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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.sql.kafka010

import java.{util => ju}

import org.apache.kafka.clients.producer.{Callback, KafkaProducer, ProducerRecord, RecordMetadata}

import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.{Attribute, Cast, Literal, UnsafeProjection}
import org.apache.spark.sql.types.{BinaryType, StringType}

/**
 * A simple trait for writing out data in a single Spark task, without any concerns about how
 * to commit or abort tasks. Exceptions thrown by the implementation of this class will
 * automatically trigger task aborts.
 */
private[kafka010] class KafkaWriteTask(
    producerConfiguration: ju.Map[String, Object],
    inputSchema: Seq[Attribute],
    topic: Option[String]) {
  // used to synchronize with Kafka callbacks
  @volatile private var failedWrite: Exception = null
  private val projection = createProjection
  private var producer: KafkaProducer[Array[Byte], Array[Byte]] = _

  /**
   * Writes key value data out to topics.
   */
  def execute(iterator: Iterator[InternalRow]): Unit = {
    producer = CachedKafkaProducer.getOrCreate(producerConfiguration)
    while (iterator.hasNext && failedWrite == null) {
      val currentRow = iterator.next()
      val projectedRow = projection(currentRow)
      val topic = projectedRow.getUTF8String(0)
      val key = projectedRow.getBinary(1)
      val value = projectedRow.getBinary(2)
      if (topic == null) {
        throw new NullPointerException(s"null topic present in the data. Use the " +
        s"${KafkaSourceProvider.TOPIC_OPTION_KEY} option for setting a default topic.")
      }
      val record = new ProducerRecord[Array[Byte], Array[Byte]](topic.toString, key, value)
      val callback = new Callback() {
        override def onCompletion(recordMetadata: RecordMetadata, e: Exception): Unit = {
          if (failedWrite == null && e != null) {
            failedWrite = e
          }
        }
      }
      producer.send(record, callback)
    }
  }

  def close(): Unit = {
    checkForErrors()
    if (producer != null) {
      producer.flush()
      checkForErrors()
      producer = null
    }
  }

  private def createProjection: UnsafeProjection = {
    val topicExpression = topic.map(Literal(_)).orElse {
      inputSchema.find(_.name == KafkaWriter.TOPIC_ATTRIBUTE_NAME)
    }.getOrElse {
      throw new IllegalStateException(s"topic option required when no " +
        s"'${KafkaWriter.TOPIC_ATTRIBUTE_NAME}' attribute is present")
    }
    topicExpression.dataType match {
      case StringType => // good
      case t =>
        throw new IllegalStateException(s"${KafkaWriter.TOPIC_ATTRIBUTE_NAME} " +
          s"attribute unsupported type $t. ${KafkaWriter.TOPIC_ATTRIBUTE_NAME} " +
          "must be a StringType")
    }
    val keyExpression = inputSchema.find(_.name == KafkaWriter.KEY_ATTRIBUTE_NAME)
      .getOrElse(Literal(null, BinaryType))
    keyExpression.dataType match {
      case StringType | BinaryType => // good
      case t =>
        throw new IllegalStateException(s"${KafkaWriter.KEY_ATTRIBUTE_NAME} " +
          s"attribute unsupported type $t")
    }
    val valueExpression = inputSchema
      .find(_.name == KafkaWriter.VALUE_ATTRIBUTE_NAME).getOrElse(
      throw new IllegalStateException("Required attribute " +
        s"'${KafkaWriter.VALUE_ATTRIBUTE_NAME}' not found")
    )
    valueExpression.dataType match {
      case StringType | BinaryType => // good
      case t =>
        throw new IllegalStateException(s"${KafkaWriter.VALUE_ATTRIBUTE_NAME} " +
          s"attribute unsupported type $t")
    }
    UnsafeProjection.create(
      Seq(topicExpression, Cast(keyExpression, BinaryType),
        Cast(valueExpression, BinaryType)), inputSchema)
  }

  private def checkForErrors(): Unit = {
    if (failedWrite != null) {
      throw failedWrite
    }
  }
}





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