Connecting to an Elasticsearch cluster

Elasticsearch is a well known full text search engine and NoSQL datastore.

In this guide, we will see how you can get your REST services to interact with an Elasticsearch cluster.

Quarkus provides two ways of accessing Elasticsearch:

  • The lower level REST Client

  • The Elasticsearch Java client

A third Quarkus extension for the "high level REST Client" used to exist, but was removed as this client has been deprecated by Elastic and has some licensing issues.

Prerequisites

To complete this guide, you need:

  • Roughly 15 minutes

  • An IDE

  • JDK 11+ installed with JAVA_HOME configured appropriately

  • Apache Maven 3.9.3

  • Optionally the Quarkus CLI if you want to use it

  • Optionally Mandrel or GraalVM installed and configured appropriately if you want to build a native executable (or Docker if you use a native container build)

  • Elasticsearch installed or Docker installed

Architecture

The application built in this guide is quite simple: the user can add elements in a list using a form and the list is updated.

All the information between the browser and the server is formatted as JSON.

The elements are stored in Elasticsearch.

Creating the Maven project

First, we need a new project. Create a new project with the following command:

CLI
quarkus create app org.acme:elasticsearch-quickstart \
    --extension='resteasy-reactive-jackson,elasticsearch-rest-client' \
    --no-code
cd elasticsearch-quickstart

To create a Gradle project, add the --gradle or --gradle-kotlin-dsl option.

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:3.4.1:create \
    -DprojectGroupId=org.acme \
    -DprojectArtifactId=elasticsearch-quickstart \
    -Dextensions='resteasy-reactive-jackson,elasticsearch-rest-client' \
    -DnoCode
cd elasticsearch-quickstart

To create a Gradle project, add the -DbuildTool=gradle or -DbuildTool=gradle-kotlin-dsl option.

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=elasticsearch-quickstart"

This command generates a Maven structure importing the RESTEasy Reactive, Jackson, and Elasticsearch low level REST client extensions.

The Elasticsearch low level REST client comes with the quarkus-elasticsearch-rest-client extension that has been added to your build file.

If you want to use the Elasticsearch Java client instead, replace the quarkus-elasticsearch-rest-client extension by the quarkus-elasticsearch-java-client extension.

We use the resteasy-reactive-jackson extension here and not the JSON-B variant because we will use the Vert.x JsonObject helper to serialize/deserialize our objects to/from Elasticsearch and it uses Jackson under the hood.

To add the extensions to an existing project, follow the instructions below.

For the Elasticsearch low level REST client, add the following dependency to your build file:

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

For the Elasticsearch Java client, add the following dependency to your build file:

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

Creating your first JSON REST service

In this example, we will create an application to manage a list of fruits.

First, let’s create the Fruit bean as follows:

package org.acme.elasticsearch;

public class Fruit {
    public String id;
    public String name;
    public String color;
}

Nothing fancy. One important thing to note is that having a default constructor is required by the JSON serialization layer.

Now create a org.acme.elasticsearch.FruitService that will be the business layer of our application and will store/load the fruits from the Elasticsearch instance. Here we use the low level REST client, if you want to use the Java API client instead, follow the instructions in the Using the Elasticsearch Java Client paragraph instead.

package org.acme.elasticsearch;

import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

import jakarta.enterprise.context.ApplicationScoped;
import jakarta.inject.Inject;

import org.apache.http.util.EntityUtils;
import org.elasticsearch.client.Request;
import org.elasticsearch.client.Response;
import org.elasticsearch.client.RestClient;

import io.vertx.core.json.JsonArray;
import io.vertx.core.json.JsonObject;

@ApplicationScoped
public class FruitService {
    @Inject
    RestClient restClient; (1)

    public void index(Fruit fruit) throws IOException {
        Request request = new Request(
                "PUT",
                "/fruits/_doc/" + fruit.id); (2)
        request.setJsonEntity(JsonObject.mapFrom(fruit).toString()); (3)
        restClient.performRequest(request); (4)
    }

    public Fruit get(String id) throws IOException {
        Request request = new Request(
                "GET",
                "/fruits/_doc/" + id);
        Response response = restClient.performRequest(request);
        String responseBody = EntityUtils.toString(response.getEntity());
        JsonObject json = new JsonObject(responseBody); (5)
        return json.getJsonObject("_source").mapTo(Fruit.class);
    }

