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Use Hibernate Search in Standalone mode with Elasticsearch/OpenSearch

You have a Quarkus application? You want to provide a full-featured full-text search to your users? You’re at the right place.

With this guide, you’ll learn how to index entities into an Elasticsearch or OpenSearch cluster in a heartbeat with Hibernate Search. We will also explore how you can query your Elasticsearch or OpenSearch cluster using the Hibernate Search API.

If you want to index Hibernate ORM entities, see this dedicated guide instead.

先决条件

完成这个指南,你需要:

  • 大概20 minutes

  • 编辑器

  • JDK 17+ installed with JAVA_HOME configured appropriately

  • Apache Maven 3.9.6

  • A working container runtime (Docker or Podman)

  • 如果你愿意的话,还可以选择使用Quarkus CLI

  • 如果你想构建原生可执行程序,可以选择安装Mandrel或者GraalVM,并正确配置(或者使用Docker在容器中进行构建)

架构

The application described in this guide allows to manage a (simple) library: you manage authors and their books.

The entities are stored and indexed in an Elasticsearch cluster.

解决方案

我们建议您按照下一节的说明逐步创建应用程序。然而,您可以直接转到已完成的示例。

克隆 Git 仓库。 git clone https://github.com/quarkusio/quarkus-quickstarts.git ,或者下载一个 存档

The solution is located in the hibernate-search-standalone-elasticsearch-quickstart directory.

The provided solution contains a few additional elements such as tests and testing infrastructure.

创建Maven项目

首先,我们需要一个新的工程项目。用以下命令创建一个新项目:

CLI
quarkus create app org.acme:hibernate-search-standalone-elasticsearch-quickstart \
    --extension='hibernate-search-standalone-elasticsearch,rest-jackson' \
    --no-code
cd hibernate-search-standalone-elasticsearch-quickstart

创建Grade项目,请添加 --gradle 或者 --gradle-kotlin-dsl 参数。

For more information about how to install and use the Quarkus CLI, see the Quarkus CLI guide.

Maven
mvn io.quarkus.platform:quarkus-maven-plugin:3.11.3:create \
    -DprojectGroupId=org.acme \
    -DprojectArtifactId=hibernate-search-standalone-elasticsearch-quickstart \
    -Dextensions='hibernate-search-standalone-elasticsearch,rest-jackson' \
    -DnoCode
cd hibernate-search-standalone-elasticsearch-quickstart

创建Grade项目,请添加 -DbuildTool=gradle 或者 -DbuildTool=gradle-kotlin-dsl 参数。

For Windows users:

  • If using cmd, (don’t use backward slash \ and put everything on the same line)

  • If using Powershell, wrap -D parameters in double quotes e.g. "-DprojectArtifactId=hibernate-search-standalone-elasticsearch-quickstart"

This command generates a Maven structure importing the following extensions:

  • Hibernate Search Standalone + Elasticsearch,

  • Quarkus REST (formerly RESTEasy Reactive) and Jackson.

If you already have your Quarkus project configured, you can add the hibernate-search-standalone-elasticsearch extension to your project by running the following command in your project base directory:

CLI
quarkus extension add hibernate-search-standalone-elasticsearch
Maven
./mvnw quarkus:add-extension -Dextensions='hibernate-search-standalone-elasticsearch'
Gradle
./gradlew addExtension --extensions='hibernate-search-standalone-elasticsearch'

这将在你的 pom.xml 中添加以下内容:

pom.xml
<dependency>
    <groupId>io.quarkus</groupId>
    <artifactId>quarkus-hibernate-search-standalone-elasticsearch</artifactId>
</dependency>
build.gradle
implementation("io.quarkus:quarkus-hibernate-search-standalone-elasticsearch")

Creating the bare classes

First, let’s create our Book and Author classes in the model subpackage.

package org.acme.hibernate.search.elasticsearch.model;

import java.util.List;
import java.util.Objects;

public class Author {

    public UUID id; (1)

    public String firstName;

    public String lastName;

    public List<Book> books;

    public Author(UUID id, String firstName, String lastName, List<Book> books) {
        this.id = id;
        this.firstName = firstName;
        this.lastName = lastName;
        this.books = books;
    }
}
1 We’re using public fields here, because it’s shorter and there is no expectation of encapsulation on what is essentially a data class.

However, if you prefer using private fields with getters/setters, that’s totally fine and will work perfectly as long as the getters/setters follow the JavaBeans naming convention (getSomething()/isSomething()/setSomething(…​)).

package org.acme.hibernate.search.elasticsearch.model;

import java.util.Objects;

public class Book {

    public UUID id;

    public String title;

    public Book(UUID id, String title) {
        this.id = id;
        this.title = title;
    }
}

Using Hibernate Search annotations

Enabling full text search capabilities for our classes is as simple as adding a few annotations.

Let’s edit the Author entity to include this content:

package org.acme.hibernate.search.elasticsearch.model;

import java.util.ArrayList;
import java.util.List;
import java.util.Objects;
import java.util.UUID;

import org.hibernate.search.engine.backend.types.Sortable;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.DocumentId;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.FullTextField;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.IdProjection;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.Indexed;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.IndexedEmbedded;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.KeywordField;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.ProjectionConstructor;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.SearchEntity;

@SearchEntity (1)
@Indexed (2)
public class Author {

    @DocumentId (3)
    public UUID id;

    @FullTextField(analyzer = "name") (4)
    @KeywordField(name = "firstName_sort", sortable = Sortable.YES, normalizer = "sort") (5)
    public String firstName;

    @FullTextField(analyzer = "name")
    @KeywordField(name = "lastName_sort", sortable = Sortable.YES, normalizer = "sort")
    public String lastName;

    @IndexedEmbedded (6)
    public List<Book> books = new ArrayList<>();

    public Author(UUID id, String firstName, String lastName) {
        this.id = id;
        this.firstName = firstName;
        this.lastName = lastName;
    }

