akka.kafka.scaladsl.Consumer Scala Examples

package com.softwaremill.kmq.redelivery

import java.time.Duration
import java.util.Random

import akka.actor.ActorSystem
import akka.kafka.scaladsl.{Consumer, Producer}
import akka.kafka.{ConsumerSettings, ProducerMessage, ProducerSettings, Subscriptions}
import akka.stream.ActorMaterializer
import akka.testkit.TestKit
import com.softwaremill.kmq._
import com.softwaremill.kmq.redelivery.infrastructure.KafkaSpec
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.clients.producer.{ProducerConfig, ProducerRecord}
import org.apache.kafka.common.serialization.StringDeserializer
import org.scalatest.concurrent.Eventually
import org.scalatest.time.{Seconds, Span}
import org.scalatest.{BeforeAndAfterAll, FlatSpecLike, Matchers}

import scala.collection.mutable.ArrayBuffer

class IntegrationTest extends TestKit(ActorSystem("test-system")) with FlatSpecLike with KafkaSpec with BeforeAndAfterAll with Eventually with Matchers {

  implicit val materializer = ActorMaterializer()
  import system.dispatcher

  "KMQ" should "resend message if not committed" in {
    val bootstrapServer = s"localhost:${testKafkaConfig.kafkaPort}"
    val kmqConfig = new KmqConfig("queue", "markers", "kmq_client", "kmq_redelivery", Duration.ofSeconds(1).toMillis,
    1000)

    val consumerSettings = ConsumerSettings(system, new StringDeserializer, new StringDeserializer)
      .withBootstrapServers(bootstrapServer)
      .withGroupId(kmqConfig.getMsgConsumerGroupId)
      .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

    val markerProducerSettings = ProducerSettings(system,
      new MarkerKey.MarkerKeySerializer(), new MarkerValue.MarkerValueSerializer())
      .withBootstrapServers(bootstrapServer)
      .withProperty(ProducerConfig.PARTITIONER_CLASS_CONFIG, classOf[ParititionFromMarkerKey].getName)
    val markerProducer = markerProducerSettings.createKafkaProducer()

    val random = new Random()

    lazy val processedMessages = ArrayBuffer[String]()
    lazy val receivedMessages = ArrayBuffer[String]()

    val control = Consumer.committableSource(consumerSettings, Subscriptions.topics(kmqConfig.getMsgTopic)) // 1. get messages from topic
      .map { msg =>
      ProducerMessage.Message(
        new ProducerRecord[MarkerKey, MarkerValue](kmqConfig.getMarkerTopic, MarkerKey.fromRecord(msg.record), new StartMarker(kmqConfig.getMsgTimeoutMs)), msg)
    }
      .via(Producer.flow(markerProducerSettings, markerProducer)) // 2. write the "start" marker
      .map(_.message.passThrough)
      .mapAsync(1) { msg =>
        msg.committableOffset.commitScaladsl().map(_ => msg.record) // this should be batched
      }
      .map { msg =>
        receivedMessages += msg.value
        msg
      }
      .filter(_ => random.nextInt(5) != 0)
      .map { processedMessage =>
        processedMessages += processedMessage.value
        new ProducerRecord[MarkerKey, MarkerValue](kmqConfig.getMarkerTopic, MarkerKey.fromRecord(processedMessage), EndMarker.INSTANCE)
      }
      .to(Producer.plainSink(markerProducerSettings, markerProducer)) // 5. write "end" markers
      .run()

    val redeliveryHook = RedeliveryTracker.start(new KafkaClients(bootstrapServer), kmqConfig)

    val messages = (0 to 20).map(_.toString)
    messages.foreach(msg => sendToKafka(kmqConfig.getMsgTopic,msg))

    eventually {
      receivedMessages.size should be > processedMessages.size
      processedMessages.sortBy(_.toInt).distinct shouldBe messages
    }(PatienceConfig(timeout = Span(15, Seconds)), implicitly)

    redeliveryHook.close()
    control.shutdown()
  }

  override def afterAll(): Unit = {
    super.afterAll()
    TestKit.shutdownActorSystem(system)
  }
} 

