Apache Ignite on your Kubernetes Cluster Part 4: Deployment explained

Previously we saw the Ignite configuration that comes with the Kubernetes installation.
The default configuration does not have persistence enabled so we won’t focus on any storage classes provided by the helm chart.

The default installation uses a stateful set. You can find more information on a stateful set on the Kubernetes documentation.

> kubectl get statefulset ignite-cache -o yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
  creationTimestamp: 2020-04-09T12:29:04Z
  generation: 1
  labels:
    app.kubernetes.io/instance: ignite-cache
    app.kubernetes.io/managed-by: Helm
    app.kubernetes.io/name: ignite
    helm.sh/chart: ignite-1.0.1
  name: ignite-cache
  namespace: default
  resourceVersion: "281390"
  selfLink: /apis/apps/v1/namespaces/default/statefulsets/ignite-cache
  uid: fcaa7bef-84cd-4e7c-aa33-a4312a1d47a9
spec:
  podManagementPolicy: OrderedReady
  replicas: 2
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: ignite-cache
  serviceName: ignite-cache
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: ignite-cache
    spec:
      containers:
      - env:
        - name: IGNITE_QUIET
          value: "false"
        - name: JVM_OPTS
          value: -Djava.net.preferIPv4Stack=true
        - name: OPTION_LIBS
          value: ignite-kubernetes,ignite-rest-http
        image: apacheignite/ignite:2.7.6
        imagePullPolicy: IfNotPresent
        name: ignite
        ports:
        - containerPort: 11211
          protocol: TCP
        - containerPort: 47100
          protocol: TCP
        - containerPort: 47500
          protocol: TCP
        - containerPort: 49112
          protocol: TCP
        - containerPort: 10800
          protocol: TCP
        - containerPort: 8080
          protocol: TCP
        - containerPort: 10900
          protocol: TCP
        resources: {}
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
        volumeMounts:
        - mountPath: /opt/ignite/apache-ignite/config
          name: config-volume
      dnsPolicy: ClusterFirst
      restartPolicy: Always
      schedulerName: default-scheduler
      securityContext: {}
      serviceAccount: ignite-cache
      serviceAccountName: ignite-cache
      terminationGracePeriodSeconds: 30
      volumes:
      - configMap:
          defaultMode: 420
          items:
          - key: ignite-config.xml
            path: default-config.xml
          name: ignite-cache-configmap
        name: config-volume
  updateStrategy:
    rollingUpdate:
      partition: 0
    type: RollingUpdate
status:
  replicas: 0

As you can see the Ingite configuration has been mounted through the configmap. Also you can see that this pod will use a specific service account.
Through the environment variables certain libraries are enabled which provide more features on the Ignite cluster. Also the ports needed for the communication and various protocols are being specified.

The last step is the service. All the ignite nodes shall be load balancer behind the Kubernetes service.

> kubectl get svc ignite-cache -o yaml
apiVersion: v1
kind: Service
metadata:
  creationTimestamp: 2020-04-09T12:29:04Z
  labels:
    app: ignite-cache
  name: ignite-cache
  namespace: default
  resourceVersion: "281389"
  selfLink: /api/v1/namespaces/default/services/ignite-cache
  uid: 5be68e28-a57c-4cb5-b610-b708bff80da7
spec:
  clusterIP: None
  ports:
  - name: jdbc
    port: 11211
    protocol: TCP
    targetPort: 11211
  - name: spi-communication
    port: 47100
    protocol: TCP
    targetPort: 47100
  - name: spi-discovery
    port: 47500
    protocol: TCP
    targetPort: 47500
  - name: jmx
    port: 49112
    protocol: TCP
    targetPort: 49112
  - name: sql
    port: 10800
    protocol: TCP
    targetPort: 10800
  - name: rest
    port: 8080
    protocol: TCP
    targetPort: 8080
  - name: thin-clients
    port: 10900
    protocol: TCP
    targetPort: 10900
  selector:
    app: ignite-cache
  sessionAffinity: None
  type: ClusterIP
status:
  loadBalancer: {}

Whether you add a new node or you add an ignite client node your ignite cluster shall be reached through this Kubernetes service. Apart from, that based on the Kubernetes services you can make this cache public or internal.

Apache Ignite on your Kubernetes Cluster Part 3: Configuration explained

Previously we had a look on the RBAC needed for and ignite cluster in Kubernetes.
This blogs focuses on the deployment and the configuration of the cache.