    @ProjectionConstructor (7)
    public Author(@IdProjection UUID id, String firstName, String lastName, List<Book> books) {
        this( id, firstName, lastName );
        this.books = books;
    }
}
1 First, let’s mark the Author type as an entity type. In short, this implies the Author type it has its own, distinct lifecycle (not tied to another type), and that every `BookAuthor instance carries an immutable, unique identifier.
2 Then, let’s use the @Indexed annotation to register our Author entity as part of the full text index.
3 And let’s end the mandatory configuration by defining a document identifier.
4 The @FullTextField annotation declares a field in the index specifically tailored for full text search. In particular, we have to define an analyzer to split and analyze the tokens (~ words) - more on this later.
5 As you can see, we can define several fields for the same property. Here, we define a @KeywordField with a specific name. The main difference is that a keyword field is not tokenized (the string is kept as one single token) but can be normalized (i.e. filtered) - more on this later. This field is marked as sortable as our intention is to use it for sorting our authors.
6 The purpose of @IndexedEmbedded is to include the Book fields into the Author index. In this case, we just use the default configuration: all the fields of the associated Book instances are included in the index (i.e. the title field). @IndexedEmbedded also supports nested documents (using the structure = NESTED attribute), but we don’t need it here. You can also specify the fields you want to embed in your parent index using the includePaths/excludePaths attributes if you don’t want them all.
7 We mark a (single) constructor as a @ProjectionConstructor, so that an Author instance can be reconstructed from the content of the index.

Now that our authors are indexed, we will want to map books, so that this @IndexedEmbedded annotation actually embeds something.

Open the Book class and include the content below.

package org.acme.hibernate.search.elasticsearch.model;

import java.util.Objects;
import java.util.UUID;

import org.hibernate.search.mapper.pojo.mapping.definition.annotation.FullTextField;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.KeywordField;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.ProjectionConstructor;
import org.hibernate.search.mapper.pojo.mapping.definition.annotation.SearchEntity;

@SearchEntity (1)
public class Book {

    @KeywordField (2)
    public UUID id;

    @FullTextField(analyzer = "english") (3)
    public String title;

    @ProjectionConstructor (4)
    public Book(UUID id, String title) {
        this.id = id;
        this.title = title;
    }
}
1 We also mark the Book type as an entity type, but we don’t use @Indexed, because we decided we don’t need a dedicated index for books.
2 We index the book’s ID, so it can be projected (see below).
3 We use a @FullTextField similar to what we did for Author but you’ll notice that the analyzer is different - more on this later.
4 Like Author, we mark a constructor as a @ProjectionConstructor, so that a Book instance can be reconstructed from the content of the index.

Analyzers and normalizers

简介

Analysis is a big part of full text search: it defines how text will be processed when indexing or building search queries.

The role of analyzers is to split the text into tokens (~ words) and filter them (making it all lowercase and removing accents for instance).

Normalizers are a special type of analyzers that keeps the input as a single token. It is especially useful for sorting or indexing keywords.

There are a lot of bundled analyzers, but you can also develop your own for your own specific purposes.

You can learn more about the Elasticsearch analysis framework in the Analysis section of the Elasticsearch documentation.

Defining the analyzers used

When we added the Hibernate Search annotations to our entities, we defined the analyzers and normalizers used. Typically:

@FullTextField(analyzer = "english")
@FullTextField(analyzer = "name")
@KeywordField(name = "lastName_sort", sortable = Sortable.YES, normalizer = "sort")

We use:

  • an analyzer called name for person names,

  • an analyzer called english for book titles,

  • a normalizer called sort for our sort fields

but we haven’t set them up yet.

Let’s see how you can do it with Hibernate Search.

Setting up the analyzers

It is an easy task, we just need to create an implementation of ElasticsearchAnalysisConfigurer (and configure Quarkus to use it, more on that later).

To fulfill our requirements, let’s create the following implementation:

package org.acme.hibernate.search.elasticsearch.config;

import org.hibernate.search.backend.elasticsearch.analysis.ElasticsearchAnalysisConfigurationContext;
import org.hibernate.search.backend.elasticsearch.analysis.ElasticsearchAnalysisConfigurer;

import io.quarkus.hibernate.search.standalone.elasticsearch.SearchExtension;

@SearchExtension (1)
public class AnalysisConfigurer implements ElasticsearchAnalysisConfigurer {

    @Override
    public void configure(ElasticsearchAnalysisConfigurationContext context) {
        context.analyzer("name").custom() (2)
                .tokenizer("standard")
                .tokenFilters("asciifolding", "lowercase");

        context.analyzer("english").custom() (3)
                .tokenizer("standard")
                .tokenFilters("asciifolding", "lowercase", "porter_stem");

        context.normalizer("sort").custom() (4)
                .tokenFilters("asciifolding", "lowercase");
    }
}
1 Annotate the configurer implementation with the @SearchExtension qualifier to tell Quarkus it should be used in Hibernate Search Standalone, for all Elasticsearch indexes (by default).

The annotation can also target a specific persistence unit (@SearchExtension(persistenceUnit = "nameOfYourPU")), backend (@SearchExtension(backend = "nameOfYourBackend")), index (@SearchExtension(index = "nameOfYourIndex")), or a combination of those (@SearchExtension(persistenceUnit = "nameOfYourPU", backend = "nameOfYourBackend", index = "nameOfYourIndex")).

2 This is a simple analyzer separating the words on spaces, removing any non-ASCII characters by its ASCII counterpart (and thus removing accents) and putting everything in lowercase. It is used in our examples for the author’s names.
3 We are a bit more aggressive with this one and we include some stemming: we will be able to search for mystery and get a result even if the indexed input contains mysteries. It is definitely too aggressive for person names, but it is perfect for the book titles.
4 Here is the normalizer used for sorting. Very similar to our first analyzer, except we don’t tokenize the words as we want one and only one token.

For more information about configuring analyzers, see this section of the reference documentation.

