativeSearchQueryBuilder()
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.withQuery(queryString(documentId).field("id"))
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.build();
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Page<SampleEntity> sampleEntities = elasticsearchTemplate.queryForPage(searchQuery,SampleEntity.class);
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----
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=== Reactive Elasticsearch
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The `ReactiveElasticsearchClient`, introduced in Spring Data Elasticsearch 3.2, is a non official driver based on `WebClient`.
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It uses the request/response objects provided by the Elasticsearch core project.
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[source,java]
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----
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@Configuration
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public class Config {
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@Bean
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ReactiveElasticsearchClient client() {
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ClientConfiguration clientConfiguration = ClientConfiguration.builder()
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.connectedTo("localhost:9200", "localhost:9291")
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.build();
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return ReactiveRestClients.create(clientConfiguration);
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}
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}
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// If necessary, a BASIC_AUTH (user and password) header can be set with:
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@Configuration
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public class ConfigWithAuthentication {
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@Bean
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public ReactiveElasticsearchClient reactiveElasticsearchClient() {
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HttpHeaders defaultHeaders = new HttpHeaders();
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defaultHeaders.setBasicAuth(USER_NAME, USER_PASS);
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ClientConfiguration clientConfiguration = ClientConfiguration.builder()
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.connectedTo("localhost:9200", "localhost:9291")
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.withDefaultHeaders(defaultHeaders).build();
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return ReactiveRestClients.create(clientConfiguration);
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}
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}
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// ...
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Mono<IndexResponse> response = client.index(request ->
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request.index("spring-data")
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.type("elasticsearch")
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.id(randomID())
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.source(singletonMap("feature", "reactive-client"))
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.setRefreshPolicy(IMMEDIATE)
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);
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----
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The reactive client response, especially for search operations, is bound to the `from` (offset) & `size` (limit) options of the request.
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`ReactiveElasticsearchOperations` is the gateway to executing high level commands against an Elasticsearch cluster using the `ReactiveElasticsearchClient`.
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The easiest way of setting up the `ReactiveElasticsearchTemplate` is via `AbstractReactiveElasticsearchConfiguration`.
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[source,java]
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----
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@Configuration
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public class Config extends AbstractReactiveElasticsearchConfiguration {
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@Bean
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@Override
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public ReactiveElasticsearchClient reactiveElasticsearchClient() {
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// ...
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}
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}
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----
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If needed the `ReactiveElasticsearchTemplate` can be configured with default `RefreshPolicy` and `IndicesOptions` that get applied to the related requests by overriding the defaults of `refreshPolicy()` and `indicesOptions()`.
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[source,java]
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----
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template.save(new Person("Bruce Banner", 42))
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.doOnNext(System.out::println)
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.flatMap(person -> template.findById(person.id, Person.class))
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.doOnNext(System.out::println)
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.flatMap(person -> template.delete(person))
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.doOnNext(System.out::println)
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.flatMap(id -> template.count(Person.class))
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.doOnNext(System.out::println)
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.subscribe();
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----
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The above outputs the following sequence on the console.
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[source,bash]
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----
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> Person(id=QjWCWWcBXiLAnp77ksfR, name=Bruce Banner, age=42)
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> Person(id=QjWCWWcBXiLAnp77ksfR, name=Bruce Banner, age=42)
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> QjWCWWcBXiLAnp77ksfR
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> 0
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----
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=== XML Namespace
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You can set up repository scanning via xml configuration, which will happily create your repositories.