The default ignite installation uses and xml based configuration. It is easy to mount files using configmaps.

> kubectl get configmap ignite-cache-configmap -o yaml
NAME                     DATA   AGE
ignite-cache-configmap   1      32d
gkatzioura@MacBook-Pro-2 templates % kubectl get configmap ignite-cache-configmap -o yaml
apiVersion: v1
data:
  ignite-config.xml: "....\n"
kind: ConfigMap
metadata:
  creationTimestamp: 2020-03-07T22:23:50Z
  name: ignite-cache-configmap
  namespace: default
  resourceVersion: "137521"
  selfLink: /api/v1/namespaces/default/configmaps/ignite-cache-configmap
  uid: ff530e3d-10d6-4708-817f-f9845886c1b0

Since viewing the xml from the configmap is cumbersome this is the actual xml

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
	   xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="
		       http://www.springframework.org/schema/beans        http://www.springframework.org/schema/beans/spring-beans.xsd">
	<bean class="org.apache.ignite.configuration.IgniteConfiguration">
		<property
				name="peerClassLoadingEnabled" value="false"/>
		<property name="dataStorageConfiguration">
			<bean class="org.apache.ignite.configuration.DataStorageConfiguration">
			</bean>
		</property>
		<property
				name="discoverySpi">
			<bean class="org.apache.ignite.spi.discovery.tcp.TcpDiscoverySpi">
				<property name="ipFinder">
					<bean class="org.apache.ignite.spi.discovery.tcp.ipfinder.kubernetes.TcpDiscoveryKubernetesIpFinder">
						<property name="namespace" value="default"/>
						<property
								name="serviceName" value="ignite-cache"/>
					</bean>
				</property>
			</bean>
		</property>
	</bean>
</beans>

The default DataStorageConfiguration is being used.
What you can see different from other ignite installations is TCP discovery. The tcp discover used is using the Kubernetes TCP based discovery.

The next blog focuses on the services and the deployment.

Apache Ignite on your Kubernetes Cluster Part 2: RBAC Explained

So previously we had a vanilla installation of Apache Ignite on Kubernetes.

You had a cache service running however all you did was installing a helm chart.
In this blog we shall evaluate what is installed and take notes for our futures helm charts.

The first step would be to view the helm chart.

> helm list
NAME        	NAMESPACE	REVISION	UPDATED                             	STATUS  	CHART       	APP VERSION
ignite-cache	default  	1       	2020-03-07 22:23:49.918924 +0000 UTC	deployed	ignite-1.0.1	2.7.6

Now let’s download it

> helm fetch stable/ignite
> tar xvf ignite-1.0.1.tgz
> cd ignite/; ls -R
Chart.yaml	README.md	templates	values.yaml

./templates:
NOTES.txt			account-role.yaml		persistence-storage-class.yaml	service-account.yaml		svc.yaml
_helpers.tpl			configmap.yaml			role-binding.yaml		stateful-set.yaml		wal-storage-class.yaml

Reading through the template files is a bit challenging (well they are tempaltes :P) so we shall just check what was installed through our previous blog.

Let’s get started with the account-role. The cluster role that ignite shall use needs to be able to get/list/watch the pods and the endpoints. It makes sense since there is a need for discovery between the nodes.

> kubectl get ClusterRole ignite-cache -o yaml
kind: ClusterRole
metadata:
  creationTimestamp: 2020-03-07T22:23:50Z
  name: ignite-cache
  resourceVersion: "137525"
  selfLink: /apis/rbac.authorization.k8s.io/v1/clusterroles/ignite-cache
  uid: 0cad0689-2f94-4b74-87bc-b468e2ac78ae
rules:
- apiGroups:
  - ""
  resources:
  - pods
  - endpoints
  verbs:
  - get
  - list
  - watch

In order to use this role you need a service account. A service account is create with a token.

> kubectl get serviceaccount ignite-cache -o yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  creationTimestamp: 2020-03-07T22:23:50Z
  name: ignite-cache
  namespace: default
  resourceVersion: "137524"
  selfLink: /api/v1/namespaces/default/serviceaccounts/ignite-cache
  uid: 7aab67e5-04db-41a8-b73d-e76e34ca1d8e
secrets:
- name: ignite-cache-token-8rln4

Then we have the role binding. We have a new service account called the ignite-cache which has the role ignite-cache.