Implementing the REST service

Create the org.acme.hibernate.search.elasticsearch.LibraryResource class:

package org.acme.hibernate.search.elasticsearch;

import java.util.ArrayList;
import java.util.UUID;

import jakarta.inject.Inject;
import jakarta.ws.rs.Consumes;
import jakarta.ws.rs.DELETE;
import jakarta.ws.rs.GET;
import jakarta.ws.rs.NotFoundException;
import jakarta.ws.rs.POST;
import jakarta.ws.rs.PUT;
import jakarta.ws.rs.Path;
import jakarta.ws.rs.core.MediaType;

import org.acme.hibernate.search.elasticsearch.model.Author;
import org.acme.hibernate.search.elasticsearch.model.Book;

import org.hibernate.search.mapper.pojo.standalone.mapping.SearchMapping;
import org.hibernate.search.mapper.pojo.standalone.session.SearchSession;

import org.jboss.resteasy.reactive.RestForm;
import org.jboss.resteasy.reactive.RestPath;

@Path("/library")
public class LibraryResource {

    @Inject
    SearchMapping searchMapping; (1)

    @PUT
    @Path("author")
    @Consumes(MediaType.APPLICATION_FORM_URLENCODED)
    public void addAuthor(@RestForm String firstName, @RestForm String lastName) {
        try (var searchSession = searchMapping.createSession()) { (2)
            Author author = new Author(UUID.randomUUID(), firstName, lastName, new ArrayList<>());
            searchSession.indexingPlan().add(author); (3)
        }
    }

    @GET
    @Path("author/{id}")
    public Author getAuthor(@RestPath UUID id) {
        try (var searchSession = searchMapping.createSession()) {
            return getAuthor(searchSession, id);
        }
    }

    private Author getAuthor(SearchSession searchSession, UUID id) {
        return searchSession.search(Author.class) (4)
                .where(f -> f.id().matching(id))
                .fetchSingleHit()
                .orElseThrow(NotFoundException::new);
    }

    @POST
    @Path("author/{id}")
    @Consumes(MediaType.APPLICATION_FORM_URLENCODED)
    public void updateAuthor(@RestPath UUID id, @RestForm String firstName, @RestForm String lastName) {
        try (var searchSession = searchMapping.createSession()) {
            Author author = getAuthor(searchSession, id); (5)
            author.firstName = firstName;
            author.lastName = lastName;
            searchSession.indexingPlan().addOrUpdate(author); (5)
        }
    }

    @DELETE
    @Path("author/{id}")
    public void deleteAuthor(@RestPath UUID id) {
        try (var searchSession = searchMapping.createSession()) {
            searchSession.indexingPlan().purge(Author.class, id, null); (6)
        }
    }

    @PUT
    @Path("author/{authorId}/book/")
    @Consumes(MediaType.APPLICATION_FORM_URLENCODED)
    public void addBook(@RestPath UUID authorId, @RestForm String title) {
        try (var searchSession = searchMapping.createSession()) {
            Author author = getAuthor(searchSession, authorId); (7)
            author.books.add(new Book(authorId, title));
            searchSession.indexingPlan().addOrUpdate(author);
        }
    }

    @DELETE
    @Path("author/{authorId}/book/{bookId}")
    public void deleteBook(@RestPath UUID authorId, @RestPath UUID bookId) {
        try (var searchSession = searchMapping.createSession()) {
            Author author = getAuthor(searchSession, authorId); (7)
            author.books.removeIf(book -> book.id.equals(bookId));
            searchSession.indexingPlan().addOrUpdate(author);
        }
    }
}
1 Inject a Hibernate Search mapping, the main entry point to Hibernate Search APIs.
2 Create a Hibernate Search session, which allows executing operations on the indexes.
3 To index a new Author, retrieve the session’s indexing plan and call add, passing the author instance in argument.
4 To retrieve an Author from the index, execute a simple search — more on search later — by identifier.
5 To update an Author, retrieve it from the index, apply changes, retrieve the session’s indexing plan and call addOrUpdate, passing the author instance in argument.
6 To delete an Author by identifier, retrieve the session’s indexing plan and call purge, passing the author class and identifier in argument.
7 Since books are "owned" by authors (they are duplicated for each author and their lifecycle is bound to their author’s), adding/deleting a book is simply an update to the author.

Nothing groundbreaking here: just a few CRUD operations in a REST service, using Hibernate Search APIs.

The interesting part comes with the addition of a search endpoint. In our LibraryResource, we just need to add the following method (and a few imports):

    @GET
    @Path("author/search")
    public List<Author> searchAuthors(@RestQuery String pattern, (1)
            @RestQuery Optional<Integer> size) {
        try (var searchSession = searchMapping.createSession()) { (2)
            return searchSession.search(Author.class) (3)
                    .where(f -> pattern == null || pattern.isBlank()
                            ? f.matchAll() (4)
                            : f.simpleQueryString()
                                    .fields("firstName", "lastName", "books.title").matching(pattern)) (5)
                    .sort(f -> f.field("lastName_sort").then().field("firstName_sort")) (6)
                    .fetchHits(size.orElse(20)); (7)
        }
    }
1 Use the org.jboss.resteasy.reactive.RestQuery annotation type to avoid repeating the parameter name.
2 Create a Hibernate Search session, which allows executing operations on the indexes.
3 We indicate that we are searching for Authors.
4 We create a predicate: if the pattern is empty, we use a matchAll() predicate.
5 If we have a valid pattern, we create a simpleQueryString() predicate on the firstName, lastName and books.title fields matching our pattern.
6 We define the sort order of our results. Here we sort by last name, then by first name. Note that we use the specific fields we created for sorting.
7 Fetch the size top hits, 20 by default. Obviously, paging is also supported.

The Hibernate Search DSL supports a significant subset of the Elasticsearch predicates (match, range, nested, phrase, spatial…​). Feel free to explore the DSL using autocompletion.

When that’s not enough, you can always fall back to defining a predicate using JSON directly.

Automatic data initialization

For the purpose of this demonstration, let’s import an initial dataset.

