For the latest stable version, please use Spring Data Elasticsearch 5.4.0! |
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 Custom Repository Implementations .
Index settings
When creating Elasticsearch indices with Spring Data Elasticsearch different index settings can be defined by using the @Setting
annotation.
The following arguments are available:
-
useServerConfiguration
does not send any settings parameters, so the Elasticsearch server configuration determines them. -
settingPath
refers to a JSON file defining the settings that must be resolvable in the classpath -
shards
the number of shards to use, defaults to 1 -
replicas
the number of replicas, defaults to 1 -
refreshIntervall
, defaults to "1s" -
indexStoreType
, defaults to "fs"
It is as well possible to define index sorting (check the linked Elasticsearch documentation for the possible field types and values):
@Document(indexName = "entities")
@Setting(
sortFields = { "secondField", "firstField" }, (1)
sortModes = { Setting.SortMode.max, Setting.SortMode.min }, (2)
sortOrders = { Setting.SortOrder.desc, Setting.SortOrder.asc },
sortMissingValues = { Setting.SortMissing._last, Setting.SortMissing._first })
class Entity {
@Nullable
@Id private String id;
@Nullable
@Field(name = "first_field", type = FieldType.Keyword)
private String firstField;
@Nullable @Field(name = "second_field", type = FieldType.Keyword)
private String secondField;
// getter and setter...
}
1 | when defining sort fields, use the name of the Java property (firstField), not the name that might be defined for Elasticsearch (first_field) |
2 | sortModes , sortOrders and sortMissingValues are optional, but if they are set, the number of entries must match the number of sortFields elements |
Index Mapping
When Spring Data Elasticsearch creates the index mapping with the IndexOperations.createMapping()
methods, it uses the annotations described in Mapping Annotation Overview, especially the @Field
annotation.
In addition to that it is possible to add the @Mapping
annotation to a class.
This annotation has the following properties:
-
mappingPath
a classpath resource in JSON format; if this is not empty it is used as the mapping, no other mapping processing is done. -
enabled
when set to false, this flag is written to the mapping and no further processing is done. -
dateDetection
andnumericDetection
set the corresponding properties in the mapping when not set toDEFAULT
. -
dynamicDateFormats
when this String array is not empty, it defines the date formats used for automatic date detection. -
runtimeFieldsPath
a classpath resource in JSON format containing the definition of runtime fields which is written to the index mappings, for example:
{
"day_of_week": {
"type": "keyword",
"script": {
"source": "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))"
}
}
}
Filter Builder
Filter Builder improves query speed.
private ElasticsearchOperations operations;
IndexCoordinates index = IndexCoordinates.of("sample-index");
Query query = NativeQuery.builder()
.withQuery(q -> q
.matchAll(ma -> ma))
.withFilter( q -> q
.bool(b -> b
.must(m -> m
.term(t -> t
.field("id")
.value(documentId))
)))
.build();
SearchHits<SampleEntity> sampleEntities = operations.search(query, SampleEntity.class, index);
Using Scroll For Big Result Set
Elasticsearch has a scroll API for getting big result set in chunks.
This is internally used by Spring Data Elasticsearch to provide the implementations of the <T> SearchHitsIterator<T> SearchOperations.searchForStream(Query query, Class<T> clazz, IndexCoordinates index)
method.
IndexCoordinates index = IndexCoordinates.of("sample-index");
Query searchQuery = NativeQuery.builder()
.withQuery(q -> q
.matchAll(ma -> ma))
.withFields("message")
.withPageable(PageRequest.of(0, 10))
.build();
SearchHitsIterator<SampleEntity> stream = elasticsearchOperations.searchForStream(searchQuery, SampleEntity.class,
index);
List<SampleEntity> sampleEntities = new ArrayList<>();
while (stream.hasNext()) {
sampleEntities.add(stream.next());
}
stream.close();
There are no methods in the SearchOperations
API to access the scroll id, if it should be necessary to access this, the following methods of the AbstractElasticsearchTemplate
can be used (this is the base implementation for the different ElasticsearchOperations
implementations):
@Autowired ElasticsearchOperations operations;
AbstractElasticsearchTemplate template = (AbstractElasticsearchTemplate)operations;
IndexCoordinates index = IndexCoordinates.of("sample-index");
Query query = NativeQuery.builder()
.withQuery(q -> q
.matchAll(ma -> ma))
.withFields("message")
.withPageable(PageRequest.of(0, 10))
.build();
SearchScrollHits<SampleEntity> scroll = template.searchScrollStart(1000, query, SampleEntity.class, index);
String scrollId = scroll.getScrollId();
List<SampleEntity> sampleEntities = new ArrayList<>();
while (scroll.hasSearchHits()) {
sampleEntities.addAll(scroll.getSearchHits());
scrollId = scroll.getScrollId();
scroll = template.searchScrollContinue(scrollId, 1000, SampleEntity.class);
}
template.searchScrollClear(scrollId);
To use the Scroll API with repository methods, the return type must defined as Stream
in the Elasticsearch Repository.