    public List<Fruit> searchByColor(String color) throws IOException {
        return search("color", color);
    }

    public List<Fruit> searchByName(String name) throws IOException {
        return search("name", name);
    }

    private List<Fruit> search(String term, String match) throws IOException {
        Request request = new Request(
                "GET",
                "/fruits/_search");
        //construct a JSON query like {"query": {"match": {"<term>": "<match"}}
        JsonObject termJson = new JsonObject().put(term, match);
        JsonObject matchJson = new JsonObject().put("match", termJson);
        JsonObject queryJson = new JsonObject().put("query", matchJson);
        request.setJsonEntity(queryJson.encode());
        Response response = restClient.performRequest(request);
        String responseBody = EntityUtils.toString(response.getEntity());

        JsonObject json = new JsonObject(responseBody);
        JsonArray hits = json.getJsonObject("hits").getJsonArray("hits");
        List<Fruit> results = new ArrayList<>(hits.size());
        for (int i = 0; i < hits.size(); i++) {
            JsonObject hit = hits.getJsonObject(i);
            Fruit fruit = hit.getJsonObject("_source").mapTo(Fruit.class);
            results.add(fruit);
        }
        return results;
    }
}
1 We inject an Elasticsearch low level RestClient into our service.
2 We create an Elasticsearch request.
3 We use Vert.x JsonObject to serialize the object before sending it to Elasticsearch, you can use whatever you want to serialize your objects to JSON.
4 We send the request (indexing request here) to Elasticsearch.
5 In order to deserialize the object from Elasticsearch, we again use Vert.x JsonObject.

Now, create the org.acme.elasticsearch.FruitResource class as follows:

package org.acme.elasticsearch;

import jakarta.inject.Inject;
import jakarta.ws.rs.BadRequestException;
import jakarta.ws.rs.GET;
import jakarta.ws.rs.POST;
import jakarta.ws.rs.Path;
import jakarta.ws.rs.core.Response;
import java.io.IOException;
import java.net.URI;
import java.util.List;
import java.util.UUID;

import org.jboss.resteasy.reactive.RestQuery;

@Path("/fruits")
public class FruitResource {

    @Inject
    FruitService fruitService;

    @POST
    public Response index(Fruit fruit) throws IOException {
        if (fruit.id == null) {
            fruit.id = UUID.randomUUID().toString();
        }
        fruitService.index(fruit);
        return Response.created(URI.create("/fruits/" + fruit.id)).build();
    }

    @GET
    @Path("/{id}")
    public Fruit get(String id) throws IOException {
        return fruitService.get(id);
    }

    @GET
    @Path("/search")
    public List<Fruit> search(@RestQuery String name, @RestQuery String color) throws IOException {
        if (name != null) {
            return fruitService.searchByName(name);
        } else if (color != null) {
            return fruitService.searchByColor(color);
        } else {
            throw new BadRequestException("Should provide name or color query parameter");
        }
    }
}

The implementation is pretty straightforward and you just need to define your endpoints using the Jakarta REST annotations and use the FruitService to list/add new fruits.

Configuring Elasticsearch

The main property to configure is the URL to connect to the Elasticsearch cluster.

For a typical clustered Elasticsearch service, a sample configuration would look like the following:

# configure the Elasticsearch client for a cluster of two nodes
quarkus.elasticsearch.hosts = elasticsearch1:9200,elasticsearch2:9200

In our case, we are using a single instance running on localhost:

# configure the Elasticsearch client for a single instance on localhost
quarkus.elasticsearch.hosts = localhost:9200

If you need a more advanced configuration, you can find the comprehensive list of supported configuration properties at the end of this guide.

Dev Services

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.elasticsearch.hosts, Quarkus will automatically start an Elasticsearch container when running tests or dev mode, and automatically configure the connection.

When running the production version of the application, the Elasticsearch connection needs to be configured as usual, 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.

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

Programmatically Configuring Elasticsearch

On top of the parametric configuration, you can also programmatically apply additional configuration to the client by implementing a RestClientBuilder.HttpClientConfigCallback and annotating it with ElasticsearchClientConfig. You may provide multiple implementations and configuration provided by each implementation will be applied in a randomly ordered cascading manner.