package alpakka.kafka

import akka.Done
import akka.actor.{ActorSystem, Props}
import akka.kafka.scaladsl.Consumer.DrainingControl
import akka.kafka.scaladsl.{Committer, Consumer}
import akka.kafka.{CommitterSettings, ConsumerSettings, Subscriptions}
import akka.stream.scaladsl.Sink
import akka.util.Timeout
import alpakka.kafka.TotalFake.{IncrementMessage, IncrementWord}
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.{LongDeserializer, StringDeserializer}

import scala.concurrent.Future
import scala.concurrent.duration._


object WordCountConsumer extends App {
  implicit val system = ActorSystem("WordCountConsumer")
  implicit val ec = system.dispatcher

  val total = system.actorOf(Props[TotalFake], "totalFake")

  val committerSettings = CommitterSettings(system).withMaxBatch(1)

  def createConsumerSettings(group: String): ConsumerSettings[String, java.lang.Long] = {
    ConsumerSettings(system, new StringDeserializer , new LongDeserializer)
      .withBootstrapServers("localhost:9092")
      .withGroupId(group)
      //Define consumer behavior upon starting to read a partition for which it does not have a committed offset or if the committed offset it has is invalid
      .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")
  }

  def createAndRunConsumerWordCount(id: String) = {
    Consumer.committableSource(createConsumerSettings("wordcount consumer group"), Subscriptions.topics("wordcount-output"))
      .mapAsync(1) { msg =>
        //println(s"$id - Offset: ${msg.record.offset()} - Partition: ${msg.record.partition()} Consume msg with key: ${msg.record.key()} and value: ${msg.record.value()}")
        if (msg.record.key().equalsIgnoreCase("fakeNews")) { //hardcoded because WordCountProducer.fakeNewsKeyword does not work
          import akka.pattern.ask
          implicit val askTimeout: Timeout = Timeout(3.seconds)
          (total ? IncrementWord(msg.record.value.toInt, id))
            .mapTo[Done]
            .map(_ => msg.committableOffset)
        } else {
          Future(msg).map(_ => msg.committableOffset)
        }
      }
      .via(Committer.flow(committerSettings))
      .toMat(Sink.seq)(DrainingControl.apply)
      .run()
  }

  def createAndRunConsumerMessageCount(id: String) = {
    Consumer.committableSource(createConsumerSettings("messagecount consumer group"), Subscriptions.topics("messagecount-output"))
      .mapAsync(1) { msg =>
        //println(s"$id - Offset: ${msg.record.offset()} - Partition: ${msg.record.partition()} Consume msg with key: ${msg.record.key()} and value: ${msg.record.value()}")
        import akka.pattern.ask
        implicit val askTimeout: Timeout = Timeout(3.seconds)
        (total ? IncrementMessage(msg.record.value.toInt, id))
          .mapTo[Done]
          .map(_ => msg.committableOffset)
      }
      .via(Committer.flow(committerSettings))
      .toMat(Sink.seq)(DrainingControl.apply)
      .run()
  }

  val drainingControlW1 = createAndRunConsumerWordCount("W.1")
  val drainingControlW2 = createAndRunConsumerWordCount("W.2")
  val drainingControlM = createAndRunConsumerMessageCount("M")


  sys.addShutdownHook{
    println("Got control-c cmd from shell, about to shutdown...")
    drainingControlW1.drainAndShutdown()
    drainingControlW2.drainAndShutdown()
    drainingControlM.drainAndShutdown()
  }
} 

package hydra.kafka.endpoints

import akka.actor.ActorSelection
import akka.http.scaladsl.common.EntityStreamingSupport
import akka.kafka.Subscriptions
import akka.kafka.scaladsl.Consumer
import akka.pattern.ask
import akka.util.Timeout
import hydra.core.http.RouteSupport
import hydra.kafka.consumer.KafkaConsumerProxy.{GetLatestOffsets, LatestOffsetsResponse}
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.kafka.common.TopicPartition