Let’s add a few methods in LibraryResource:

    void onStart(@Observes StartupEvent ev) { (1)
        // Index some test data if nothing exists
        try (var searchSession = searchMapping.createSession()) {
            if (0 < searchSession.search(Author.class) (2)
                    .where(f -> f.matchAll())
                    .fetchTotalHitCount()) {
                return;
            }
            for (Author author : initialDataSet()) { (3)
                searchSession.indexingPlan().add(author); (4)
            }
        }
    }

    private List<Author> initialDataSet() {
        return List.of(
                new Author(UUID.randomUUID(), "John", "Irving",
                        List.of(
                                new Book(UUID.randomUUID(), "The World According to Garp"),
                                new Book(UUID.randomUUID(), "The Hotel New Hampshire"),
                                new Book(UUID.randomUUID(), "The Cider House Rules"),
                                new Book(UUID.randomUUID(), "A Prayer for Owen Meany"),
                                new Book(UUID.randomUUID(), "Last Night in Twisted River"),
                                new Book(UUID.randomUUID(), "In One Person"),
                                new Book(UUID.randomUUID(), "Avenue of Mysteries"))),
                new Author(UUID.randomUUID(), "Paul", "Auster",
                        List.of(
                                new Book(UUID.randomUUID(), "The New York Trilogy"),
                                new Book(UUID.randomUUID(), "Mr. Vertigo"),
                                new Book(UUID.randomUUID(), "The Brooklyn Follies"),
                                new Book(UUID.randomUUID(), "Invisible"),
                                new Book(UUID.randomUUID(), "Sunset Park"),
                                new Book(UUID.randomUUID(), "4 3 2 1"))));
    }
1 Add a method that will get executed on application startup.
2 Check whether there already is data in the index — if not, bail out.
3 Generate the initial dataset.
4 For each author, add it to the index.

配置应用

As usual, we can configure everything in the Quarkus configuration file, application.properties.

Edit src/main/resources/application.properties and inject the following configuration:

quarkus.ssl.native=false (1)

quarkus.hibernate-search-standalone.mapping.structure=document (2)
quarkus.hibernate-search-standalone.elasticsearch.version=8 (3)
quarkus.hibernate-search-standalone.indexing.plan.synchronization.strategy=sync (4)

%prod.quarkus.hibernate-search-standalone.elasticsearch.hosts=localhost:9200 (5)
1 We won’t use SSL, so we disable it to have a more compact native executable.
2 We need to tell Hibernate Search about the structure of our entities.

In this application we consider an indexed entity (the author) is the root of a "document": the author "owns" books it references through associations, which cannot be updated independently of the author.

See quarkus.hibernate-search-standalone.mapping.structure for other options and more details.

3 We need to tell Hibernate Search about the version of Elasticsearch we will use.

It is important because there are significant differences between Elasticsearch mapping syntax depending on the version. Since the mapping is created at build time to reduce startup time, Hibernate Search cannot connect to the cluster to automatically detect the version. Note that, for OpenSearch, you need to prefix the version with opensearch:; see OpenSearch compatibility.

4 This means that we wait for the entities to be searchable before considering a write complete. On a production setup, the write-sync default will provide better performance. Using sync is especially important when testing as you need the entities to be searchable immediately.
5 For development and tests, we rely on Dev Services, which means Quarkus will start an Elasticsearch cluster automatically. In production mode, however, we will want to start an Elasticsearch cluster manually, which is why we provide Quarkus with this connection info in the prod profile (%prod. prefix).

Because we rely on Dev Services, the Elasticsearch schema will automatically be dropped and re-created on each application startup in tests and dev mode (unless quarkus.hibernate-search-standalone.schema-management.strategy is set explicitly).

If for some reason you cannot use Dev Services, you will have to set the following properties to get similar behavior:

%dev,test.quarkus.hibernate-search-standalone.schema-management.strategy=drop-and-create
For more information about configuration of the Hibernate Search Standalone extension, refer to the Configuration Reference.

创建一个网页

Now let’s add a simple web page to interact with our LibraryResource. Quarkus automatically serves static resources located under the META-INF/resources directory. In the src/main/resources/META-INF/resources directory, overwrite the existing index.html file with the content from this index.html file.

Time to play with your application

现在你可以与你的REST服务进行交互:

  • start your Quarkus application with:

    CLI
    quarkus dev
    Maven
    ./mvnw quarkus:dev
    Gradle
    ./gradlew --console=plain quarkusDev
  • open a browser to http://localhost:8080/

  • search for authors or book titles (we initialized some data for you)

  • create new authors and books and search for them too

As you can see, all your updates are automatically synchronized to the Elasticsearch cluster.

构建一个本地可执行文件

你可以使用常用命令构建本机可执行文件:

CLI
quarkus build --native
Maven
./mvnw install -Dnative
Gradle
./gradlew build -Dquarkus.native.enabled=true

As usual with native executable compilation, this operation consumes a lot of memory.

It might be safer to stop the two containers while you are building the native executable and start them again once you are done.

Running it is as simple as executing ./target/hibernate-search-standalone-elasticsearch-quickstart-1.0.0-SNAPSHOT-runner.

You can then point your browser to http://localhost:8080/ and use your application.

The startup is a bit slower than usual: it is mostly due to us dropping and recreating the Elasticsearch mapping every time at startup. We also index some initial data.

In a real life application, it is obviously something you won’t do on every startup.

Dev Services (Configuration Free Datastores)

Quarkus supports a feature called Dev Services that allows you to start various containers without any config.

In the case of Elasticsearch this support extends to the default Elasticsearch connection. What that means practically, is that if you have not configured quarkus.hibernate-search-standalone.elasticsearch.hosts, Quarkus will automatically start an Elasticsearch container when running tests or in dev mode, and automatically configure the connection.

When running the production version of the application, the Elasticsearch connection needs to be configured as normal, so if you want to include a production database config in your application.properties and continue to use Dev Services we recommend that you use the %prod. profile to define your Elasticsearch settings.

Dev Services for Elasticsearch is currently unable to start multiple clusters concurrently, so it only works with the default backend of the default persistence unit: named persistence units or named backends won’t be able to take advantage of Dev Services for Elasticsearch.

For more information you can read the Dev Services for Elasticsearch guide.

Programmatic mapping

If, for some reason, adding Hibernate Search annotations to entities is not possible, mapping can be applied programmatically instead. Programmatic mapping is configured through the ProgrammaticMappingConfigurationContext that is exposed via a mapping configurer (HibernateOrmSearchMappingConfigurer).

A mapping configurer (StandalonePojoMappingConfigurer) allows much more than just programmatic mapping capabilities. It also allows configuring annotation mapping, bridges, and more.