For example, when accessing an Elasticsearch cluster that is set up for TLS on the HTTP layer, the client needs to trust the certificate that Elasticsearch is using. The following is an example of setting up the client to trust the CA that has signed the certificate that Elasticsearch is using, when that CA certificate is available in a PKCS#12 keystore.

import io.quarkus.elasticsearch.restclient.lowlevel.ElasticsearchClientConfig;
import org.apache.http.impl.nio.client.HttpAsyncClientBuilder;
import org.apache.http.ssl.SSLContextBuilder;
import org.apache.http.ssl.SSLContexts;
import org.elasticsearch.client.RestClientBuilder;

import jakarta.enterprise.context.Dependent;
import javax.net.ssl.SSLContext;
import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.security.KeyStore;

@ElasticsearchClientConfig
public class SSLContextConfigurator implements RestClientBuilder.HttpClientConfigCallback {
    @Override
    public HttpAsyncClientBuilder customizeHttpClient(HttpAsyncClientBuilder httpClientBuilder) {
        try {
            String keyStorePass = "password-for-keystore";
            Path trustStorePath = Paths.get("/path/to/truststore.p12");
            KeyStore truststore = KeyStore.getInstance("pkcs12");
            try (InputStream is = Files.newInputStream(trustStorePath)) {
                truststore.load(is, keyStorePass.toCharArray());
            }
            SSLContextBuilder sslBuilder = SSLContexts.custom()
                    .loadTrustMaterial(truststore, null);
            SSLContext sslContext = sslBuilder.build();
            httpClientBuilder.setSSLContext(sslContext);
        } catch (Exception e) {
            throw new RuntimeException(e);
        }

        return httpClientBuilder;
    }
}

See Elasticsearch documentation for more details on this particular example.

Classes marked with @ElasticsearchClientConfig are made application scoped CDI beans by default. You can override the scope at the class level if you prefer a different scope.

Running an Elasticsearch cluster

As by default, the Elasticsearch client is configured to access a local Elasticsearch cluster on port 9200 (the default Elasticsearch port), if you have a local running instance on this port, there is nothing more to do before being able to test it!

If you want to use Docker to run an Elasticsearch instance, you can use the following command to launch one:

docker run --name elasticsearch  -e "discovery.type=single-node" -e "ES_JAVA_OPTS=-Xms512m -Xmx512m"\
       -e "cluster.routing.allocation.disk.threshold_enabled=false" -e "xpack.security.enabled=false"\
       --rm -p 9200:9200 docker.io/elastic/elasticsearch:8.9.1

Running the application

Let’s start our application in dev mode:

CLI
quarkus dev
Maven
./mvnw quarkus:dev
Gradle
./gradlew --console=plain quarkusDev

You can add new fruits to the list via the following curl command:

curl localhost:8080/fruits -d '{"name": "bananas", "color": "yellow"}' -H "Content-Type: application/json"

And search for fruits by name or color via the following curl command:

curl localhost:8080/fruits/search?color=yellow

Using the Elasticsearch Java Client

Here is a version of the FruitService using the Elasticsearch Java Client instead of the low level one:

import co.elastic.clients.elasticsearch.ElasticsearchClient;
import co.elastic.clients.elasticsearch._types.FieldValue;
import co.elastic.clients.elasticsearch._types.query_dsl.QueryBuilders;
import co.elastic.clients.elasticsearch.core.*;
import co.elastic.clients.elasticsearch.core.search.HitsMetadata;
import jakarta.enterprise.context.ApplicationScoped;
import jakarta.inject.Inject;
import org.acme.elasticsearch.Fruit;

import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;

@ApplicationScoped
public class FruitService {
    @Inject
    ElasticsearchClient client; (1)

    public void index(Fruit fruit) throws IOException {
        IndexRequest<Fruit> request = IndexRequest.of(  (2)
            b -> b.index("fruits")
                .id(fruit.id)
                .document(fruit)); (3)
        client.index(request);  (4)
    }

    public Fruit get(String id) throws IOException {
        GetRequest getRequest = GetRequest.of(
            b -> b.index("fruits")
                .id(id));
        GetResponse<Fruit> getResponse = client.get(getRequest, Fruit.class);
        if (getResponse.found()) {
            return getResponse.source();
        }
        return null;
    }

    public List<Fruit> searchByColor(String color) throws IOException {
        return search("color", color);
    }

    public List<Fruit> searchByName(String name) throws IOException {
        return search("name", name);
    }

    private List<Fruit> search(String term, String match) throws IOException {
        SearchRequest searchRequest = SearchRequest.of(
            b -> b.index("fruits")
                .query(QueryBuilders.match().field(term).query(FieldValue.of(match)).build()._toQuery()));