> kubectl get ClusterRoleBinding ignite-cache -o yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  creationTimestamp: 2020-03-07T22:23:50Z
  name: ignite-cache
  resourceVersion: "137526"
  selfLink: /apis/rbac.authorization.k8s.io/v1/clusterrolebindings/ignite-cache
  uid: 1e180bd1-567f-4979-a278-ba2e420ed482
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: ignite-cache
subjects:
- kind: ServiceAccount
  name: ignite-cache
  namespace: default

It is important for you ignite workloads to use this service account and its token. By doing so they have the permissions to discover the other nodes in your cluster.

The next blog focuses on the configuration.

Apache Ignite on your Kubernetes Cluster Part 1: Vanilla installation

By all means apache Ignite is an Amazing Open Source project.
Don’t assume it’s just a  Cache. It provides way more.

 

Kubernetes gets more popular by the day and is also a very convenient tool.
In this tutorial we shall integrate ignite and Kubernetes.

The first step would be to spin up Minikube.

To get ignite on your Kubernetes installation the first step would be to install the helm chart.

>helm repo add stable https://kubernetes-charts.storage.googleapis.com
>helm install ignite-cache stable/ignite
NAME: ignite-cache
LAST DEPLOYED: Sat Mar  7 22:23:49 2020
NAMESPACE: default
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
To check cluster state please run:

kubectl exec -n default ignite-cache-0 -- /opt/ignite/apache-ignite/bin/control.sh --state

Eventually after this command is issued it is expected to have an ignite cache setup on your kubernetes cluster.

>kubectl get pods
NAME             READY   STATUS    RESTARTS   AGE
ignite-cache-0   1/1     Running   0          79s
ignite-cache-1   1/1     Running   0          13s
>kubectl get svc ignite-cache
ignite-cache   ClusterIP   None         <none>        11211/TCP,47100/TCP,47500/TCP,49112/TCP,10800/TCP,8080/TCP,10900/TCP   6m24s

To those familiar with Kubernetes an ignite cache has just been spinned up in your kubernetes cluster and your applications can use the ignite service within the cluster.
The next blog focuses on the service account needed.

Spring Boot and Micrometer with InlfuxDB Part 2: Adding InfluxDB

Since we added our base application it is time for us to spin up an InfluxDB instance.

We shall follow a previous tutorial and add a docker instance.

docker run –rm -p 8086:8086 –name influxdb-local influxdb

Time to add the micrometer InfluxDB dependency on our pom

<dependencies>
...
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-actuator</artifactId>
        </dependency>
        <dependency>
            <groupId>io.micrometer</groupId>
            <artifactId>micrometer-core</artifactId>
            <version>1.3.2</version>
        </dependency>
        <dependency>
            <groupId>io.micrometer</groupId>
            <artifactId>micrometer-registry-influx</artifactId>
            <version>1.3.2</version>
        </dependency>
...
</dependencies>

Time to add the configuration through the application.yaml

management:
  metrics:
    export:
      influx:
        enabled: true
        db: devjobsapi
        uri: http://127.0.0.1:8086
  endpoints:
    web:
      expose: "*"

Let’s spin up our application and do some requests.
After some time we can check the database and the data contained.

docker exec -it influxdb-local influx
> SHOW DATABASES;
name: databases
name
----
_internal
devjobsapi
> use devjobsapi
Using database devjobsapi
> SHOW MEASUREMENTS
name: measurements
name
----
http_server_requests
jvm_buffer_count
jvm_buffer_memory_used
jvm_buffer_total_capacity
jvm_classes_loaded
jvm_classes_unloaded
jvm_gc_live_data_size
jvm_gc_max_data_size
jvm_gc_memory_allocated
jvm_gc_memory_promoted
jvm_gc_pause
jvm_memory_committed
jvm_memory_max
jvm_memory_used
jvm_threads_daemon
jvm_threads_live
jvm_threads_peak
jvm_threads_states
logback_events
process_cpu_usage
process_files_max
process_files_open
process_start_time
process_uptime
system_cpu_count
system_cpu_usage
system_load_average_1m

That’s pretty awesome. Let’s check the endpoints accessed.

