Akka Stream没有直接实现Kafka Stream所实现的连接语义。但是,你可以使用Akka Stream和Alpakka Kafka来实现类似的连接语义。下面是一个示例代码,演示如何使用Akka Stream和Alpakka Kafka实现Kafka连接语义:
import akka.actor.ActorSystem
import akka.kafka.scaladsl.Consumer
import akka.kafka.scaladsl.Producer
import akka.stream.ActorMaterializer
import akka.stream.scaladsl.{Sink, Source}
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.kafka.clients.producer.ProducerRecord
import org.apache.kafka.common.serialization.{ByteArrayDeserializer, StringDeserializer, StringSerializer}
import scala.concurrent.ExecutionContextExecutor
object KafkaConnectionExample extends App {
implicit val system: ActorSystem = ActorSystem("kafka-connection-example")
implicit val materializer: ActorMaterializer = ActorMaterializer()
implicit val executionContext: ExecutionContextExecutor = system.dispatcher
val bootstrapServers = "localhost:9092"
val consumerSettings = ConsumerSettings(system, new ByteArrayDeserializer, new StringDeserializer)
.withBootstrapServers(bootstrapServers)
.withGroupId("test-group")
val producerSettings = ProducerSettings(system, new StringSerializer, new StringSerializer)
.withBootstrapServers(bootstrapServers)
val topic = "test-topic"
// Consumer
val consumerSource = Consumer.plainSource(consumerSettings, Subscriptions.topics(topic))
.map(_.value())
// Producer
val producerSink = Producer.plainSink(producerSettings)
// Connect the consumer and producer
val pipeline = consumerSource
.map(record => new ProducerRecord[String, String](topic, record))
.runWith(producerSink)
// Run the pipeline
pipeline.onComplete {
case Success(_) =>
println("Pipeline completed successfully.")
system.terminate()
case Failure(ex) =>
println(s"Pipeline failed with error: ${ex.getMessage}")
system.terminate()
}
}
在这个示例中,我们首先设置了Kafka的消费者设置和生产者设置。然后,我们创建了一个消费者Source,将其订阅到指定的主题上。接下来,我们将消费者Source映射为生产者记录,并将其与生产者Sink连接起来。最后,我们运行整个流水线。
请注意,这只是一个简单的示例,你可以根据自己的需求进行修改和扩展。希望这可以帮助你开始使用Akka Stream和Alpakka Kafka来实现Kafka连接语义。