import scala.collection.immutable.Map
import scala.concurrent.duration._
import scala.concurrent.{Await, ExecutionContext, Future}


class TopicsEndpoint(consumerProxy:ActorSelection)(implicit ec:ExecutionContext) extends RouteSupport {

  import hydra.kafka.util.KafkaUtils._

  implicit val jsonStreamingSupport = EntityStreamingSupport.json()

  override val route =
    path("transports" / "kafka" / "consumer" / "topics" / Segment) {
      topicName =>
        get {
          extractRequestContext { ctx =>
            parameters('format.?, 'group.?, 'n ? 10, 'start ? "earliest") {
              (format, groupId, n, startOffset) =>
                val settings = loadConsumerSettings[Any, Any](
                  format.getOrElse("avro"),
                  groupId.getOrElse("hydra"),
                  startOffset
                )
                val offsets = latestOffsets(topicName)
                val source = Consumer
                  .plainSource(settings, Subscriptions.topics(topicName))
                  .initialTimeout(5.seconds)
                  .zipWithIndex
                  .takeWhile(rec =>
                    rec._2 <= n && !shouldCancel(offsets, rec._1)
                  )
                  .map(rec => rec._1.value().toString)
                  .watchTermination()((_, termination) =>
                    termination.failed.foreach {
                      case cause => ctx.fail(cause)
                    }
                  )
                complete(source)

            }
          }
        }
    }

  def shouldCancel(
      fpartitions: Future[Map[TopicPartition, Long]],
      record: ConsumerRecord[Any, Any]
  ): Boolean = {
    if (fpartitions.isCompleted) {
      val partitions = Await.result(fpartitions, 1.millis)
      val tp = new TopicPartition(record.topic(), record.partition())
      partitions.get(tp) match {
        case Some(offset) => record.offset() >= offset
        case None         => false
      }
    } else {
      false
    }

  }

  private def latestOffsets(
      topic: String
  ): Future[Map[TopicPartition, Long]] = {
    implicit val timeout = Timeout(5 seconds)
    (consumerProxy ? GetLatestOffsets(topic))
      .mapTo[LatestOffsetsResponse]
      .map(_.offsets)
  }

} 

package controllers

import javax.inject.{Inject, Singleton}

import akka.actor.{Actor, ActorRef, ActorSystem, Props}
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.scaladsl.Sink
import akka.stream.{Materializer, ThrottleMode}
import com.typesafe.config.ConfigFactory
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.{ByteArrayDeserializer, StringDeserializer}
import play.api.libs.streams.ActorFlow
import play.api.mvc.{Controller, WebSocket}

import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.Future
import scala.concurrent.duration._


//@Singleton
class KafkaWebSocket @Inject() (implicit system: ActorSystem, materializer: Materializer) extends Controller {

  def kafkaWS = WebSocket.accept[String, String] { request =>
    ActorFlow.actorRef(out => KafkaWSActor.props(out))
  }

  object KafkaWSActor {
    def props(outRef: ActorRef) = Props(new KafkaWSActor(outRef))
  }

  class KafkaWSActor(outRef: ActorRef) extends Actor {

    val config = ConfigFactory.load()
    val combinedConfig = ConfigFactory.defaultOverrides()
      .withFallback(config)
      .withFallback(ConfigFactory.defaultApplication())
      .getConfig("trucking-web-application.backend")

    val consumerSettings = ConsumerSettings(system, new ByteArrayDeserializer, new StringDeserializer)
      //.withBootstrapServers("sandbox-hdf.hortonworks.com:6667")
      .withBootstrapServers(combinedConfig.getString("kafka.bootstrap-servers"))
      .withGroupId("group1")
      .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