Below is an example of a mapping configurer that applies programmatic mapping:

package org.acme.hibernate.search.elasticsearch.config;

import org.hibernate.search.mapper.pojo.standalone.mapping.StandalonePojoMappingConfigurationContext;
import org.hibernate.search.mapper.pojo.standalone.mapping.StandalonePojoMappingConfigurer;
import org.hibernate.search.mapper.pojo.mapping.definition.programmatic.TypeMappingStep;

import io.quarkus.hibernate.search.standalone.elasticsearch.SearchExtension;

@SearchExtension (1)
public class CustomMappingConfigurer implements StandalonePojoMappingConfigurer {

	@Override
    public void configure(StandalonePojoMappingConfigurationContext context) {
        TypeMappingStep type = context.programmaticMapping()    (2)
                .type(SomeIndexedEntity.class);                 (3)
        type.searchEntity();                                    (4)
        type.indexed()                                          (5)
                .index(SomeIndexedEntity.INDEX_NAME);           (6)
        type.property("id").documentId();                       (7)
        type.property("text").fullTextField();                  (8)
    }
}
1 Annotate the configurer implementation with the @SearchExtension qualifier to tell Quarkus it should be used by Hibernate Search Standalone.
2 Access the programmatic mapping context.
3 Create mapping step for the SomeIndexedEntity type.
4 Define SomeIndexedEntity as an entity type for Hibernate Search.
5 Define the SomeIndexedEntity entity as indexed.
6 Provide an index name to be used for the SomeIndexedEntity entity.
7 Define the document id property.
8 Define a full-text search field for the text property.

OpenSearch compatibility

Hibernate Search is compatible with both Elasticsearch and OpenSearch, but it assumes it is working with an Elasticsearch cluster by default.

To have Hibernate Search work with an OpenSearch cluster instead, prefix the configured version with opensearch:, as shown below.

quarkus.hibernate-search-standalone.elasticsearch.version=opensearch:2.13

All other configuration options and APIs are exactly the same as with Elasticsearch.

You can find more information about compatible distributions and versions of Elasticsearch in this section of Hibernate Search’s reference documentation.

CDI integration

Injecting entry points

You can inject Hibernate Search’s main entry point, SearchMapping, using CDI:

@Inject
SearchMapping searchMapping;

Plugging in custom components

The Quarkus extension for Hibernate Search Standalone will automatically inject components annotated with @SearchExtension into Hibernate Search.

The annotation can optionally target a specific backend (@SearchExtension(backend = "nameOfYourBackend")), index (@SearchExtension(index = "nameOfYourIndex")), or a combination of those (@SearchExtension(backend = "nameOfYourBackend", index = "nameOfYourIndex")), when it makes sense for the type of the component being injected.

This feature is available for the following component types:

org.hibernate.search.engine.reporting.FailureHandler

A component that should be notified of any failure occurring in a background process (mainly index operations).

Scope: one per application.

org.hibernate.search.mapper.pojo.standalone.mapping.StandalonePojoMappingConfigurer

A component used to configure the Hibernate Search mapping, in particular programmatically.

Scope: one or more per persistence unit.

See this section of this guide for more information.

org.hibernate.search.mapper.pojo.work.IndexingPlanSynchronizationStrategy

A component used to configure how to synchronize between application threads and indexing.

Scope: one per application.

Can also be set to built-in implementations through quarkus.hibernate-search-standalone.indexing.plan.synchronization.strategy.

org.hibernate.search.backend.elasticsearch.analysis.ElasticsearchAnalysisConfigurer

A component used to configure full text analysis (e.g. analyzers, normalizers).

Scope: one or more per backend.

See this section of this guide for more information.

org.hibernate.search.backend.elasticsearch.index.layout.IndexLayoutStrategy

A component used to configure the Elasticsearch layout: index names, index aliases, …​

Scope: one per backend.

Can also be set to built-in implementations through quarkus.hibernate-search-standalone.elasticsearch.layout.strategy.

Offline startup

By default, Hibernate Search sends a few requests to the Elasticsearch cluster on startup. If the Elasticsearch cluster is not necessarily up and running when Hibernate Search starts, this could cause a startup failure.

To address this, you can configure Hibernate Search to not send any request on startup:

Of course, even with this configuration, Hibernate Search still won’t be able to index anything or run search queries until the Elasticsearch cluster becomes accessible.

If you disable automatic schema creation by setting quarkus.hibernate-search-standalone.schema-management.strategy to none, you will have to create the schema manually at some point before your application starts persisting/updating entities and executing search requests.

Loading

As an alternative to using Elasticsearch as a primary datastore, this extension can also be used to index entities coming from another datastore.

In such a scenario, you will need to set quarkus.hibernate-search-standalone.mapping.structure to a value matching the structure of the primary datastore.

In order to do this, entities need to be loaded from that other datastore, and such loading must be implemented explicitly.

You can refer to Hibernate Search’s reference documentation for more information about configuring loading:

In Quarkus, the entity loader mentioned in Hibernate Search’s reference documentation can be defined as a CDI bean, but will still need to be attached to particular entities using @SearchEntity(loadingBinder = …​).

Management endpoint

Hibernate Search’s management endpoint is considered preview.

In preview, backward compatibility and presence in the ecosystem is not guaranteed. Specific improvements might require changing configuration or APIs, or even storage formats, and plans to become stable are under way. Feedback is welcome on our mailing list or as issues in our GitHub issue tracker.

The Hibernate Search extension provides an HTTP endpoint to reindex your data through the management interface. By default, this endpoint is not available. It can be enabled through configuration properties as shown below.

quarkus.management.enabled=true (1)
quarkus.hibernate-search-standalone.management.enabled=true (2)
1 Enable the management interface.
2 Enable Hibernate Search Standalone specific management endpoints.

Once the management endpoints are enabled, data can be re-indexed via /q/hibernate-search/standalone/reindex, where /q is the default management root path and /hibernate-search/standalone/ is the default Hibernate Search root management path. It (/hibernate-search/standalone/) can be changed via configuration property as shown below.

quarkus.hibernate-search-standalone.management.root-path=custom-root-path (1)
1 Use a custom custom-root-path path for Hibernate Search’s management endpoint. If the default management root path is used then the reindex path becomes /q/custom-root-path/reindex.

This endpoint accepts POST requests with application/json content type only. All indexed entities will be re-indexed if an empty request body is submitted.

