云消息队列 Confluent 版使用Schema Registry管理Schema。本文将向您介绍Schema Registry的基本操作。
前提条件
设置客户端环境
执行以下命令，安装maven example示例代码，并使用
examples/clients/avro作为项目路径。git clone https://github.com/confluentinc/examples.git #使用该路径下的maven项目进行演示 cd examples/clients/avro git checkout 7.1.0-post在
$HOME/.confluent/路径下创建客户端配置文件java.config。在配置文件中，配置如下配置项。bootstrap.servers=<your broker access address> security.protocol=SASL_SSL #your user should have the authority to access the topic sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='<user>' password='<secret>'; sasl.mechanism=PLAIN schema.registry.url=<your schema registry access address> basic.auth.credentials.source=USER_INFO #your user should have the authority to access the schema registry basic.auth.user.info=<user>:<user-secret>
创建Topic
在主页的左侧导航栏，单击Topics，然后单击右上角的Add topic。
在New Topic页面，设置Topic名称和分区数，单击Create with defaults。
在Topics页面，找到创建好的Topic，单击Topic名称进入Topic详情页。
在Topic详情页，单击Messages页签，然后单击Produce a new message to this topic，向此Topic发送JSON格式的测试数据。
开启Schema格式校验
在目标Topic详情页面，单击Configuration页签。
依次单击，将confluent_value_schema_validation字段设置为true，启用Schema验证消息内容格式。启用后发送和消费数据时将进行格式校验。
创建Schema
执行cat命令，查看maven example项目如下路径的文件内容。
cat src/main/resources/avro/io/confluent/examples/clients/basicavro/Payment.avsc返回结果
{ "namespace": "io.confluent.examples.clients.basicavro", "type": "record", "name": "Payment", "fields": [ {"name": "id", "type": "string"}, {"name": "amount", "type": "double"} ] }在Topic详情页面，单击Schema，然后单击Set a schema。
在Schema页签，单击Avro，将上述Payment.avsc文本填入文本框，单击Create。
Kafka Producer/Consumer Client程序
以下示例使用Maven来配置项目和管理依赖项。完整的pom.xml示例，请参见pom.xml。
创建Producer
在Producer客户端应用程序中，需要设置Kafka相关配置参数。具体的配置请参见上文设置客户端环境。
构造生产者时，需要将消息序列化方式指定为KafkaAvroSerializer类，并将消息值类配置为Payment类。
示例代码如下：
package io.confluent.examples.clients.basicavro;
import io.confluent.kafka.serializers.AbstractKafkaSchemaSerDeConfig;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.serialization.StringSerializer;
import io.confluent.kafka.serializers.KafkaAvroSerializer;
import org.apache.kafka.common.errors.SerializationException;
import java.util.Properties;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.io.FileInputStream;
import java.io.InputStream;
public class ProducerExample {
private static final String TOPIC = "transactions";
private static final Properties props = new Properties();
private static String configFile;
@SuppressWarnings("InfiniteLoopStatement")
public static void main(final String[] args) throws IOException {
if (args.length < 1) {
// Backwards compatibility, assume localhost
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
props.put(AbstractKafkaSchemaSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, "http://localhost:8081");
} else {
// Load properties from a local configuration file
// Create the configuration file (e.g. at '$HOME/.confluent/java.config') with configuration parameters
// to connect to your Kafka cluster, which can be on your local host, Confluent Cloud, or any other cluster.