    Consumer.committableSource(consumerSettings, Subscriptions.topics("trucking_data_joined"))
      .mapAsync(1) { msg => Future(outRef ! msg.record.value).map(_ => msg) }
      //.mapAsync(1) { msg => msg.committableOffset.commitScaladsl() } // TODO: Disabling commits for debug
      .throttle(1, 250.milliseconds, 1, ThrottleMode.Shaping)
      .runWith(Sink.ignore)

    def receive = {
      case msg: String => outRef ! s"Ack: $msg"
    }
  }

} 

package com.omearac.consumers

import akka.actor.{ActorRef, ActorSystem}
import akka.kafka.ConsumerMessage.CommittableOffsetBatch
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerMessage, ConsumerSettings, Subscriptions}
import akka.stream.scaladsl.{Flow, Sink}
import com.omearac.shared.EventMessages.FailedMessageConversion
import com.omearac.shared.JsonMessageConversion.Conversion
import com.omearac.shared.{AkkaStreams, EventSourcing}
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.{ByteArrayDeserializer, StringDeserializer}

import scala.collection.mutable.ArrayBuffer
import scala.concurrent.Future



trait ConsumerStream extends AkkaStreams with EventSourcing {
    implicit val system: ActorSystem
    def self: ActorRef


    def createStreamSink(consumerActorSink : ActorRef) = {
        Sink.actorRefWithAck(consumerActorSink, "STREAM_INIT", "OK", "STREAM_DONE")
    }

    def createStreamSource(consumerProperties: Map[String,String])  = {
        val kafkaMBAddress = consumerProperties("bootstrap-servers")
        val groupID = consumerProperties("groupId")
        val topicSubscription = consumerProperties("subscription-topic")
        val consumerSettings = ConsumerSettings(system, new ByteArrayDeserializer, new StringDeserializer)
            .withBootstrapServers(kafkaMBAddress)
            .withGroupId(groupID)
            .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

        Consumer.committableSource(consumerSettings, Subscriptions.topics(topicSubscription))
    }

    def createStreamFlow[msgType: Conversion] = {
        Flow[ConsumerMessage.CommittableMessage[Array[Byte], String]]
            .map(msg => (msg.committableOffset, Conversion[msgType].convertFromJson(msg.record.value)))
            //Publish the conversion error event messages returned from the JSONConversion
            .map (tuple => publishConversionErrors[msgType](tuple))
            .filter(result => result.isRight)
            .map(test => test.right.get)
            //Group the commit offsets and correctly converted messages for more efficient Kafka commits
            .batch(max = 20, tuple => (CommittableOffsetBatch.empty.updated(tuple._1), ArrayBuffer[msgType](tuple._2)))
            {(tupleOfCommitOffsetAndMsgs, tuple) =>
            (tupleOfCommitOffsetAndMsgs._1.updated(tuple._1), tupleOfCommitOffsetAndMsgs._2 :+ tuple._2)
            }
            //Take the first element of the tuple (set of commit numbers) to add to kafka commit log and then return the collection of grouped case class messages
            .mapAsync(4)(tupleOfCommitOffsetAndMsgs => commitOffsetsToKafka[msgType](tupleOfCommitOffsetAndMsgs))
            .map(msgGroup => msgGroup._2)
    }

    def commitOffsetsToKafka[msgType](tupleOfCommitOffsetAndMsgs: (ConsumerMessage.CommittableOffsetBatch, ArrayBuffer[msgType])) = Future {
        (tupleOfCommitOffsetAndMsgs._1.commitScaladsl(), tupleOfCommitOffsetAndMsgs._2)
    }

    def publishConversionErrors[msgType](tupleOfCommitOffsetAndConversionResults: (ConsumerMessage.CommittableOffset, Either[FailedMessageConversion,msgType]))
    : Either[Unit,(ConsumerMessage.CommittableOffset,msgType)] = {

        if (tupleOfCommitOffsetAndConversionResults._2.isLeft) {

            //Publish a local event that there was a failure in conversion
            publishLocalEvent(tupleOfCommitOffsetAndConversionResults._2.left.get)