        SearchResponse<Fruit> searchResponse = client.search(searchRequest, Fruit.class);
        HitsMetadata<Fruit> hits = searchResponse.hits();
        return hits.hits().stream().map(hit -> hit.source()).collect(Collectors.toList());
    }
}
1 We inject an ElasticsearchClient inside the service.
2 We create an Elasticsearch index request using a builder.
3 We directly pass the object to the request as the Java API client has a serialization layer.
4 We send the request to Elasticsearch.

Hibernate Search Elasticsearch

Quarkus supports Hibernate Search with Elasticsearch via the quarkus-hibernate-search-orm-elasticsearch extension.

Hibernate Search Elasticsearch allows to synchronize your Jakarta Persistence entities to an Elasticsearch cluster and offers a way to query your Elasticsearch cluster using the Hibernate Search API.

If you are interested in it, please consult the Hibernate Search with Elasticsearch guide.

Cluster Health Check

If you are using the quarkus-smallrye-health extension, both extensions will automatically add a readiness health check to validate the health of the cluster.

So when you access the /q/health/ready endpoint of your application, you will have information about the cluster status. It uses the cluster health endpoint, the check will be down if the status of the cluster is red, or the cluster is not available.

This behavior can be disabled by setting the quarkus.elasticsearch.health.enabled property to false in your application.properties.

Building a native executable

You can use both clients in a native executable.

You can build a native executable with the usual command:

CLI
quarkus build --native
Maven
./mvnw install -Dnative
Gradle
./gradlew build -Dquarkus.package.type=native

Running it is as simple as executing ./target/elasticsearch-low-level-client-quickstart-1.0.0-SNAPSHOT-runner.

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

Conclusion

Accessing an Elasticsearch cluster from the low level REST client or the Elasticsearch Java client is easy with Quarkus as it provides easy configuration, CDI integration and native support for it.

Configuration Reference

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

Configuration property

Type

Default

Whether a health check is published in case the smallrye-health extension is present.

Environment variable: QUARKUS_ELASTICSEARCH_HEALTH_ENABLED

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boolean

true

The list of hosts of the Elasticsearch servers.

Environment variable: QUARKUS_ELASTICSEARCH_HOSTS

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list of host:port

localhost:9200

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

Environment variable: QUARKUS_ELASTICSEARCH_PROTOCOL

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string

http

The username for basic HTTP authentication.

Environment variable: QUARKUS_ELASTICSEARCH_USERNAME

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string

The password for basic HTTP authentication.

Environment variable: QUARKUS_ELASTICSEARCH_PASSWORD

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string

The connection timeout.

Environment variable: QUARKUS_ELASTICSEARCH_CONNECTION_TIMEOUT

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Duration

1S

The socket timeout.

Environment variable: QUARKUS_ELASTICSEARCH_SOCKET_TIMEOUT

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Duration

30S

The maximum number of connections to all the Elasticsearch servers.

Environment variable: QUARKUS_ELASTICSEARCH_MAX_CONNECTIONS

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int

20

The maximum number of connections per Elasticsearch server.

Environment variable: QUARKUS_ELASTICSEARCH_MAX_CONNECTIONS_PER_ROUTE

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int

10

The number of IO thread. By default, this is the number of locally detected processors.

Thread counts higher than the number of processors should not be necessary because the I/O threads rely on non-blocking operations, but you may want to use a thread count lower than the number of processors.

Environment variable: QUARKUS_ELASTICSEARCH_IO_THREAD_COUNTS

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int

Defines if automatic discovery is enabled.

Environment variable: QUARKUS_ELASTICSEARCH_DISCOVERY_ENABLED

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boolean

false

Refresh interval of the node list.

Environment variable: QUARKUS_ELASTICSEARCH_DISCOVERY_REFRESH_INTERVAL

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Duration

5M

About the Duration format

To write duration values, use the standard java.time.Duration format. See the Duration#parse() javadoc 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.