> SELECT*FROM http_server_requests;
name: http_server_requests
time                count exception mean        method metric_type outcome status sum         upper       uri
----                ----- --------- ----        ------ ----------- ------- ------ ---         -----       ---
1582586157093000000 1     None      252.309331  GET    histogram   SUCCESS 200    252.309331  252.309331  /actuator
1582586157096000000 0     None      0           GET    histogram   SUCCESS 200    0           2866.531375 /jobs/github/{page}

Pretty great! The next step would be to visualise those metrics.

Spring Boot and Micrometer with InlfuxDB Part 1: The base project

To those who follow this blog it’s no wonder that I tend to use InfluxDB a lot. I like the fact that it is a real single purpose database (time series) with many features and also comes with enterprise support.

Spring is also one of the tools of my choice.
Thus in this blog we shall integrate spring with micrometer and InfluxDB.

Our application will be a rest api for jobs.
Initially it will fetch the Jobs from Github’s job api as shown here.

Let’s start with a pom

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.2.4.RELEASE</version>
    </parent>

    <groupId>com.gkatzioura</groupId>
    <artifactId>DevJobsApi</artifactId>
    <version>1.0-SNAPSHOT</version>

    <build>
        <defaultGoal>spring-boot:run</defaultGoal>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>8</source>
                    <target>8</target>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>

    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-webflux</artifactId>
        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <version>1.18.12</version>
            <scope>provided</scope>
        </dependency>
   </dependencies>
</project>

Let’s add the Job Repository for GitHub.

package com.gkatzioura.jobs.repository;

import java.util.List;

import org.springframework.http.HttpMethod;
import org.springframework.stereotype.Repository;
import org.springframework.web.reactive.function.client.WebClient;

import com.gkatzioura.jobs.model.Job;

import reactor.core.publisher.Mono;

@Repository
public class GitHubJobRepository {

    private WebClient githubClient;

    public GitHubJobRepository() {
        this.githubClient = WebClient.create("https://jobs.github.com");
    }

    public Mono<List<Job>> getJobsFromPage(int page) {

        return githubClient.method(HttpMethod.GET)
                           .uri("/positions.json?page=" + page)
                           .retrieve()
                           .bodyToFlux(Job.class)
                           .collectList();
    }

}

The Job model

package com.gkatzioura.jobs.model;

import lombok.Data;

@Data
public class Job {

    private String id;
    private String type;
    private String url;
    private String createdAt;
    private String company;
    private String companyUrl;
    private String location;
    private String title;
    private String description;

}

The controller

package com.gkatzioura.jobs.controller;

import java.util.List;

import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

import com.gkatzioura.jobs.model.Job;
import com.gkatzioura.jobs.repository.GitHubJobRepository;

import reactor.core.publisher.Mono;

@RestController
@RequestMapping("/jobs")
public class JobsController {

    private final GitHubJobRepository gitHubJobRepository;

    public JobsController(GitHubJobRepository gitHubJobRepository) {
        this.gitHubJobRepository = gitHubJobRepository;
    }

    @GetMapping("/github/{page}")
    private Mono<List<Job>> getEmployeeById(@PathVariable int page) {
        return gitHubJobRepository.getJobsFromPage(page);
    }

}

And last but not least the main application.

package com.gkatzioura;


import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.security.reactive.ReactiveSecurityAutoConfiguration;

@SpringBootApplication
@EnableAutoConfiguration(exclude = {
        ReactiveSecurityAutoConfiguration.class
})
public class Application {

    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }
}

On the next blog we are going to integrate with InfluxDB and micrometer.

Scala Main class

Adding a main class is Scala is something that I always end up searching so next time it shall be through my blog.

You can go for the extends App option

One way is to add a main class by extending the App class. Everything else that get’s executed on that block is part of the “main” function.

package com.gkatzioura

object MainClass extends App {

  println("Hello world"!)
}

Then you can access the arguments since they are a variable on the App.

package com.gkatzioura

object MainClass extends App {

  for( arg <- args ) {
    println(arg)
  }

}

Add a main method

This is the most Java familiar option

package com.gkatzioura

object MainClass {

  def main(args: Array[String]): Unit = {
    println("Hello, world!")
  }

}

As expected you receive the program arguments through the function arguments.

package com.gkatzioura

object MainClass {

  def main(args: Array[String]): Unit = {
    for( arg <- args ) {
      println(arg)
    }
  }

}

AtomicInteger on Java and Round-Robin

AtomicInteger belongs to the family of Atomic Variables. The main benefit is that using it, is not blocking instead of doing a blocking synchronization, thus you avoid the suspension and rescheduling of thread.

