BAEL-2885 Spring Cloud Stream with Kakfa (#7114)
* BAEL-2927 added logging configuration for tomcat logs * BAEL-2885 coding done * BAEL-2885 formating done * BAEL-2885 scheam namespace fixed * fixed logback issue and added group name in config * updated code to use the correct header for partition key * removed the partition count * updated the code for given comments * BAEL-2885 removed the schema registry client dependency
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<project xmlns="http://maven.apache.org/POM/4.0.0"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<artifactId>spring-cloud-stream-kafka</artifactId>
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<name>spring-cloud-stream-kafka</name>
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<description>Simple Spring Cloud Stream</description>
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<packaging>jar</packaging>
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<parent>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-parent</artifactId>
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<version>2.1.5.RELEASE</version>
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</parent>
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<properties>
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<java.version>1.8</java.version>
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<spring-cloud.version>Greenwich.SR1</spring-cloud.version>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.springframework.cloud</groupId>
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<artifactId>spring-cloud-stream-binder-kafka</artifactId>
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</dependency>
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<dependency>
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<groupId>org.springframework.cloud</groupId>
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<artifactId>spring-cloud-stream-schema</artifactId>
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</dependency>
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<dependency>
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<groupId>org.springframework.cloud</groupId>
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<artifactId>spring-cloud-stream-test-support</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>io.confluent</groupId>
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<artifactId>kafka-avro-serializer</artifactId>
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<version>4.0.0</version>
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</dependency>
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<dependency>
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<groupId>org.apache.avro</groupId>
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<artifactId>avro-compiler</artifactId>
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<version>1.8.2</version>
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</dependency>
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<dependency>
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<groupId>org.apache.avro</groupId>
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<artifactId>avro-maven-plugin</artifactId>
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<version>1.8.2</version>
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</dependency>
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</dependencies>
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<dependencyManagement>
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<dependencies>
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<dependency>
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<groupId>org.springframework.cloud</groupId>
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<artifactId>spring-cloud-dependencies</artifactId>
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<version>${spring-cloud.version}</version>
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<type>pom</type>
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<scope>import</scope>
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</dependency>
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</dependencies>
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</dependencyManagement>
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<build>
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<plugins>
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<plugin>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-maven-plugin</artifactId>
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</plugin>
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<plugin>
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<groupId>org.apache.avro</groupId>
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<artifactId>avro-maven-plugin</artifactId>
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<version>1.8.2</version>
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<executions>
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<execution>
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<id>schemas</id>
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<phase>generate-sources</phase>
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<goals>
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<goal>schema</goal>
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<goal>protocol</goal>
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<goal>idl-protocol</goal>
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</goals>
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<configuration>
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<sourceDirectory>${project.basedir}/src/main/resources/</sourceDirectory>
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<outputDirectory>${project.basedir}/src/main/java/</outputDirectory>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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<repositories>
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<repository>
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<id>confluent</id>
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<url>https://packages.confluent.io/maven/</url>
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</repository>
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</repositories>
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</project>
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package com.baeldung;
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import org.springframework.boot.SpringApplication;
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import org.springframework.boot.autoconfigure.SpringBootApplication;
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import org.springframework.cloud.stream.annotation.EnableBinding;
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import org.springframework.cloud.stream.messaging.Processor;
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import org.springframework.cloud.stream.schema.client.EnableSchemaRegistryClient;
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@SpringBootApplication
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@EnableBinding(Processor.class)
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@EnableSchemaRegistryClient
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public class AvroKafkaApplication {
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public static void main(String[] args) {
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SpringApplication.run(AvroKafkaApplication.class, args);
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}
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}
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package com.baeldung.config;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.cloud.stream.schema.client.ConfluentSchemaRegistryClient;
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import org.springframework.cloud.stream.schema.client.SchemaRegistryClient;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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@Configuration
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public class SchemRegistryConfig {
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@Bean
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public SchemaRegistryClient schemaRegistryClient(@Value("${spring.cloud.stream.kafka.binder.producer-properties.schema.registry.url}") String endPoint) {
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ConfluentSchemaRegistryClient client = new ConfluentSchemaRegistryClient();
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client.setEndpoint(endPoint);
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return client;
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}
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}
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package com.baeldung.consumer;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.cloud.stream.annotation.StreamListener;
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import org.springframework.cloud.stream.messaging.Processor;
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import org.springframework.stereotype.Service;
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import com.baeldung.schema.Employee;
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@Service
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public class AvroConsumer {
