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java.lang.ClassNotFoundException: java.time.temporal.TemporalField when running Spark code

由 痴心易碎 提交于 2019-12-12 01:20:36

问题


This question is related to the previous thread. I am extracting sessions from the stream of users' click events. For validation purposes, I am always waiting on a timeout of 2 minutes, and if the user was inactive during these 2 minutes (no click events), then I assume that the session was finished. These finished sessions should be saved in finishedSessions.

The below-given code provides the error (see below).

   settings = ssc.sparkContext.broadcast(Map(
                                              "metadataBrokerList_OutputQueue" -> metadataBrokerList_OutputQueue,
                                              "topicOutput" -> topicOutput))

   val spec = StateSpec.function(Utils.updateState _).timeout(Minutes(2))
   val latestSessionInfo = membersSessions.map[(String, (Long, Long, Long, List[String]))](a => {
      //transform to (member_id, (time, time, counter, events within session))
          (a._1, (a._2._1, a._2._2, 1, a._2._3))
   })

   val finishedSessions = latestSessionInfo.mapWithState(spec).filter(_.isDefined)

    finishedSessions.foreachRDD( rdd => {
      rdd.foreachPartition{iter =>
        val producer = Utils.createProducer(settings.value("metadataBrokerList_OutputQueue"))
        iter.foreach { msg =>
          val jsonString = msg.get._4.toString()
          val streamEvent = new ProducerRecord[String, String](settings.value("topicOutput"), null, jsonString)
          producer.send(streamEvent)
        }
        producer.close()
      }
    })

This is my serializable object Utils:

object Utils extends Serializable {

  def updateState(key: String,
                  value: Option[(Long, Long, Long, List[String])],
                  state: State[(Long, Long, Long, List[String])]): Option[(Long, Long, Long, List[String])] = {
    def reduce(first: (Long, Long, Long, List[String]), second: (Long, Long, Long, List[String])) = {
      (Math.min(first._1, second._1), Math.max(first._2, second._2), first._3 + second._3, first._4 ++ second._4)
    }

    value match {
      case Some(currentValue) =>
        val result = state
          .getOption()
          .map(currentState => reduce(currentState, currentValue))
          .getOrElse(currentValue)
        state.update(result)
        None
      case _ if state.isTimingOut() => state.getOption()
    }
  }

  def createProducer(metadataBrokerList: String): KafkaProducer[String, String] = {

    val  kafkaProps = new Properties()

    println("metadataBrokerList: " + metadataBrokerList)

    kafkaProps.put("bootstrap.servers", metadataBrokerList)

    // This is mandatory, even though we don't send key
    kafkaProps.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer")
    kafkaProps.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer")
    kafkaProps.put("acks", "1")

    // how many times to retry when produce request fails?
    kafkaProps.put("retries", "3")
    // This is an upper limit of how many messages Kafka Producer will attempt to batch before sending (bytes)
    kafkaProps.put("batch.size", "5")
    // How long will the producer wait before sending in order to allow more messages to get accumulated in the same batch
    kafkaProps.put("linger.ms", "5")

    new KafkaProducer[String, String](kafkaProps)
  }
}

EDIT:

After defining settings as a local Broadcast variable (val settings = ... instead of settings), the error message disappeared. However, the new error appeared and it's related to Caused by: java.lang.ClassNotFoundException: java.time.temporal.TemporalField. What does it mean?:

Driver stacktrace:

org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 3.0 failed 4 times, most recent failure: Lost task 6.3 in stage 3.0 (TID 34, ip-172-20-233-19.eu-west-1.compute.internal): java.lang.NoClassDefFoundError: java/time/temporal/TemporalField
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2$$anonfun$apply$1.apply(KafkaEventsConsumer.scala:163)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2$$anonfun$apply$1.apply(KafkaEventsConsumer.scala:160)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassNotFoundException: java.time.temporal.TemporalField
    at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
    at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
    at java.security.AccessController.doPrivileged(Native Method)
    at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
    ... 12 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:920)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:918)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
    at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:918)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2.apply(KafkaEventsConsumer.scala:160)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2.apply(KafkaEventsConsumer.scala:159)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:661)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:661)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:426)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
    at scala.util.Try$.apply(Try.scala:161)
    at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:224)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:223)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NoClassDefFoundError: java/time/temporal/TemporalField
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2$$anonfun$apply$1.apply(KafkaEventsConsumer.scala:163)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2$$anonfun$apply$1.apply(KafkaEventsConsumer.scala:160)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    ... 3 more
Caused by: java.lang.ClassNotFoundException: java.time.temporal.TemporalField
    at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
    at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
    at java.security.AccessController.doPrivileged(Native Method)
    at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
    ... 12 more
Exception in thread "streaming-job-executor-0" java.lang.Error: java.lang.InterruptedException
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1151)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.InterruptedException
    at java.lang.Object.wait(Native Method)
    at java.lang.Object.wait(Object.java:503)
    at org.apache.spark.scheduler.JobWaiter.awaitResult(JobWaiter.scala:73)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:612)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:920)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:918)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
    at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:918)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2.apply(KafkaEventsConsumer.scala:160)
    at org.testconsumer.kafka.KafkaEventsConsumer$$anonfun$run$2.apply(KafkaEventsConsumer.scala:159)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:661)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:661)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:426)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
    at scala.util.Try$.apply(Try.scala:161)
    at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:224)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:223)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    ... 2 more
16/11/28 18:42:08 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerStageCompleted(org.apache.spark.scheduler.StageInfo@764e333a)
16/11/28 18:42:08 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerJobEnd(1,1480354928309,JobFailed(org.apache.spark.SparkException: Job 1 cancelled because SparkContext was shut down))