            //Commit the Kafka Offset to acknowledge that the message was consumed
            Left(tupleOfCommitOffsetAndConversionResults._1.commitScaladsl())
        }
        else
            Right(tupleOfCommitOffsetAndConversionResults._1,tupleOfCommitOffsetAndConversionResults._2.right.get)
    }
} 

package com.packt.chapter8

import akka.actor.ActorSystem
import akka.kafka.scaladsl.{Consumer, Producer}
import akka.kafka.{ConsumerSettings, ProducerSettings, Subscriptions}
import akka.stream.{ActorMaterializer, ClosedShape}
import akka.stream.scaladsl.{Flow, GraphDSL, RunnableGraph, Sink, Source}
import org.apache.kafka.clients.consumer.{ConsumerConfig, ConsumerRecord}
import org.apache.kafka.clients.producer.ProducerRecord
import org.apache.kafka.common.TopicPartition
import org.apache.kafka.common.serialization.{ByteArrayDeserializer, ByteArraySerializer, StringDeserializer, StringSerializer}

import scala.concurrent.duration._

object ProcessingKafkaApplication extends App {
  implicit val actorSystem = ActorSystem("SimpleStream")
  implicit val actorMaterializer = ActorMaterializer()

  val bootstrapServers = "localhost:9092"
  val kafkaTopic = "akka_streams_topic"
  val partition = 0
  val subscription = Subscriptions.assignment(new TopicPartition(kafkaTopic, partition))

  val consumerSettings = ConsumerSettings(actorSystem, new ByteArrayDeserializer, new StringDeserializer)
    .withBootstrapServers(bootstrapServers)
    .withGroupId("akka_streams_group")
    .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

  val producerSettings = ProducerSettings(actorSystem, new ByteArraySerializer, new StringSerializer)
    .withBootstrapServers(bootstrapServers)

  val runnableGraph = RunnableGraph.fromGraph(GraphDSL.create() { implicit builder =>
    import GraphDSL.Implicits._

    val tickSource = Source.tick(0 seconds, 5 seconds, "Hello from Akka Streams using Kafka!")
    val kafkaSource = Consumer.plainSource(consumerSettings, subscription)
    val kafkaSink = Producer.plainSink(producerSettings)
    val printlnSink = Sink.foreach(println)

    val mapToProducerRecord = Flow[String].map(elem => new ProducerRecord[Array[Byte], String](kafkaTopic, elem))
    val mapFromConsumerRecord = Flow[ConsumerRecord[Array[Byte], String]].map(record => record.value())

    tickSource  ~> mapToProducerRecord   ~> kafkaSink
    kafkaSource ~> mapFromConsumerRecord ~> printlnSink

    ClosedShape
  })

  runnableGraph.run()
} 

package com.lightbend.kafkalagexporter.integration

import akka.actor.Cancellable
import akka.actor.typed.scaladsl.Behaviors
import akka.actor.typed.{Behavior, PostStop}
import akka.kafka.{CommitterSettings, Subscriptions}
import akka.kafka.scaladsl.{Committer, Consumer}
import akka.kafka.testkit.scaladsl.KafkaSpec
import akka.stream.OverflowStrategy
import akka.stream.scaladsl.Keep
import akka.stream.testkit.scaladsl.TestSink
import org.scalatest.concurrent.ScalaFutures

import scala.concurrent.Await
import scala.concurrent.duration._

trait LagSim extends KafkaSpec with ScalaFutures {
  private implicit val patience: PatienceConfig = PatienceConfig(30.seconds, 1.second)

  class LagSimulator(topic: String, group: String) {
    private var offset: Int = 0
    private val committerSettings = CommitterSettings(system).withMaxBatch(1).withParallelism(1)

    private lazy val (consumerControl, consumerProbe) = Consumer
      .committableSource(consumerDefaults.withGroupId(group), Subscriptions.topics(topic))
      .buffer(size = 1, OverflowStrategy.backpressure)
      .map { elem =>
        log.debug("Committing elem with offset: {}", elem.committableOffset.partitionOffset)
        elem.committableOffset.commitScaladsl()
      }
      .toMat(TestSink.probe)(Keep.both)
      .run()

    def produceElements(num: Int): Unit = {
      Await.result(produce(topic, offset to (offset + num)), remainingOrDefault)
      offset += num + 1
    }