The AtomicInteger is based on the Compare and Swap mechanism and is part of the scalar group of the atomic variables.

Our first use case would be a function on a web page which might be accessed multiple times.

package com.gkatzioura.concurrency;

import java.util.concurrent.atomic.AtomicInteger;

public class AtomicIntegerExample {

    private AtomicInteger atomicInteger = new AtomicInteger();
    public void serveRequest() {
        atomicInteger.incrementAndGet();
        /**
         * logic
         */
    }

    public int requestsServed() {
        return atomicInteger.get();
    }
}

And the test for our use case

package com.gkatzioura.concurrency;

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;

import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;

public class AtomicIntegerExampleTest {

    private AtomicIntegerExample atomicIntegerExample;

    @BeforeEach
    void setUp() {
        atomicIntegerExample = new AtomicIntegerExample();
    }

    @Test
    void testConcurrentIncrementAndGet() throws ExecutionException, InterruptedException {
        final int threads = 10;

        ExecutorService executorService = Executors.newFixedThreadPool(threads);

        List<Future> futures = new ArrayList();

        for (int i = 0; i  {
                atomicIntegerExample.serveRequest();
                return null;
            }));
        }

        for(Future future: futures) {
            future.get();
        }

        Assertions.assertEquals(10,atomicIntegerExample.requestsServed());
    }

}

Apart from using atomic integer as a counter, you can use it in various cases. For example a thread safe round robin algorithm.

package com.gkatzioura.concurrency;

import java.util.concurrent.atomic.AtomicInteger;

public class AtomicIntegerRoundRobin {

    private final int totalIndexes;
    private final AtomicInteger atomicInteger = new AtomicInteger(-1);

    public AtomicIntegerRoundRobin(int totalIndexes) {
        this.totalIndexes = totalIndexes;
    }

    public int index() {
        int currentIndex;
        int nextIndex;

        do {
            currentIndex = atomicInteger.get();
            nextIndex = currentIndex< Integer.MAX_VALUE ? currentIndex+1: 0;
        } while (!atomicInteger.compareAndSet(currentIndex, nextIndex));

        return nextIndex % totalIndexes;
    }

}

The totalIndex is the total number of indexes. When a request for the next index is being requested then the counter shall be incremented and a compare and set operation will take place. If it fails due to another thread then it will try the operation again and will get the next value of the counter.
A modulo operation will give the current index. If the atomic Integer reaches the max value it shall be reset to zero. The reset can cause an edge case and change the order of the indexes. If this is an issue you can adjust you max value based on your total index size in order to avoid this.

Also some testing on that.

package com.gkatzioura.concurrency;

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;

import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;

class AtomicIntegerRoundRobinTest {

    private static final int MAX_INDEX = 10;

    private AtomicIntegerRoundRobin atomicIntegerRoundRobin;

    @BeforeEach
    void setUp() {
        atomicIntegerRoundRobin = new AtomicIntegerRoundRobin(MAX_INDEX);
    }

    @Test
    void testIndexesSerially() {
        for(long i=0;i<MAX_INDEX*20;i++) {
            System.out.println(atomicIntegerRoundRobin.index());
        }

        Assertions.assertEquals(0, atomicIntegerRoundRobin.index());
    }

    @Test
    void testIndexesConcurrently() throws ExecutionException, InterruptedException {
        ExecutorService executorService = Executors.newFixedThreadPool(4);

        List<Future> futures = new ArrayList();

        for (int i = 0; i  atomicIntegerRoundRobin.index()));
        }

        for(Future future: futures) {
            System.out.println(future.get());
        }

        Assertions.assertEquals(0,atomicIntegerRoundRobin.index());
    }

}

Read replicas and Spring Data Part 4: Configuring the read repository

Previously we set up two EntityManagers in the same application. One for the reads and one for the writes. Now it’s time to create our read repository.

The read only repository will use the secondary read only EntityManager.

In order to make it a read only repository, it is essential not to have any save and persist actions.

package com.gkatzioura.springdatareadreplica.repository;

import java.util.List;

import org.springframework.data.repository.Repository;

import com.gkatzioura.springdatareadreplica.config.ReadOnlyRepository;
import com.gkatzioura.springdatareadreplica.entity.Employee;

/**
 * This is a read only repository
 */
public interface ReadEmployeeRepository extends Repository {

    List findAll();

}

Our next task would be to create this repository with the read database entity manager.
This means that all repositories shall be created using the default entity manager except from the read only repositories.

