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/*
 * Copyright 2018-2024 OVO Energy Limited
 *
 * SPDX-License-Identifier: Apache-2.0
 */

package fs2.kafka

import scala.annotation.nowarn
import scala.concurrent.Promise

import cats.effect.{Async, Outcome, Resource}
import cats.effect.syntax.all.*
import cats.syntax.all.*
import fs2.{Chunk, Stream}
import fs2.kafka.internal.*
import fs2.kafka.internal.converters.collection.*
import fs2.kafka.producer.MkProducer

import org.apache.kafka.clients.consumer.ConsumerGroupMetadata
import org.apache.kafka.clients.producer.RecordMetadata
import org.apache.kafka.common.{Metric, MetricName}

/**
  * Represents a producer of Kafka records specialized for 'read-process-write' streams, with the
  * ability to atomically produce `ProducerRecord`s and commit corresponding [[CommittableOffset]]s
  * using [[produce]].

* * Records are wrapped in [[TransactionalProducerRecords]], which is a chunk of * [[CommittableProducerRecord]] which wrap zero or more records together with a * [[CommittableOffset]]. */ abstract class TransactionalKafkaProducer[F[_], K, V] { /** * Produces the `ProducerRecord`s in the specified [[TransactionalProducerRecords]] in four * steps: first a transaction is initialized, then the records are placed in the buffer of the * producer, then the offsets of the records are sent to the transaction, and lastly the * transaction is committed. If errors or cancellation occurs, the transaction is aborted. The * returned effect succeeds if the whole transaction completes successfully. */ def produce( records: TransactionalProducerRecords[F, K, V] ): F[ProducerResult[K, V]] } object TransactionalKafkaProducer { /** * [[TransactionalKafkaProducer.Metrics]] extends [[TransactionalKafkaProducer]] to provide * access to the underlying producer metrics. */ abstract class Metrics[F[_], K, V] extends TransactionalKafkaProducer[F, K, V] { /** * Returns producer metrics. * * @see * org.apache.kafka.clients.producer.KafkaProducer#metrics */ def metrics: F[Map[MetricName, Metric]] } /** * [[TransactionalKafkaProducer.WithoutOffsets]] extends [[TransactionalKafkaProducer.Metrics]] * to allow producing of records without corresponding upstream offsets. */ abstract class WithoutOffsets[F[_], K, V] extends Metrics[F, K, V] { /** * Produces the `ProducerRecord`s in the specified [[ProducerRecords]] in three steps: first a * transaction is initialized, then the records are placed in the buffer of the producer, and * lastly the transaction is committed. If errors or cancellation occurs, the transaction is * aborted. The returned effect succeeds if the whole transaction completes successfully. */ def produceWithoutOffsets(records: ProducerRecords[K, V]): F[ProducerResult[K, V]] } /** * Creates a new [[TransactionalKafkaProducer]] in the `Resource` context, using the specified * [[TransactionalProducerSettings]]. Note that there is another version where `F[_]` is * specified explicitly and the key and value type can be inferred, which allows you to use the * following syntax. * * {{{ * TransactionalKafkaProducer.resource[F].using(settings) * }}} */ def resource[F[_], K, V]( settings: TransactionalProducerSettings[F, K, V] )(implicit F: Async[F], mk: MkProducer[F] ): Resource[F, TransactionalKafkaProducer.WithoutOffsets[F, K, V]] = ( settings.producerSettings.keySerializer, settings.producerSettings.valueSerializer, WithTransactionalProducer(mk, settings) ).mapN { (keySerializer, valueSerializer, withProducer) => new TransactionalKafkaProducer.WithoutOffsets[F, K, V] { override def produce( records: TransactionalProducerRecords[F, K, V] ): F[ProducerResult[K, V]] = produceTransactionWithOffsets(records) private[this] def produceTransactionWithOffsets( records: Chunk[CommittableProducerRecords[F, K, V]] ): F[Chunk[(ProducerRecord[K, V], RecordMetadata)]] = if (records.isEmpty) F.pure(Chunk.empty) else { val batch = CommittableOffsetBatch.fromFoldableMap(records)(_.offset) val consumerGroupId = if (batch.consumerGroupIdsMissing || batch.consumerGroupIds.size != 1) F.raiseError(ConsumerGroupException(batch.consumerGroupIds)) else