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private static final Logger LOGGER = LoggerFactory.getLogger(AvroConsumer.class);
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@StreamListener(Processor.INPUT)
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public void consumeEmployeeDetails(Employee employeeDetails) {
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LOGGER.info("Let's process employee details: {}", employeeDetails);
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}
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}
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package com.baeldung.controller;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.web.bind.annotation.PathVariable;
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import org.springframework.web.bind.annotation.PostMapping;
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import org.springframework.web.bind.annotation.RestController;
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import com.baeldung.producer.AvroProducer;
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@RestController
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public class AvroController {
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@Autowired
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private AvroProducer avroProducer;
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@PostMapping("/employees/{id}/{firstName}/{lastName}")
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public String producerAvroMessage(@PathVariable int id, @PathVariable String firstName, @PathVariable String lastName) {
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avroProducer.produceEmployeeDetails(id, firstName, lastName);
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return "Sent employee details to consumer";
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}
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}
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package com.baeldung.producer;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.cloud.stream.messaging.Processor;
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import org.springframework.kafka.support.KafkaHeaders;
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import org.springframework.messaging.Message;
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import org.springframework.messaging.support.MessageBuilder;
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import org.springframework.stereotype.Service;
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import com.baeldung.schema.Employee;
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import com.baeldung.schema.EmployeeKey;
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@Service
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public class AvroProducer {
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@Autowired
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private Processor processor;
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public void produceEmployeeDetails(int empId, String firstName, String lastName) {
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// creating employee details
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Employee employee = new Employee();
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employee.setId(empId);
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employee.setFirstName(firstName);
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employee.setLastName(lastName);
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employee.setDepartment("IT");
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employee.setDesignation("Engineer");
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// creating partition key for kafka topic
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EmployeeKey employeeKey = new EmployeeKey();
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employeeKey.setId(empId);
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employeeKey.setDepartmentName("IT");
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Message<Employee> message = MessageBuilder.withPayload(employee)
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.setHeader(KafkaHeaders.MESSAGE_KEY, employeeKey)
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.build();
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processor.output()
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.send(message);
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}
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}
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spring:
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cloud:
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stream:
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default:
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producer:
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useNativeEncoding: true
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consumer:
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useNativeEncoding: true
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bindings:
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input:
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destination: employee-details
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content-type: application/*+avro
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group: group-1
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concurrency: 3
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output:
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destination: employee-details
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content-type: application/*+avro
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kafka:
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binder:
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producer-properties:
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key.serializer: io.confluent.kafka.serializers.KafkaAvroSerializer
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value.serializer: io.confluent.kafka.serializers.KafkaAvroSerializer
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schema.registry.url: http://localhost:8081
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consumer-properties:
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key.deserializer: io.confluent.kafka.serializers.KafkaAvroDeserializer
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value.deserializer: io.confluent.kafka.serializers.KafkaAvroDeserializer
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schema.registry.url: http://localhost:8081
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specific.avro.reader: true
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{
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"type": "record",
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"name": "EmployeeKey",
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"namespace": "com.baeldung.schema",
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"fields": [
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{
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"name": "id",
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"type": "int"
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},
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{
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"name": "departmentName",
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"type": "string"
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}]
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}
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{
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"type": "record",
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"name": "Employee",
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"namespace": "com.baeldung.schema",
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"fields": [
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{
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"name": "id",
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"type": "int"
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},
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{
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"name": "firstName",
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"type": "string"
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},
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{
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"name": "lastName",
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"type": "string"
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},
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{
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"name": "department",
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"type": "string",
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"default": "IT "
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},
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{
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"name": "designation",
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"type": "string",
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"default": "Software Engineer"
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}
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]
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}
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