The implementation of the method will then use the scroll methods from the ElasticsearchTemplate.
interface SampleEntityRepository extends Repository<SampleEntity, String> {
Stream<SampleEntity> findBy();
}
Sort options
In addition to the default sort options described in Paging and Sorting, Spring Data Elasticsearch provides the class org.springframework.data.elasticsearch.core.query.Order
which derives from org.springframework.data.domain.Sort.Order
.
It offers additional parameters that can be sent to Elasticsearch when specifying the sorting of the result (see www.elastic.co/guide/en/elasticsearch/reference/7.15/sort-search-results.html).
There also is the org.springframework.data.elasticsearch.core.query.GeoDistanceOrder
class which can be used to have the result of a search operation ordered by geographical distance.
If the class to be retrieved has a GeoPoint
property named location, the following Sort
would sort the results by distance to the given point:
Sort.by(new GeoDistanceOrder("location", new GeoPoint(48.137154, 11.5761247)))
Runtime Fields
From version 7.12 on Elasticsearch has added the feature of runtime fields (www.elastic.co/guide/en/elasticsearch/reference/7.12/runtime.html). Spring Data Elasticsearch supports this in two ways:
Runtime field definitions in the index mappings
The first way to define runtime fields is by adding the definitions to the index mappings (see www.elastic.co/guide/en/elasticsearch/reference/7.12/runtime-mapping-fields.html). To use this approach in Spring Data Elasticsearch the user must provide a JSON file that contains the corresponding definition, for example:
{
"day_of_week": {
"type": "keyword",
"script": {
"source": "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))"
}
}
}
The path to this JSON file, which must be present on the classpath, must then be set in the @Mapping
annotation of the entity:
@Document(indexName = "runtime-fields")
@Mapping(runtimeFieldsPath = "/runtime-fields.json")
public class RuntimeFieldEntity {
// properties, getter, setter,...
}
Runtime fields definitions set on a Query
The second way to define runtime fields is by adding the definitions to a search query (see www.elastic.co/guide/en/elasticsearch/reference/7.12/runtime-search-request.html). The following code example shows how to do this with Spring Data Elasticsearch :
The entity used is a simple object that has a price
property:
@Document(indexName = "some_index_name")
public class SomethingToBuy {
private @Id @Nullable String id;
@Nullable @Field(type = FieldType.Text) private String description;
@Nullable @Field(type = FieldType.Double) private Double price;
// getter and setter
}
The following query uses a runtime field that calculates a priceWithTax
value by adding 19% to the price and uses this value in the search query to find all entities where priceWithTax
is higher or equal than a given value:
RuntimeField runtimeField = new RuntimeField("priceWithTax", "double", "emit(doc['price'].value * 1.19)");
Query query = new CriteriaQuery(new Criteria("priceWithTax").greaterThanEqual(16.5));
query.addRuntimeField(runtimeField);
SearchHits<SomethingToBuy> searchHits = operations.search(query, SomethingToBuy.class);
This works with every implementation of the Query
interface.
Point In Time (PIT) API
ElasticsearchOperations
supports the point in time API of Elasticsearch (see www.elastic.co/guide/en/elasticsearch/reference/8.3/point-in-time-api.html).
