spark KafkaDataWriter 源码
spark KafkaDataWriter 代码
文件路径：/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaDataWriter.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 org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.Attribute
import org.apache.spark.sql.connector.write.{DataWriter, WriterCommitMessage}
import org.apache.spark.sql.kafka010.producer.{CachedKafkaProducer, InternalKafkaProducerPool}
/**
* Dummy commit message. The DataSourceV2 framework requires a commit message implementation but we
* don't need to really send one.
*/
private case object KafkaDataWriterCommitMessage extends WriterCommitMessage
/**
* A [[DataWriter]] for Kafka writing. One data writer will be created in each partition to
* process incoming rows.
*
* @param targetTopic The topic that this data writer is targeting. If None, topic will be inferred
* from a `topic` field in the incoming data.
* @param producerParams Parameters to use for the Kafka producer.
* @param inputSchema The attributes in the input data.
*/
private[kafka010] class KafkaDataWriter(
targetTopic: Option[String],
producerParams: ju.Map[String, Object],
inputSchema: Seq[Attribute])
extends KafkaRowWriter(inputSchema, targetTopic) with DataWriter[InternalRow] {
private var producer: Option[CachedKafkaProducer] = None
def write(row: InternalRow): Unit = {
checkForErrors()
if (producer.isEmpty) {
producer = Some(InternalKafkaProducerPool.acquire(producerParams))
}
producer.foreach { p => sendRow(row, p.producer) }
}
def commit(): WriterCommitMessage = {
// Send is asynchronous, but we can't commit until all rows are actually in Kafka.
// This requires flushing and then checking that no callbacks produced errors.
// We also check for errors before to fail as soon as possible - the check is cheap.
checkForErrors()
producer.foreach(_.producer.flush())
checkForErrors()
KafkaDataWriterCommitMessage
}
def abort(): Unit = {}
def close(): Unit = {
producer.foreach(InternalKafkaProducerPool.release)
producer = None
}
}
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