    // TODO: Replace this with regular Kafka Consumer for more fine-grained control over committing
    def consumeElements(num: Int): Unit = {
      consumerProbe
        .request(num)
        .expectNextN(num)
    }

    def shutdown(): Unit = {
      consumerControl.shutdown().futureValue
      consumerProbe.cancel()
    }
  }

  sealed trait Simulator
  case class Tick(produce: Int, consume: Int) extends Simulator

  def lagSimActor(simulator: LagSimulator,
                  scheduledTick: Cancellable = Cancellable.alreadyCancelled): Behavior[Simulator] =
    Behaviors.receive[Simulator] {
      case (context, tick @ Tick(produce, consume)) =>
        simulator.produceElements(produce)
        simulator.consumeElements(consume)
        lagSimActor(simulator, context.scheduleOnce(1 second, context.self, tick))
    } receiveSignal {
      case (_, PostStop) =>
        simulator.shutdown()
        scheduledTick.cancel()
        Behaviors.same
    }

} 

package asura.kafka

import akka.actor.ActorSystem
import akka.kafka.scaladsl.Consumer
import akka.kafka.scaladsl.Consumer.Control
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.scaladsl.Source
import io.confluent.kafka.serializers.{AbstractKafkaAvroSerDeConfig, KafkaAvroDeserializer, KafkaAvroDeserializerConfig}
import org.apache.kafka.clients.consumer.{ConsumerConfig, ConsumerRecord}
import org.apache.kafka.common.serialization.{Deserializer, StringDeserializer}

import scala.collection.JavaConverters._

object ConsumerBuilder {

  def buildAvroSource[V](
                          brokerUrl: String,
                          schemaRegisterUrl: String,
                          group: String,
                          topics: Set[String],
                          resetType: String = "latest",
                        )(implicit system: ActorSystem): Source[ConsumerRecord[String, V], Control] = {

    val kafkaAvroSerDeConfig = Map[String, Any](
      AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG -> schemaRegisterUrl,
      KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG -> true.toString
    )
    val consumerSettings: ConsumerSettings[String, V] = {
      val kafkaAvroDeserializer = new KafkaAvroDeserializer()
      kafkaAvroDeserializer.configure(kafkaAvroSerDeConfig.asJava, false)
      val deserializer = kafkaAvroDeserializer.asInstanceOf[Deserializer[V]]

      ConsumerSettings(system, new StringDeserializer, deserializer)
        .withBootstrapServers(brokerUrl)
        .withGroupId(group)
        .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, resetType)
    }
    Consumer.plainSource(consumerSettings, Subscriptions.topics(topics))
  }
} 

package asura.kafka.consumer

import akka.actor.ActorSystem
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.ActorMaterializer
import akka.stream.scaladsl.Sink
import com.typesafe.scalalogging.StrictLogging
import org.apache.kafka.common.serialization.StringDeserializer

object TestConsumer extends StrictLogging {

  def main(args: Array[String]): Unit = {

    logger.info("Start consumer")

    implicit val system = ActorSystem("consumer")
    implicit val materializer = ActorMaterializer()
    implicit val ec = system.dispatcher

    val consumerSettings = ConsumerSettings(system, new StringDeserializer, new StringDeserializer)
      .withGroupId("test-group1")

    val done = Consumer
      .plainSource(consumerSettings, Subscriptions.topics("test-topic"))
      .runWith(Sink.foreach(record =>
        logger.info(s"topic:${record.topic()}, partition:${record.partition()}, offset:${record.offset()}, key:${record.key()}, value: ${record.value()}"))
      )
    done onComplete {
      case scala.util.Success(_) => logger.info("Done"); system.terminate()
      case scala.util.Failure(err) => logger.error(err.toString); system.terminate()
    }
  }
} 

package asura.kafka.consumer

import akka.actor.ActorSystem
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.ActorMaterializer
import akka.stream.scaladsl.{Keep, Sink}
import asura.kafka.avro.SampleAvroClass
import com.typesafe.scalalogging.StrictLogging
import io.confluent.kafka.serializers.{AbstractKafkaAvroSerDeConfig, KafkaAvroDeserializer, KafkaAvroDeserializerConfig}
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization._

