使用外部源（例如MS SQL Server）连接到Spark Streaming，并将表数据发布到Kafka。
获取
java.io.NotSerializableException：org.apache.kafka.clients.producer.KafkaProducer 错误。
请在下面查看详细信息。
**CustomReceiver.sacla**
package com.sparkdemo.app
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.receiver.Receiver
import java.util.List
import java.util.Map
import com.sparkdemo.entity.Inventory
import org.apache.kafka.clients.consumer.{ConsumerRecords, KafkaConsumer}
import java.net.ConnectException
import scala.util.{Try, Success, Failure}
import collection.JavaConversions._
class CustomReceiver(topic: String, kafkaParams: Map[String, Object]) extends Receiver[Inventory](StorageLevel.MEMORY_AND_DISK_2) {
override def onStart(): Unit = {
val dataService = new DataService()
var records: Inventory = dataService.selectAll()
new Thread("Socket Receiver") {
override def run() {
Try {
val consumer = new KafkaConsumer(kafkaParams)
consumer.subscribe(topic)
while (!isStopped && records!=null) {
// store(tokenData)
// tokenData = new DataService().selectAll();
val records = new DataService().selectAll();
store(records)
}
} match {
case e: ConnectException =>
restart("Error connecting to...", e)
case t: Throwable =>
restart("Error receiving data", t)
}
}
}.start()
}
override def onStop(): Unit = {
println("Nothing")
}
}
**DataService.scala**
package com.sparkdemo.app;
import java.sql.Connection
import java.sql.DriverManager
import java.sql.ResultSet
import java.sql.Statement
import java.util._
import scala.collection.JavaConversions._
import com.sparkdemo.entity.Inventory
class DataService {
var connect: Connection = DriverManager.getConnection(
"jdbc:sqlserver://localhost;databaseName=TestDB;user=SA;password=Sqlserver@007")
var statement: Statement = connect.createStatement()
var resultSet: ResultSet = null
var inv: Inventory = new Inventory()
Class.forName("com.microsoft.sqlserver.jdbc.SQLServerDriver")
def selectAll(): Inventory = {
resultSet = statement.executeQuery("select * from Inventory")
while (resultSet.next()) {
val inv: Inventory = new Inventory()
inv.setId(resultSet.getInt("id"))
inv.setName(resultSet.getString("name"))
inv.setQuantity(resultSet.getInt("quantity"))
}
inv
}
}
Scala main class **Stream.scala**
package com.sparkdemo.app
import org.apache.spark.streaming.dstream.DStream
import com.sparkdemo.config.Config
import org.apache.kafka.common.serialization.{ StringDeserializer, StringSerializer }
import org.apache.kafka.clients.producer.{ ProducerRecord, KafkaProducer }
import java.util.Properties
import collection.JavaConversions._
import com.sparkdemo.entity.Inventory
object Stream extends Serializable{
def main(args: Array[String]) {
import org.apache.spark.streaming._
def getKafkaParams: Map[String, Object] = {
Map[String, Object](
"auto.offset.reset" -> "earliest",
"bootstrap.servers" -> "localhost:9092",
"key.deserializer" -> classOf[StringDeserializer],
"value.deserializer" -> classOf[StringDeserializer],
"group.id" -> "group3")
}
val properties = new Properties()
properties.put("bootstrap.servers", "localhost:9092")
properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer")
properties.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer")
val topic1 = "topic1"
val topic2 = "topic2"
val producer :KafkaProducer[String, Object] = new KafkaProducer(properties)
val ssc = Config.configReceiver()
val stream = ssc.receiverStream(new CustomReceiver(topic1, getKafkaParams))
stream.map(Inventory=>producer.send(new ProducerRecord[String,Object](topic2,Inventory)))
stream.print()
ssc.start()
ssc.awaitTermination()
}
}
Entity class: **Inventory.scala**
package com.sparkdemo.entity
import scala.beans.{BeanProperty}
class Inventory extends Serializable{
@BeanProperty
var id: Int = _
@BeanProperty
var name: String = _
@BeanProperty
var quantity: Int = _
}
错误：
Exception in thread "main" org.apache.spark.SparkException: Task not serializable
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2287)
at org.apache.spark.streaming.dstream.DStream$$anonfun$map$1.apply(DStream.scala:547)
at org.apache.spark.streaming.dstream.DStream$$anonfun$map$1.apply(DStream.scala:547)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:701)
at org.apache.spark.streaming.StreamingContext.withScope(StreamingContext.scala:265)
at org.apache.spark.streaming.dstream.DStream.map(DStream.scala:546)
at com.sparkdemo.app.Stream$.main(Stream.scala:36)
at com.sparkdemo.app.Stream.main(Stream.scala)
Caused by: java.io.NotSerializableException: org.apache.kafka.clients.producer.KafkaProducer
Serialization stack:
- object not serializable (class: org.apache.kafka.clients.producer.KafkaProducer, value: org.apache.kafka.clients.producer.KafkaProducer@557286ad)
- field (class: com.sparkdemo.app.Stream$$anonfun$main$1, name: producer$1, type: class org.apache.kafka.clients.producer.KafkaProducer)
- object (class com.sparkdemo.app.Stream$$anonfun$main$1, <function1>)
at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295)
... 12 more
答案 0 :(得分：0)
问题是您用于对象类型值的序列化器的类型。
properties.put（“ value.serializer”，“ org.apache.kafka.common.serialization.StringSerializer”）
请编写一个序列化器以读取对象类型值。您可以参考以下链接 Send Custom Java Objects to Kafka Topic
答案 1 :(得分：0)
您遇到了由于以下代码而将kafkaproducer无意发送给执行者的问题 stream.map（Inventory => producer.send（new ProducerRecordString，Object））
您可以mappartitions并在mappartitions中创建生产者，这样它就不会被交付给执行者。