In order to reindex an entity type, it needs to be configured for loading from an external source.

Without that configuration, reindexing through the management endpoint (or through any other API) will fail.

If only a subset of entities must be re-indexed or if there is a need to have a custom configuration of the underlying mass indexer then this information can be passed through the request body as shown below.

{
  "filter": {
    "types": ["EntityName1", "EntityName2", "EntityName3", ...], (1)
  },
  "massIndexer":{
    "typesToIndexInParallel": 1, (2)
  }
}
1 An array of entity names that should be re-indexed. If unspecified or empty, all entity types will be re-indexed.
2 Sets the number of entity types to be indexed in parallel.

The full list of possible filters and available mass indexer configurations is presented in the example below.

{
  "filter": { (1)
    "types": ["EntityName1", "EntityName2", "EntityName3", ...], (2)
    "tenants": ["tenant1", "tenant2", ...] (3)
  },
  "massIndexer":{ (4)
    "typesToIndexInParallel": 1, (5)
    "threadsToLoadObjects": 6,  (6)
    "batchSizeToLoadObjects": 10, (7)
    "cacheMode": "IGNORE", (8)
    "mergeSegmentsOnFinish": false, (9)
    "mergeSegmentsAfterPurge": true, (10)
    "dropAndCreateSchemaOnStart": false, (11)
    "purgeAllOnStart": true, (12)
    "idFetchSize": 100, (13)
    "transactionTimeout": 100000, (14)
  }
}
1 Filter object that allows to limit the scope of reindexing.
2 An array of entity names that should be re-indexed. If unspecified or empty, all entity types will be re-indexed.
3 An array of tenant ids, in case of multi-tenancy. If unspecified or empty, all tenants will be re-indexed.
4 Mass indexer configuration object.
5 Sets the number of entity types to be indexed in parallel.
6 Sets the number of threads to be used to load the root entities.
7 Sets the batch size used to load the root entities.
8 Sets the cache interaction mode for the data loading tasks.
9 Whether each index is merged into a single segment after indexing.
10 Whether each index is merged into a single segment after the initial index purge, just before indexing.
11 Whether the indexes and their schema (if they exist) should be dropped and re-created before indexing.
12 Whether all entities are removed from the indexes before indexing.
13 Specifies the fetch size to be used when loading primary keys if objects to be indexed.
14 Specifies the timeout of transactions for loading ids and entities to be re-indexed.

Note all the properties in the JSON are optional, and only those that are needed should be used.

For more detailed information on mass indexer configuration see the corresponding section of the Hibernate Search reference documentation.

Submitting the reindexing request will trigger indexing in the background. Mass indexing progress will appear in the application logs. For testing purposes, it might be useful to know when the indexing finished. Adding wait_for=finished query parameter to the URL will result in the management endpoint returning a chunked response that will report when the indexing starts and then when it is finished.

Limitations

Further reading

If you are interested in learning more about Hibernate Search, the Hibernate team publishes an extensive reference documentation, as well as a page listing other relevant resources.

FAQ

Why Elasticsearch only?

Hibernate Search supports both a Lucene backend and an Elasticsearch backend.

In the context of Quarkus and to build scalable applications, we thought the latter would make more sense. Thus, we focused our efforts on it.

We don’t have plans to support the Lucene backend in Quarkus for now, though there is an issue tracking progress on such an implementation in the Quarkiverse: quarkiverse/quarkus-hibernate-search-extras#180.

Configuration Reference for Hibernate Search Standalone

Configuration property fixed at build time - All other configuration properties are overridable at runtime

Configuration property

类型

默认

Whether Hibernate Search Standalone is enabled during the build.

If Hibernate Search is disabled during the build, all processing related to Hibernate Search will be skipped, but it will not be possible to activate Hibernate Search at runtime: quarkus.hibernate-search-standalone.active will default to false and setting it to true will lead to an error.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ENABLED

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boolean

true

A bean reference to a component that should be notified of any failure occurring in a background process (mainly index operations).

The referenced bean must implement FailureHandler.

Instead of setting this configuration property, you can simply annotate your custom FailureHandler implementation with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. See this section for more information.

If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_BACKGROUND_FAILURE_HANDLER

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string

One or more bean references to the component(s) used to configure the Hibernate Search mapping, in particular programmatically.

The referenced beans must implement StandalonePojoMappingConfigurer.

See Programmatic mapping for an example on how mapping configurers can be used to apply programmatic mappings.

Instead of setting this configuration property, you can simply annotate your custom StandalonePojoMappingConfigurer implementations with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. See this section for more information.

If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_MAPPING_CONFIGURER

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list of string

The structure of the Hibernate Search entity mapping.

This must match the structure of the application model being indexed with Hibernate Search:

graph (default)

Entities indexed through Hibernate Search are nodes in an entity graph, i.e. an indexed entity is independent of other entities it references through associations, which can be updated independently of the indexed entity.

Associations between entities must be bi-directional: specifying the inverse side of associations through @AssociationInverseSide is required, unless reindexing is disabled for that association through @IndexingDependency(reindexOnUpdate = …​).

tree

Entities indexed through Hibernate Search are the root of a document, i.e. an indexed entity "owns" other entities it references through associations, which cannot be updated independently of the indexed entity.

Associations between entities can be uni-directional: specifying the inverse side of associations through @AssociationInverseSide is not required.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_MAPPING_STRUCTURE

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graph, document

graph

Whether Hibernate Search Standalone should be active at runtime.

If Hibernate Search Standalone is not active, it won’t start with the application, and accessing the SearchMapping for search or other operations will not be possible.

Note that if Hibernate Search Standalone is disabled (i.e. quarkus.hibernate-search-standalone.enabled is set to false), it won’t be active, and setting this property to true will fail.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ACTIVE

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boolean

'true' if Hibernate Search Standalone is enabled; 'false' otherwise

The schema management strategy, controlling how indexes and their schema are created, updated, validated or dropped on startup and shutdown.

Available values:

Strategy

Definition

none

Do nothing: assume that indexes already exist and that their schema matches Hibernate Search’s expectations.

validate

Validate that indexes exist and that their schema matches Hibernate Search’s expectations.