import scala.collection.JavaConverters._

object TestAvroConsumer extends StrictLogging {

  def main(args: Array[String]): Unit = {

    implicit val system = ActorSystem("consumer")
    implicit val materializer = ActorMaterializer()
    implicit val ec = system.dispatcher

    val schemaRegistryUrl = ""
    val bootstrapServers = ""
    val topic = ""
    val group = ""

    val kafkaAvroSerDeConfig = Map[String, Any](
      AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG -> schemaRegistryUrl,
      KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG -> true.toString
    )
    val consumerSettings: ConsumerSettings[String, SampleAvroClass] = {
      val kafkaAvroDeserializer = new KafkaAvroDeserializer()
      kafkaAvroDeserializer.configure(kafkaAvroSerDeConfig.asJava, false)
      val deserializer = kafkaAvroDeserializer.asInstanceOf[Deserializer[SampleAvroClass]]

      ConsumerSettings(system, new StringDeserializer, deserializer)
        .withBootstrapServers(bootstrapServers)
        .withGroupId(group)
        .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")
    }

    val samples = (1 to 3)
    val (control, result) = Consumer
      .plainSource(consumerSettings, Subscriptions.topics(topic))
      .take(samples.size.toLong)
      .map(_.value())
      .toMat(Sink.seq)(Keep.both)
      .run()

    control.shutdown()
    result.map(records => records.foreach(record => logger.info(s"${record}")))
  }
} 

package com.example.integration
import akka.kafka.scaladsl.{Consumer, Producer}
import akka.kafka.{ProducerMessage, Subscriptions}
import org.apache.kafka.clients.producer.ProducerRecord

import com.example._

object CommitConsumerToSinkProducer {

  
  val done = Consumer.committableSource(consumerSettings, Subscriptions.topics(topic1))
    .map { msg =>
      println(s"topic1 -> topic2: $msg")
      ProducerMessage.Message(new ProducerRecord[Array[Byte], String](
        topic2,
        msg.record.value
      ), msg.committableOffset)
    }
    .runWith(Producer.commitableSink(producerSettings))

} 

package com.example.integration

import akka.kafka.scaladsl.{Consumer, Producer}
import akka.kafka.{ProducerMessage, Subscriptions}
import akka.stream.scaladsl.Sink
import com.example._
import org.apache.kafka.clients.producer.ProducerRecord

object CommitConsumerToFlowProducer extends App {

  
  val done = Consumer.committableSource(consumerSettings, Subscriptions.topics(topic1))
    .map { msg =>
      println(s"topic1 -> topic2: $msg")
      ProducerMessage.Message(new ProducerRecord[Array[Byte], String](
        topic2,
        msg.record.value
      ), msg.committableOffset)
    }
    .via(Producer.flow(producerSettings))
    .mapAsync(producerSettings.parallelism) { result =>
      result.message.passThrough.commitScaladsl()
    }
    .runWith(Sink.ignore)
} 

package com.example.consumer

import java.util.concurrent.atomic.AtomicLong

import akka.Done
import akka.kafka.Subscriptions
import akka.kafka.scaladsl.Consumer
import akka.stream.scaladsl.Sink
import com.example._
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.kafka.common.TopicPartition

import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.Future

object PlainSourceConsumer extends App {

  val db = new DB
  db.loadOffset().foreach { fromOffset =>
    val partition = 0
    val subscription = Subscriptions.assignmentWithOffset(
      new TopicPartition(topic, partition) -> fromOffset
    )

    val done =
      Consumer.plainSource(consumerSettings, subscription)
        .mapAsync(1)(db.save)
        .runWith(Sink.ignore)
  }

