spark KafkaWriteTask 源码
spark KafkaWriteTask 代码
文件路径:/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaWriteTask.scala
/*
* 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 scala.collection.JavaConverters._
import org.apache.kafka.clients.producer.{Callback, KafkaProducer, ProducerRecord, RecordMetadata}
import org.apache.kafka.common.header.Header
import org.apache.kafka.common.header.internals.RecordHeader
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.{Attribute, Cast, UnsafeProjection}
import org.apache.spark.sql.kafka010.producer.{CachedKafkaProducer, InternalKafkaProducerPool}
import org.apache.spark.sql.types.BinaryType
/**
* Writes 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]) extends KafkaRowWriter(inputSchema, topic) {
// used to synchronize with Kafka callbacks
private var producer: Option[CachedKafkaProducer] = None
/**
* Writes key value data out to topics.
*/
def execute(iterator: Iterator[InternalRow]): Unit = {
producer = Some(InternalKafkaProducerPool.acquire(producerConfiguration))
val internalProducer = producer.get.producer
while (iterator.hasNext && failedWrite == null) {
val currentRow = iterator.next()
sendRow(currentRow, internalProducer)
}
}
def close(): Unit = {
try {
checkForErrors()
producer.foreach { p =>
p.producer.flush()
checkForErrors()
}
} finally {
producer.foreach(InternalKafkaProducerPool.release)
producer = None
}
}
}
private[kafka010] abstract class KafkaRowWriter(
inputSchema: Seq[Attribute], topic: Option[String]) {
// used to synchronize with Kafka callbacks
@volatile protected var failedWrite: Exception = _
protected val projection = createProjection
private val callback = new Callback() {
override def onCompletion(recordMetadata: RecordMetadata, e: Exception): Unit = {
if (failedWrite == null && e != null) {
failedWrite = e
}
}
}
/**
* Send the specified row to the producer, with a callback that will save any exception
* to failedWrite. Note that send is asynchronous; subclasses must flush() their producer before
* assuming the row is in Kafka.
*/
protected def sendRow(
row: InternalRow, producer: KafkaProducer[Array[Byte], Array[Byte]]): Unit = {
val projectedRow = projection(row)
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 partition: Integer =
if (projectedRow.isNullAt(4)) null else projectedRow.getInt(4)
val record = if (projectedRow.isNullAt(3)) {
new ProducerRecord[Array[Byte], Array[Byte]](topic.toString, partition, key, value)
} else {
val headerArray = projectedRow.getArray(3)
val headers = (0 until headerArray.numElements()).map { i =>
val struct = headerArray.getStruct(i, 2)
new RecordHeader(struct.getUTF8String(0).toString, struct.getBinary(1))
.asInstanceOf[Header]
}
new ProducerRecord[Array[Byte], Array[Byte]](
topic.toString, partition, key, value, headers.asJava)
}
producer.send(record, callback)
}
protected def checkForErrors(): Unit = {
if (failedWrite != null) {
throw failedWrite
}
}
private def createProjection = {
UnsafeProjection.create(
Seq(
KafkaWriter.topicExpression(inputSchema, topic),
Cast(KafkaWriter.keyExpression(inputSchema), BinaryType),
Cast(KafkaWriter.valueExpression(inputSchema), BinaryType),
KafkaWriter.headersExpression(inputSchema),
KafkaWriter.partitionExpression(inputSchema)
),
inputSchema
)
}
}
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