The following code snippet shows how to use this feature with a fictional Person
class:
ElasticsearchOperations operations; // autowired
Duration tenSeconds = Duration.ofSeconds(10);
String pit = operations.openPointInTime(IndexCoordinates.of("person"), tenSeconds); (1)
// create query for the pit
Query query1 = new CriteriaQueryBuilder(Criteria.where("lastName").is("Smith"))
.withPointInTime(new Query.PointInTime(pit, tenSeconds)) (2)
.build();
SearchHits<Person> searchHits1 = operations.search(query1, Person.class);
// do something with the data
// create 2nd query for the pit, use the id returned in the previous result
Query query2 = new CriteriaQueryBuilder(Criteria.where("lastName").is("Miller"))
.withPointInTime(
new Query.PointInTime(searchHits1.getPointInTimeId(), tenSeconds)) (3)
.build();
SearchHits<Person> searchHits2 = operations.search(query2, Person.class);
// do something with the data
operations.closePointInTime(searchHits2.getPointInTimeId()); (4)
1 | create a point in time for an index (can be multiple names) and a keep-alive duration and retrieve its id |
2 | pass that id into the query to search together with the next keep-alive value |
3 | for the next query, use the id returned from the previous search |
4 | when done, close the point in time using the last returned id |
Search Template support
Use of the search template API is supported.
To use this, it first is necessary to create a stored script.
The ElasticsearchOperations
interface extends ScriptOperations
which provides the necessary functions.
The example used here assumes that we have Person
entity with a property named firstName
.
A search template script can be saved like this:
import org.springframework.data.elasticsearch.core.ElasticsearchOperations;
import org.springframework.data.elasticsearch.core.script.Script;
operations.putScript( (1)
Script.builder()
.withId("person-firstname") (2)
.withLanguage("mustache") (3)
.withSource(""" (4)
{
"query": {
"bool": {
"must": [
{
"match": {
"firstName": "{{firstName}}" (5)
}
}
]
}
},
"from": "{{from}}", (6)
"size": "{{size}}" (7)
}
""")
.build()
);
1 | Use the putScript() method to store a search template script |
2 | The name / id of the script |
3 | Scripts that are used in search templates must be in the mustache language. |
4 | The script source |
5 | The search parameter in the script |
6 | Paging request offset |
7 | Paging request size |
To use a search template in a search query, Spring Data Elasticsearch provides the SearchTemplateQuery
, an implementation of the org.springframework.data.elasticsearch.core.query.Query
interface.
In the following code, we will add a call using a search template query to a custom repository implementation (see Custom Repository Implementations) as an example how this can be integrated into a repository call.
We first define the custom repository fragment interface:
interface PersonCustomRepository {
SearchPage<Person> findByFirstNameWithSearchTemplate(String firstName, Pageable pageable);
}
The implementation of this repository fragment looks like this:
public class PersonCustomRepositoryImpl implements PersonCustomRepository {
private final ElasticsearchOperations operations;
public PersonCustomRepositoryImpl(ElasticsearchOperations operations) {
this.operations = operations;
}
@Override
public SearchPage<Person> findByFirstNameWithSearchTemplate(String firstName, Pageable pageable) {
var query = SearchTemplateQuery.builder() (1)
.withId("person-firstname") (2)
.withParams(
Map.of( (3)
"firstName", firstName,
"from", pageable.getOffset(),
"size", pageable.getPageSize()
)
)
.build();
SearchHits<Person> searchHits = operations.search(query, Person.class); (4)
return SearchHitSupport.searchPageFor(searchHits, pageable);
}
}
1 | Create a SearchTemplateQuery |
2 | Provide the id of the search template |
3 | The parameters are passed in a Map<String,Object> |
4 | Do the search in the same way as with the other query types. |
Nested sort
Spring Data Elasticsearch supports sorting within nested objects (www.elastic.co/guide/en/elasticsearch/reference/8.9/sort-search-results.html#nested-sorting)
The following example, taken from the org.springframework.data.elasticsearch.core.query.sort.NestedSortIntegrationTests
class, shows how to define the nested sort.
var filter = StringQuery.builder("""
{ "term": {"movies.actors.sex": "m"} }
""").build();
var order = new org.springframework.data.elasticsearch.core.query.Order(Sort.Direction.DESC,
"movies.actors.yearOfBirth")
.withNested(
Nested.builder("movies")
.withNested(
Nested.builder("movies.actors")
.withFilter(filter)
.build())
.build());
var query = Query.findAll().addSort(Sort.by(order));
About the filter query: It is not possible to use a CriteriaQuery
here, as this query would be converted into a Elasticsearch nested query which does not work in the filter context. So only StringQuery
or NativeQuery
can be used here. When using one of these, like the term query above, the Elasticsearch field names must be used, so take care, when these are redefined with the @Field(name="…")
definition.
For the definition of the order path and the nested paths, the Java entity property names should be used.