// Documentation at https://docs.confluent.io/platform/current/tutorials/examples/clients/docs/java.html
configFile = args[0];
if (!Files.exists(Paths.get(configFile))) {
throw new IOException(configFile + " not found.");
} else {
try (InputStream inputStream = new FileInputStream(configFile)) {
props.load(inputStream);
}
}
}
props.put(ProducerConfig.ACKS_CONFIG, "all");
props.put(ProducerConfig.RETRIES_CONFIG, 0);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class);
try (KafkaProducer<String, Payment> producer = new KafkaProducer<String, Payment>(props)) {
for (long i = 0; i < 10; i++) {
final String orderId = "id" + Long.toString(i);
final Payment payment = new Payment(orderId, 1000.00d);
final ProducerRecord<String, Payment> record = new ProducerRecord<String, Payment>(TOPIC, payment.getId().toString(), payment);
producer.send(record);
Thread.sleep(1000L);
}
producer.flush();
System.out.printf("Successfully produced 10 messages to a topic called %s%n", TOPIC);
} catch (final SerializationException e) {
e.printStackTrace();
} catch (final InterruptedException e) {
e.printStackTrace();
}
}
}更多信息，请参见ProducerExample。
说明
pom.xml包含avro-maven-plugin，Payment类二进制文件是在编译期间自动生成的。
运行Producer
进入example项目的examples/clients/avro目录下，执行以下步骤。
执行以下命令，编译项目。
mvn clean compile package查看Topic详情页面的Messages页签。此时应该没有消息记录。
执行Producer代码。
mvn exec:java -Dexec.mainClass=io.confluent.examples.clients.basicavro.ProducerExample \ -Dexec.args="$HOME/.confluent/java.config"该命令使用了之前准备的客户端配置文件
$HOME/.confluent/java.config。命令执行完成后，会输出如下结果：... Successfully produced 10 messages to a topic called transactions [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESS [INFO] ------------------------------------------------------------------------ ...查看结果。此时，您应该可以在Messages页面查看到上一步骤写入到消息。
创建Consumer
在Consumer客户端应用程序中，同样需要设置Kafka相关配置参数。具体的配置详情请参见上文设置客户端环境。构造消费者时，需要将消息反序列化方式指定为KafkaAvroDeSerializer类，并将消息值类配置为Payment类。示例代码如下：
package io.confluent.examples.clients.basicavro;
import io.confluent.kafka.serializers.AbstractKafkaSchemaSerDeConfig;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import io.confluent.kafka.serializers.KafkaAvroDeserializerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import java.time.Duration;
import java.util.Collections;
import java.util.Properties;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.io.FileInputStream;
import java.io.InputStream;
public class ConsumerExample {
private static final String TOPIC = "transactions";
private static final Properties props = new Properties();
private static String configFile;
@SuppressWarnings("InfiniteLoopStatement")
public static void main(final String[] args) throws IOException {
if (args.length < 1) {
// Backwards compatibility, assume localhost
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
props.put(AbstractKafkaSchemaSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, "http://localhost:8081");
} else {
// Load properties from a local configuration file
// Create the configuration file (e.g. at '$HOME/.confluent/java.config') with configuration parameters
// to connect to your Kafka cluster, which can be on your local host, Confluent Cloud, or any other cluster.
// Documentation at https://docs.confluent.io/platform/current/tutorials/examples/clients/docs/java.html
configFile = args[0];
if (!Files.exists(Paths.get(configFile))) {
throw new IOException(configFile + " not found.");
} else {
try (InputStream inputStream = new FileInputStream(configFile)) {
props.load(inputStream);
}
}
}
props.put(ConsumerConfig.GROUP_ID_CONFIG, "test-payments");
props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "1000");
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, KafkaAvroDeserializer.class);
props.put(KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG, true);
try (final KafkaConsumer<String, Payment> consumer = new KafkaConsumer<>(props)) {
consumer.subscribe(Collections.singletonList(TOPIC));
while (true) {
final ConsumerRecords<String, Payment> records = consumer.poll(Duration.ofMillis(100));
for (final ConsumerRecord<String, Payment> record : records) {
final String key = record.key();
final Payment value = record.value();
System.out.printf("key = %s, value = %s%n", key, value);
}
}
}
}
}更多信息，请参见ConsumerExample.。
运行Consumer代码
执行以下命令，编译项目。
mvn clean compile package运行ConsumerExample。
mvn exec:java -Dexec.mainClass=io.confluent.examples.clients.basicavro.ConsumerExample \ -Dexec.args="$HOME/.confluent/java.config"执行成功后，查看输出：
... key = id0, value = {"id": "id0", "amount": 1000.0} key = id1, value = {"id": "id1", "amount": 1000.0} key = id2, value = {"id": "id2", "amount": 1000.0} key = id3, value = {"id": "id3", "amount": 1000.0} key = id4, value = {"id": "id4", "amount": 1000.0} key = id5, value = {"id": "id5", "amount": 1000.0} key = id6, value = {"id": "id6", "amount": 1000.0} key = id7, value = {"id": "id7", "amount": 1000.0} key = id8, value = {"id": "id8", "amount": 1000.0} key = id9, value = {"id": "id9", "amount": 1000.0} ...
相关文档
更多关于Schema Registry的信息，请参见Schema Registry Overview。
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