If it does not, throw an exception, but make no attempt to fix the problem.

create

For indexes that do not exist, create them along with their schema.

For indexes that already exist, do nothing: assume that their schema matches Hibernate Search’s expectations.

create-or-validate (default unless using Dev Services)

For indexes that do not exist, create them along with their schema.

For indexes that already exist, validate that their schema matches Hibernate Search’s expectations.

If it does not, throw an exception, but make no attempt to fix the problem.

create-or-update

For indexes that do not exist, create them along with their schema.

For indexes that already exist, validate that their schema matches Hibernate Search’s expectations; if it does not match expectations, try to update it.

This strategy is unfit for production environments, due to several important limitations, but can be useful when developing.

drop-and-create

For indexes that do not exist, create them along with their schema.

For indexes that already exist, drop them, then create them along with their schema.

drop-and-create-and-drop (default when using Dev Services)

For indexes that do not exist, create them along with their schema.

For indexes that already exist, drop them, then create them along with their schema.

Also, drop indexes and their schema on shutdown.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_SCHEMA_MANAGEMENT_STRATEGY

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SchemaManagementStrategyName

drop-and-create-and-drop when using Dev Services; create-or-validate otherwise

How to synchronize between application threads and indexing, in particular when relying on (implicit) listener-triggered indexing on entity change, but also when using a SearchIndexingPlan explicitly.

Defines how complete indexing should be before resuming the application thread after a SearchSession is closed.

Available values:

Strategy

Throughput

Guarantees when the application thread resumes

Changes applied

Changes safe from crash/power loss

Changes visible on search

async

Best

write-sync (default)

Medium

read-sync

Medium to worst

sync

Worst

This property also accepts a bean reference to a custom implementations of IndexingPlanSynchronizationStrategy.

Instead of setting this configuration property, you can simply annotate your custom IndexingPlanSynchronizationStrategy implementation with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_INDEXING_PLAN_SYNCHRONIZATION_STRATEGY

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string

write-sync

Root path for reindexing endpoints. This value will be resolved as a path relative to ${quarkus.management.root-path}.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_MANAGEMENT_ROOT_PATH

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string

hibernate-search/standalone/

If management interface is turned on the reindexing endpoints will be published under the management interface. This property allows to enable this functionality by setting it to `true.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_MANAGEMENT_ENABLED

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boolean

false

Configuration for backends

类型

默认

The version of Elasticsearch used in the cluster.

As the schema is generated without a connection to the server, this item is mandatory.

It doesn’t have to be the exact version (it can be 7 or 7.1 for instance) but it has to be sufficiently precise to choose a model dialect (the one used to generate the schema) compatible with the protocol dialect (the one used to communicate with Elasticsearch).

There’s no rule of thumb here as it depends on the schema incompatibilities introduced by Elasticsearch versions. In any case, if there is a problem, you will have an error when Hibernate Search tries to connect to the cluster.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_VERSION

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ElasticsearchVersion

A bean reference to the component used to configure the Elasticsearch layout: index names, index aliases, …​

The referenced bean must implement IndexLayoutStrategy.

Available built-in implementations:

simple

The default, future-proof strategy: if the index name in Hibernate Search is myIndex, this strategy will create an index named myindex-000001, an alias for write operations named myindex-write, and an alias for read operations named myindex-read.

no-alias

A strategy without index aliases, mostly useful on legacy clusters: if the index name in Hibernate Search is myIndex, this strategy will create an index named myindex, and will not use any alias.

Instead of setting this configuration property, you can simply annotate your custom IndexLayoutStrategy implementation with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. See this section for more information.

If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_LAYOUT_STRATEGY

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string

Path to a file in the classpath holding custom index settings to be included in the index definition when creating an Elasticsearch index.

The provided settings will be merged with those generated by Hibernate Search, including analyzer definitions. When analysis is configured both through an analysis configurer and these custom settings, the behavior is undefined; it should not be relied upon.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_SCHEMA_MANAGEMENT_SETTINGS_FILE

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string

Path to a file in the classpath holding a custom index mapping to be included in the index definition when creating an Elasticsearch index.

The file does not need to (and generally shouldn’t) contain the full mapping: Hibernate Search will automatically inject missing properties (index fields) in the given mapping.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_SCHEMA_MANAGEMENT_MAPPING_FILE

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string

One or more bean references to the component(s) used to configure full text analysis (e.g. analyzers, normalizers).

The referenced beans must implement ElasticsearchAnalysisConfigurer.

See Setting up the analyzers for more information.

Instead of setting this configuration property, you can simply annotate your custom ElasticsearchAnalysisConfigurer implementations with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. See this section for more information.

If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_ANALYSIS_CONFIGURER

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list of string

The list of hosts of the Elasticsearch servers.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_HOSTS

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list of string

localhost:9200

The protocol to use when contacting Elasticsearch servers. Set to "https" to enable SSL/TLS.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_PROTOCOL

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http, https

http

The username used for authentication.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_USERNAME

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string

The password used for authentication.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_PASSWORD

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string

The timeout when establishing a connection to an Elasticsearch server.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_CONNECTION_TIMEOUT

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Duration

1S

The timeout when reading responses from an Elasticsearch server.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_READ_TIMEOUT

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Duration

30S

The timeout when executing a request to an Elasticsearch server.

This includes the time needed to wait for a connection to be available, send the request and read the response.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_REQUEST_TIMEOUT

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Duration

The maximum number of connections to all the Elasticsearch servers.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_MAX_CONNECTIONS

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int

20

The maximum number of connections per Elasticsearch server.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_MAX_CONNECTIONS_PER_ROUTE

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int

10

Defines if automatic discovery is enabled.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_DISCOVERY_ENABLED

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boolean

false

Refresh interval of the node list.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_DISCOVERY_REFRESH_INTERVAL

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Duration

10S

The size of the thread pool assigned to the backend.

Note that number is per backend, not per index. Adding more indexes will not add more threads.

As all operations happening in this thread-pool are non-blocking, raising its size above the number of processor cores available to the JVM will not bring noticeable performance benefit. The only reason to alter this setting would be to reduce the number of threads; for example, in an application with a single index with a single indexing queue, running on a machine with 64 processor cores, you might want to bring down the number of threads.