F.pure(batch.consumerGroupIds.head) consumerGroupId.flatMap { groupId => val sendOffsets: (KafkaByteProducer, Blocking[F]) => F[Unit] = (producer, blocking) => blocking { producer.sendOffsetsToTransaction( batch.offsets.asJava, new ConsumerGroupMetadata(groupId) ) } produceTransaction(records.flatMap(_.records), Some(sendOffsets)) } } override def produceWithoutOffsets( records: ProducerRecords[K, V] ): F[ProducerResult[K, V]] = produceTransaction(records, None) private[this] def produceTransaction( records: Chunk[ProducerRecord[K, V]], sendOffsets: Option[(KafkaByteProducer, Blocking[F]) => F[Unit]] ): F[Chunk[(ProducerRecord[K, V], RecordMetadata)]] = withProducer.exclusiveAccess { (producer, blocking) => blocking(producer.beginTransaction()).bracketCase { _ => def produceRecords(produceRecordError: Option[Promise[Throwable]]) = records .traverse( KafkaProducer.produceRecord( keySerializer, valueSerializer, producer, blocking, produceRecordError ) ) .flatMap(_.sequence) val produce = if (settings.producerSettings.failFastProduce) Async[F] .delay(Promise[Throwable]()) .flatMap { produceRecordError => Async[F] .race( Async[F].fromFutureCancelable( Async[F].delay((produceRecordError.future, Async[F].unit)) ), produceRecords(produceRecordError.some) ) .rethrow } else produceRecords(None) sendOffsets.fold(produce)(f => produce.flatTap(_ => f(producer, blocking))) } { case (_, Outcome.Succeeded(_)) => blocking(producer.commitTransaction()) case (_, Outcome.Canceled() | Outcome.Errored(_)) => blocking(producer.abortTransaction()) } } override def metrics: F[Map[MetricName, Metric]] = withProducer.blocking(_.metrics().asScala.toMap) override def toString: String = "TransactionalKafkaProducer$" + System.identityHashCode(this) } } /** * Creates a new [[TransactionalKafkaProducer]] in the `Stream` context, using the specified * [[TransactionalProducerSettings]]. Note that there is another version where `F[_]` is * specified explicitly and the key and value type can be inferred, which allows you to use the * following syntax. * * {{{ * TransactionalKafkaProducer.stream[F].using(settings) * }}} */ def stream[F[_], K, V]( settings: TransactionalProducerSettings[F, K, V] )(implicit F: Async[F], mk: MkProducer[F] ): Stream[F, TransactionalKafkaProducer.WithoutOffsets[F, K, V]] = Stream.resource(resource(settings)(F, mk)) def apply[F[_]]: TransactionalProducerPartiallyApplied[F] = new TransactionalProducerPartiallyApplied final private[kafka] class TransactionalProducerPartiallyApplied[F[_]](val dummy: Boolean = true) extends AnyVal { /** * Alternative version of `resource` where the `F[_]` is specified explicitly, and where the * key and value type can be inferred from the [[TransactionalProducerSettings]]. This allows * you to use the following syntax. * * {{{ * KafkaProducer[F].resource(settings) * }}} */ def resource[K, V](settings: TransactionalProducerSettings[F, K, V])(implicit F: Async[F], mk: MkProducer[F] ): Resource[F, TransactionalKafkaProducer.WithoutOffsets[F, K, V]] = TransactionalKafkaProducer.resource(settings)(F, mk) /** * Alternative version of `stream` where the `F[_]` is specified explicitly, and where the key * and value type can be inferred from the [[TransactionalProducerSettings]]. This allows you * to use the following syntax. * * {{{ * KafkaProducer[F].stream(settings) * }}} */ def stream[K, V](settings: TransactionalProducerSettings[F, K, V])(implicit F: Async[F], mk: MkProducer[F] ): Stream[F, TransactionalKafkaProducer.WithoutOffsets[F, K, V]] = TransactionalKafkaProducer.stream(settings)(F, mk) override def toString: String = "TransactionalProducerPartiallyApplied$" + System.identityHashCode(this) } /* * Prevents the default `MkProducer` instance from being implicitly available * to code defined in this object, ensuring factory methods require an instance * to be provided at the call site. */ @nowarn("msg=never used") implicit private def mkAmbig1[F[_]]: MkProducer[F] = throw new AssertionError("should not be used") @nowarn("msg=never used") implicit private def mkAmbig2[F[_]]: MkProducer[F] = throw new AssertionError("should not be used") }




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