I would create an Annotation first. This annotation will declare my repository as Read only. Also I will use this annotation for the scanning operation so that the appropriate EntityManager will be used.

package com.gkatzioura.springdatareadreplica.config;

import java.lang.annotation.Documented;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE})
@Documented
public @interface ReadOnlyRepository {
}

Now I know that spring boot removes the need for annotations and does repository creation in an automated way however our case is a peculiar one.

By making some adjustments our read only repository will look like this

package com.gkatzioura.springdatareadreplica.repository;

import java.util.List;

import org.springframework.data.repository.Repository;

import com.gkatzioura.springdatareadreplica.config.ReadOnlyRepository;
import com.gkatzioura.springdatareadreplica.entity.Employee;

/**
 * This is a read only repository
 */
@ReadOnlyRepository
public interface ReadEmployeeRepository extends Repository {

    List findAll();

}

And now it’s time to work with our repository scanning. All the repositories will be injected with the main EntityManager except from the ones annotated with the @ReadOnlyRepository annotation.

package com.gkatzioura.springdatareadreplica.config;

import javax.sql.DataSource;

import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.jdbc.DataSourceBuilder;
import org.springframework.boot.orm.jpa.EntityManagerFactoryBuilder;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
import org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean;

@Configuration
@EnableJpaRepositories(
        basePackages = "com.gkatzioura",
        excludeFilters = @ComponentScan.Filter(ReadOnlyRepository.class),
        entityManagerFactoryRef = "entityManagerFactory"
)
public class PrimaryEntityManagerConfiguration {

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.url}")
    private String url;

    @Bean
    @Primary
    public DataSource dataSource() throws Exception {
        return DataSourceBuilder.create()
                                .url(url)
                                .username(username)
                                .password(password)
                                .driverClassName("org.postgresql.Driver")
                                .build();
    }

    @Bean
    @Primary
    public LocalContainerEntityManagerFactoryBean entityManagerFactory(
            EntityManagerFactoryBuilder builder,
            @Qualifier("dataSource") DataSource dataSource) {
        return builder.dataSource(dataSource)
                      .packages("com.gkatzioura.springdatareadreplica")
                      .persistenceUnit("main")
                      .build();
    }

}

Also we will add the configuration for the read only repositories.

package com.gkatzioura.springdatareadreplica.config;

import javax.sql.DataSource;

import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.jdbc.DataSourceBuilder;
import org.springframework.boot.orm.jpa.EntityManagerFactoryBuilder;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
import org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean;

@Configuration
@EnableJpaRepositories(
        basePackages = "com.gkatzioura",
        includeFilters= @ComponentScan.Filter(ReadOnlyRepository.class),
        entityManagerFactoryRef = "readEntityManagerFactory"
)
public class ReadOnlyEntityManagerConfiguration {

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.readUrl}")
    private String readUrl;

    @Bean
    public DataSource readDataSource() throws Exception {
        return DataSourceBuilder.create()
                                .url(readUrl)
                                .username(username)
                                .password(password)
                                .driverClassName("org.postgresql.Driver")
                                .build();
    }

    @Bean
    public LocalContainerEntityManagerFactoryBean readEntityManagerFactory(
            EntityManagerFactoryBuilder builder,
            @Qualifier("readDataSource") DataSource dataSource) {
        return builder.dataSource(dataSource)
                      .packages("com.gkatzioura.springdatareadreplica")
                      .persistenceUnit("read")
                      .build();
    }

}

The secondary entity manager will be injected only to the repositories that only have the @ReadOnlyRepository annotation.