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.Using TransportClient
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[source,xml]
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----
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<?xml version="1.0" encoding="UTF-8"?>
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<beans xmlns="http://www.springframework.org/schema/beans"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
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xsi:schemaLocation="http://www.springframework.org/schema/data/elasticsearch https://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch.xsd
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http://www.springframework.org/schema/beans https://www.springframework.org/schema/beans/spring-beans.xsd">
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<elasticsearch:repositories base-package="com.xyz.acme"/>
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<elasticsearch:transport-client id="client" cluster-nodes="ip:9300,ip:9300" cluster-name="elasticsearch" />
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<bean name="elasticsearchTemplate" class="org.springframework.data.elasticsearch.core.ElasticsearchTemplate">
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<constructor-arg name="client" ref="client"/>
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</bean>
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</beans>
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----
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.Using RestClient
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[source,xml]
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----
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<?xml version="1.0" encoding="UTF-8"?>
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<beans xmlns="http://www.springframework.org/schema/beans"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
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xsi:schemaLocation="http://www.springframework.org/schema/data/elasticsearch https://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch.xsd
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http://www.springframework.org/schema/beans https://www.springframework.org/schema/beans/spring-beans.xsd">
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<elasticsearch:repositories base-package="com.xyz.acme"/>
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<elasticsearch:rest-client id="restClient" hosts="http://localhost:9200"/>
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<bean name="elasticsearchTemplate"
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class="org.springframework.data.elasticsearch.core.ElasticsearchRestTemplate">
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<constructor-arg name="client" ref="restClient"/>
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</bean>
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</beans>
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----
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== Help Pages
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* https://github.com/spring-projects/spring-data-elasticsearch/wiki/Geo-indexing-and-request[Geo distance and location search]
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* https://github.com/spring-projects/spring-data-elasticsearch/wiki/Custom-ObjectMapper[Custom object mapper]
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== Contributing to Spring Data
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Here are some ways for you to get involved in the community:
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* Get involved with the Spring community on Stack OverFlow. Please help out on the https://stackoverflow.com/questions/tagged/spring-data-elasticsearch[forum] by responding to questions and joining the debate.
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* Create https://jira.spring.io/browse/DATAES/[JIRA] tickets for bugs and new features and comment and vote on the ones that you are interested in.
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* Github is for social coding: if you want to write code, we encourage contributions through pull requests from https://help.github.com/forking/[forks of this repository]. If you want to contribute code this way, please reference a JIRA ticket as well covering the specific issue you are addressing.
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* Watch for upcoming articles on Spring by https://www.springsource.org/node/feed[subscribing] to springframework.org
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Before we accept a pull request we will need you to https://cla.pivotal.io/sign/spring[sign the Contributor License Agreement]. Signing the contributor’s agreement does not grant anyone commit rights to the main repository, but it does mean that we can accept your contributions, and you will get an author credit if we do. If you forget to do so, you'll be reminded when you submit a pull request. Active contributors might be asked to join the core team, and given the ability to merge pull requests.
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Code formatting for https://github.com/spring-projects/spring-data-build/tree/master/etc/ide[Eclipse and Intellij]
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https://github.com/spring-projects/spring-data-build/blob/master/CONTRIBUTING.adoc[More information about contributing to Spring Data]
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== Running CI tasks locally
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Since this pipeline is purely Docker-based, it's easy to:
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* Debug what went wrong on your local machine.
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* Test out a a tweak to your `test.sh` script before sending it out.
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* Experiment against a new image before submitting your pull request.
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All of these use cases are great reasons to essentially run what the CI server does on your local machine.
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IMPORTANT: To do this you must have Docker installed on your machine.
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1. `docker run -it --mount type=bind,source="$(pwd)",target=/spring-data-elasticsearch-github adoptopenjdk/openjdk8:latest /bin/bash`
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+
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This will launch the Docker image and mount your source code at `spring-data-elasticsearch-github`.
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+
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2. `cd spring-data-elasticsearch-github`
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+
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Next, run your tests from inside the container:
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+
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3. `./mvnw clean dependency:list test -Dsort` (or whatever profile you need to test out)
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Since the container is binding to your source, you can make edits from your IDE and continue to run build jobs.
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If you need to test the `build.sh` script, do this:
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1. `docker run -it --mount type=bind,source="$(pwd)",target=/spring-data-elasticsearch-github adoptopenjdk/openjdk8:latest /bin/bash`
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+
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This will launch the Docker image and mount your source code at `spring-data-elasticsearch-github`.
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+
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2. `cd spring-data-elasticsearch-github`
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+
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Next, try to package everything up from inside the container:
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+
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3. `./mvnw -Pci,snapshot -Dmaven.test.skip=true clean deploy`
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|
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IMPORTANT: This will attempt to deploy to artifactory, but without credentials, it will fail, leaving you simply with a built artifact.
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|
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NOTE: Docker containers can eat up disk space fast! From time to time, run `docker system prune` to clean out old images.
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|