}

//Zookeeper or DB storage mock
class DB {

  private val offset = new AtomicLong(2)

  def save(record: ConsumerRecord[Array[Byte], String]): Future[Done] = {
    println(s"DB.save: ${record.value}")
    offset.set(record.offset)
    Future.successful(Done)
  }

  def loadOffset(): Future[Long] =
    Future.successful(offset.get)

  def update(data: String): Future[Done] = {
    println(s"DB.update: $data")
    Future.successful(Done)
  }
} 

package com.example.consumer

import akka.Done
import akka.kafka.ConsumerMessage.CommittableOffsetBatch
import akka.kafka.Subscriptions
import akka.kafka.scaladsl.Consumer
import akka.stream.scaladsl.Sink
import com.example._

import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.Future

object BatchCommitConsumer extends App {

  val done = Consumer.committableSource(consumerSettings, Subscriptions.topics(topic))
    .mapAsync(1) { msg =>
      println(s"BatchCommittableConsumer consume: $msg")
      Future.successful(Done).map(_ => msg.committableOffset)
    }
    .batch(max = 20, first => CommittableOffsetBatch.empty.updated(first)) { (batch, elem) =>
      batch.updated(elem)
    }
    .mapAsync(3)(_.commitScaladsl())
    .runWith(Sink.ignore)
} 

package com.lightbend.modelserving.tensorflowserving

import akka.actor.typed.scaladsl.Behaviors
import akka.actor.typed.scaladsl.adapter._
import akka.actor.typed.{ActorRef, ActorSystem}
import akka.http.scaladsl.Http
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.scaladsl.Sink
import akka.stream.typed.scaladsl.{ActorFlow, ActorMaterializer}
import akka.util.Timeout
import com.lightbend.modelserving.configuration.ModelServingConfiguration
import com.lightbend.modelserving.model.ServingResult
import com.lightbend.modelserving.winemodel.DataRecord
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.ByteArrayDeserializer

import scala.concurrent.duration._
import scala.util.Success


object TFServingModelServer {

  import ModelServingConfiguration._

  // Initialization

  implicit val modelServer = ActorSystem(
    Behaviors.setup[TFModelServerActor](
      context => new TFModelServerBehaviour(context)), "ModelServing")

  implicit val materializer = ActorMaterializer()
  implicit val executionContext = modelServer.executionContext
  implicit val askTimeout = Timeout(30.seconds)

  // Configuration properties for the Kafka topic.
  val dataSettings = ConsumerSettings(modelServer.toUntyped, new ByteArrayDeserializer, new ByteArrayDeserializer)
    .withBootstrapServers(KAFKA_BROKER)
    .withGroupId(DATA_GROUP)
    .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

  def main(args: Array[String]): Unit = {

    println(s"Akka application that uses TensorFlow Serving, brokers $KAFKA_BROKER")

    // Data stream processing
    Consumer.atMostOnceSource(dataSettings, Subscriptions.topics(DATA_TOPIC))
      .map(record => DataRecord.wineFromByteArray(record.value)).collect { case Success(a) => a }
      .via(ActorFlow.ask(1)(modelServer)((elem, replyTo : ActorRef[Option[ServingResult[Double]]]) => new ServeData(replyTo, elem)))
      .collect{ case Some(result) => result}
      .runWith(Sink.foreach(result =>
        println(s"Model served in ${System.currentTimeMillis() - result.submissionTs} ms, with result ${result.result} " +
          s"(model ${result.name}, data type ${result.dataType})")))
    // Rest Server
    startRest(modelServer)
  }

  def startRest(modelServerManager: ActorSystem[TFModelServerActor]): Unit = {

    implicit val timeout = Timeout(10.seconds)
    implicit val system = modelServerManager.toUntyped

    val host = "0.0.0.0"
    val port = MODELSERVING_PORT
    val routes = TFQueriesAkkaHttpResource.storeRoutes(modelServerManager)(modelServerManager.scheduler)

    val _ = Http().bindAndHandle(routes, host, port) map
      { binding =>
        println(s"Starting models observer on port ${binding.localAddress}") } recover {
      case ex =>
        println(s"Models observer could not bind to $host:$port - ${ex.getMessage}")
    }
  }
}