And to show this let’s make some changes to our controller.

package com.gkatzioura.springdatareadreplica.controller;

import java.util.List;

import org.springframework.http.HttpStatus;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.ResponseStatus;
import org.springframework.web.bind.annotation.RestController;

import com.gkatzioura.springdatareadreplica.entity.Employee;
import com.gkatzioura.springdatareadreplica.repository.EmployeeRepository;
import com.gkatzioura.springdatareadreplica.repository.ReadEmployeeRepository;

@RestController
public class EmployeeContoller {

    private final EmployeeRepository employeeRepository;
    private final ReadEmployeeRepository readEmployeeRepository;

    public EmployeeContoller(EmployeeRepository employeeRepository,
                             ReadEmployeeRepository readEmployeeRepository) {
        this.employeeRepository = employeeRepository;
        this.readEmployeeRepository = readEmployeeRepository;
    }

    @GetMapping("/employee")
    public List getEmployees() {
        return employeeRepository.findAll();
    }

    @GetMapping("/employee/read")
    public List getEmployeesRead() {
        return readEmployeeRepository.findAll();
    }

    @PostMapping("/employee")
    @ResponseStatus(HttpStatus.CREATED)
    public void addEmployee(@RequestBody Employee employee) {
        employeeRepository.save(employee);
    }

}

As you add employees to the system the read only repository will keep fetching the old employees while the main repository will fetch all of them including the recently persisted.

Read replicas and Spring Data Part 3: Configuring two entity managers

Our previous setup works as expected. What we shall do now is to get one step further and configure two separate entity managers without affecting the functionality we achieved previously.

The first step would be to set the default entity manager configuration to a primary one.
This is the first step

package com.gkatzioura.springdatareadreplica.config;

import javax.sql.DataSource;

import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.jdbc.DataSourceBuilder;
import org.springframework.boot.orm.jpa.EntityManagerFactoryBuilder;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
import org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean;

@Configuration
public class PrimaryEntityManagerConfiguration {

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.url}")
    private String url;

    @Bean
    @Primary
    public DataSource dataSource() throws Exception {
        return DataSourceBuilder.create()
                                .url(url)
                                .username(username)
                                .password(password)
                                .driverClassName("org.postgresql.Driver")
                                .build();
    }

    @Bean
    @Primary
    public LocalContainerEntityManagerFactoryBean entityManagerFactory(
            EntityManagerFactoryBuilder builder,
            @Qualifier("dataSource") DataSource dataSource) {
        return builder.dataSource(dataSource)
                      .packages("com.gkatzioura.springdatareadreplica")
                      .persistenceUnit("main")
                      .build();
    }

}

If you run your application with this configuration it will run just like our application previously.
Now it is time to configure the read only entity manager.

package com.gkatzioura.springdatareadreplica.config;

import javax.sql.DataSource;

import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.jdbc.DataSourceBuilder;
import org.springframework.boot.orm.jpa.EntityManagerFactoryBuilder;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Primary;
import org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean;

@Configuration
public class ReadOnlyEntityManagerConfiguration {

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.readUrl}")
    private String readUrl;

    @Bean
    public DataSource readDataSource() throws Exception {
        return DataSourceBuilder.create()
                                .url(readUrl)
                                .username(username)
                                .password(password)
                                .driverClassName("org.postgresql.Driver")
                                .build();
    }

    @Bean
    public LocalContainerEntityManagerFactoryBean readEntityManagerFactory(
            EntityManagerFactoryBuilder builder,
            @Qualifier("readDataSource") DataSource dataSource) {
        return builder.dataSource(dataSource)
                      .packages("com.gkatzioura.springdatareadreplica")
                      .persistenceUnit("read")
                      .build();
    }

}

Also I will add a method to a controller in order to save the models.

package com.gkatzioura.springdatareadreplica.controller;

import java.util.List;

import org.springframework.http.HttpStatus;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.ResponseStatus;
import org.springframework.web.bind.annotation.RestController;

import com.gkatzioura.springdatareadreplica.entity.Employee;
import com.gkatzioura.springdatareadreplica.repository.EmployeeRepository;

@RestController
public class EmployeeContoller {

    private final EmployeeRepository employeeRepository;

    public EmployeeContoller(EmployeeRepository employeeRepository) {
        this.employeeRepository = employeeRepository;
    }

    @GetMapping("/employee")
    public List<Employee> getEmployees() {
        return employeeRepository.findAll();
    }

    @PostMapping("/employee")
    @ResponseStatus(HttpStatus.CREATED)
    public void addEmployee(@RequestBody Employee employee) {
        employeeRepository.save(employee);
    }

}

If you do try to add the an employee using the controller and then query the read database you shall see that no entry is being added at all.

So we have our primary entity manager up and running and we also have a secondary one. The secondary one is not used yet. The next blog focuses on putting the secondary read only entity manager in use.