Defaults to the number of processor cores available to the JVM on startup.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_THREAD_POOL_SIZE

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int

Whether partial shard failures are ignored (true) or lead to Hibernate Search throwing an exception (false).

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_QUERY_SHARD_FAILURE_IGNORE

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boolean

false

Whether Hibernate Search should check the version of the Elasticsearch cluster on startup.

Set to false if the Elasticsearch cluster may not be available on startup.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_VERSION_CHECK_ENABLED

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boolean

true

The minimal Elasticsearch cluster status required on startup.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_SCHEMA_MANAGEMENT_REQUIRED_STATUS

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green, yellow, red

yellow

How long we should wait for the status before failing the bootstrap.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_SCHEMA_MANAGEMENT_REQUIRED_STATUS_WAIT_TIMEOUT

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Duration

10S

The number of indexing queues assigned to each index.

Higher values will lead to more connections being used in parallel, which may lead to higher indexing throughput, but incurs a risk of overloading Elasticsearch, i.e. of overflowing its HTTP request buffers and tripping circuit breakers, leading to Elasticsearch giving up on some request and resulting in indexing failures.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXING_QUEUE_COUNT

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int

10

The size of indexing queues.

Lower values may lead to lower memory usage, especially if there are many queues, but values that are too low will reduce the likeliness of reaching the max bulk size and increase the likeliness of application threads blocking because the queue is full, which may lead to lower indexing throughput.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXING_QUEUE_SIZE

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int

1000

The maximum size of bulk requests created when processing indexing queues.

Higher values will lead to more documents being sent in each HTTP request sent to Elasticsearch, which may lead to higher indexing throughput, but incurs a risk of overloading Elasticsearch, i.e. of overflowing its HTTP request buffers and tripping circuit breakers, leading to Elasticsearch giving up on some request and resulting in indexing failures.

Note that raising this number above the queue size has no effect, as bulks cannot include more requests than are contained in the queue.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXING_MAX_BULK_SIZE

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int

100

Per-index configuration overrides

类型

默认

Path to a file in the classpath holding custom index settings to be included in the index definition when creating an Elasticsearch index.

The provided settings will be merged with those generated by Hibernate Search, including analyzer definitions. When analysis is configured both through an analysis configurer and these custom settings, the behavior is undefined; it should not be relied upon.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__SCHEMA_MANAGEMENT_SETTINGS_FILE

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string

Path to a file in the classpath holding a custom index mapping to be included in the index definition when creating an Elasticsearch index.

The file does not need to (and generally shouldn’t) contain the full mapping: Hibernate Search will automatically inject missing properties (index fields) in the given mapping.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__SCHEMA_MANAGEMENT_MAPPING_FILE

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string

One or more bean references to the component(s) used to configure full text analysis (e.g. analyzers, normalizers).

The referenced beans must implement ElasticsearchAnalysisConfigurer.

See Setting up the analyzers for more information.

Instead of setting this configuration property, you can simply annotate your custom ElasticsearchAnalysisConfigurer implementations with @SearchExtension and leave the configuration property unset: Hibernate Search will use the annotated implementation automatically. See this section for more information.

If this configuration property is set, it takes precedence over any @SearchExtension annotation.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__ANALYSIS_CONFIGURER

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list of string

The minimal Elasticsearch cluster status required on startup.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__SCHEMA_MANAGEMENT_REQUIRED_STATUS

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green, yellow, red

yellow

How long we should wait for the status before failing the bootstrap.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__SCHEMA_MANAGEMENT_REQUIRED_STATUS_WAIT_TIMEOUT

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Duration

10S

The number of indexing queues assigned to each index.

Higher values will lead to more connections being used in parallel, which may lead to higher indexing throughput, but incurs a risk of overloading Elasticsearch, i.e. of overflowing its HTTP request buffers and tripping circuit breakers, leading to Elasticsearch giving up on some request and resulting in indexing failures.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__INDEXING_QUEUE_COUNT

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int

10

The size of indexing queues.

Lower values may lead to lower memory usage, especially if there are many queues, but values that are too low will reduce the likeliness of reaching the max bulk size and increase the likeliness of application threads blocking because the queue is full, which may lead to lower indexing throughput.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__INDEXING_QUEUE_SIZE

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int

1000

The maximum size of bulk requests created when processing indexing queues.

Higher values will lead to more documents being sent in each HTTP request sent to Elasticsearch, which may lead to higher indexing throughput, but incurs a risk of overloading Elasticsearch, i.e. of overflowing its HTTP request buffers and tripping circuit breakers, leading to Elasticsearch giving up on some request and resulting in indexing failures.

Note that raising this number above the queue size has no effect, as bulks cannot include more requests than are contained in the queue.

Environment variable: QUARKUS_HIBERNATE_SEARCH_STANDALONE_ELASTICSEARCH_INDEXES__INDEX_NAME__INDEXING_MAX_BULK_SIZE

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int

100

About the Duration format

To write duration values, use the standard java.time.Duration format. See the Duration#parse() Java API documentation for more information.

You can also use a simplified format, starting with a number:

  • If the value is only a number, it represents time in seconds.

  • If the value is a number followed by ms, it represents time in milliseconds.

In other cases, the simplified format is translated to the java.time.Duration format for parsing:

  • If the value is a number followed by h, m, or s, it is prefixed with PT.

  • If the value is a number followed by d, it is prefixed with P.

About bean references

First, be aware that referencing beans in configuration properties is optional and, in fact, discouraged: you can achieve the same results by annotating your beans with @SearchExtension. See this section for more information.

If you really do want to reference beans using a string value in configuration properties know that string is parsed; here are the most common formats:

  • bean: followed by the name of a @Named CDI bean. For example bean:myBean.

  • class: followed by the fully-qualified name of a class, to be instantiated through CDI if it’s a CDI bean, or through its public, no-argument constructor otherwise. For example class:com.mycompany.MyClass.

  • An arbitrary string referencing a built-in implementation. Available values are detailed in the documentation of each configuration property, such as async/read-sync/write-sync/sync for quarkus.hibernate-search-standalone.indexing.plan.synchronization.strategy.

Other formats are also accepted, but are only useful for advanced use cases. See this section of Hibernate Search’s reference documentation for more information.

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