创建Kafka Avro序列化器:可以使用io.confluent.kafka.serializers.KafkaAvroSerializer类创建一个Kafka Avro序列化器实例。创建Kafka Avro序列化器时需要指定Schema Registry的URL
import org.apache.kafka.common.serialization.StringSerializer
import io.confluent.kafka.serializers.KafkaAvroSerializer
val schemaRegistryUrl = "http://localhost:8081"
val kafkaAvroSerializer = new KafkaAvroSerializer()
kafkaAvroSerializer.configure(Map("schema.registry.url" -> schemaRegistryUrl), false)
准备要序列化的数据:需要将要序列化的数据准备好。例如,下面是一个包含字符串键和Avro记录值的数据:
import org.apache.avro.Schema
import org.apache.avro.generic.GenericData
import org.apache.avro.generic.GenericRecord
val key = "key"
val valueSchemaStr = "{\"type\":\"record\",\"name\":\"User\",\"fields\":[{\"name\":\"name\",\"type\":\"string\"},{\"name\":\"age\",\"type\":\"int\"}]}"
val valueSchema = new Schema.Parser().parse(valueSchemaStr)
val value = new GenericData.Record(valueSchema)
value.put("name", "Alice")
value.put("age", 30)
序列化数据并将其发送到Kafka:可以使用kafkaAvroSerializer序列化数据并将其发送到Kafka主题中。
import org.apache.kafka.clients.producer.{KafkaProducer, ProducerRecord}
val topic = "my_topic"
val producerProperties = Map(
"bootstrap.servers" -> "localhost:9092",
"key.serializer" -> classOf[StringSerializer],
"value.serializer" -> classOf[KafkaAvroSerializer]
)
val producer = new KafkaProducer[String, GenericRecord](producerProperties.asJava)
val record = new ProducerRecord[String, GenericRecord](topic, key, value)
producer.send(record)
上述代码中,key.serializer和value.serializer分别指定键和值的序列化器。在这种情况下,键使用默认的StringSerializer,而值使用Kafka Avro序列化器。