It seems to be related to the version of Java. I have the following version on the cluster, but then how can I deploy my code and how to avoid the erro with java.time.temporal.TemporalField?:

java version "1.7.0_111"

EDIT #2 (POM.xml):

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.test</groupId>
    <artifactId>streaming_test</artifactId>
    <version>1.0-SNAPSHOT</version>
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>

        <java.version>1.7</java.version>
        <scala.version>2.10.6</scala.version>
        <spark.version>1.6.2</spark.version>
        <jackson.version>2.8.3</jackson.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <!--<dependency>-->
        <!--<groupId>org.apache.spark</groupId>-->
        <!--<artifactId>spark-core_2.10</artifactId>-->
        <!--<version>${spark.version}</version>-->
        <!--</dependency>-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <!--<dependency>-->
        <!--<groupId>org.apache.spark</groupId>-->
        <!--<artifactId>spark-mllib_2.10</artifactId>-->
        <!--<version>${spark.version}</version>-->
        <!--</dependency>-->
        <dependency>
            <groupId>com.fasterxml.jackson.module</groupId>
            <artifactId>jackson-module-scala_2.10</artifactId>
            <version>${jackson.version}</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>${jackson.version}</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-annotations</artifactId>
            <version>${jackson.version}</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-core</artifactId>
            <version>${jackson.version}</version>
        </dependency>
        <dependency>
            <groupId>net.debasishg</groupId>
            <artifactId>redisclient_2.10</artifactId>
            <version>3.3</version>
        </dependency>
        <dependency>
            <groupId>org.sedis</groupId>
            <artifactId>sedis_2.10</artifactId>
            <version>1.2.2</version>
        </dependency>
        <dependency>
            <groupId>com.lambdaworks</groupId>
            <artifactId>jacks_2.10</artifactId>
            <version>2.3.3</version>
        </dependency>
        <dependency>
            <groupId>com.typesafe</groupId>
            <artifactId>config</artifactId>
            <version>1.3.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-aws</artifactId>
            <version>2.6.0</version>
        </dependency>
        <dependency>
            <groupId>com.amazonaws</groupId>
            <artifactId>aws-java-sdk-s3</artifactId>
            <version>1.11.53</version>
        </dependency>
        <dependency>
            <groupId>org.apache.httpcomponents</groupId>
            <artifactId>httpclient</artifactId>
            <version>4.5.2</version>
        </dependency>
        <dependency>
            <groupId>net.java.dev.jets3t</groupId>
            <artifactId>jets3t</artifactId>
            <version>0.9.4</version>
        </dependency>
        <!--<dependency>-->
            <!--<groupId>com.github.nscala-time</groupId>-->
            <!--<artifactId>nscala-time_2.10</artifactId>-->
            <!--<version>2.12.0</version>-->
        <!--</dependency>-->
        <dependency>
            <groupId>com.databricks</groupId>
            <artifactId>spark-csv_2.10</artifactId>
            <version>1.5.0</version>
        </dependency>
    </dependencies>


    <build>
        <plugins>
            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <executions>
                    <execution>
                        <id>build-a</id>
                        <configuration>
                            <archive>
                                <manifest>
                                    <mainClass>org.test.consumer.SessionizerRunner</mainClass>
                                </manifest>
                            </archive>
                            <descriptorRefs>
                                <descriptorRef>jar-with-dependencies</descriptorRef>
                            </descriptorRefs>
                            <finalName>myTest</finalName>
                        </configuration>
                        <phase>package</phase>
                        <goals>
                            <goal>assembly</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <!-- Configure maven-compiler-plugin to use the desired Java version -->
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.1</version>
                <configuration>
                    <source>${java.version}</source>
                    <target>${java.version}</target>
                </configuration>
            </plugin>

            <!-- Use build-helper-maven-plugin to add Scala source and test source directories -->
            <plugin>
                <groupId>org.codehaus.mojo</groupId>
                <artifactId>build-helper-maven-plugin</artifactId>
                <version>1.10</version>
                <executions>
                    <execution>
                        <id>add-source</id>
                        <phase>generate-sources</phase>
                        <goals>
                            <goal>add-source</goal>
                        </goals>
                        <configuration>
                            <sources>
                                <source>src/main/scala</source>
                            </sources>
                        </configuration>
                    </execution>
                    <execution>
                        <id>add-test-source</id>
                        <phase>generate-test-sources</phase>
                        <goals>
                            <goal>add-test-source</goal>
                        </goals>
                        <configuration>
                            <sources>
                                <source>src/test/scala</source>
                            </sources>
                        </configuration>
                    </execution>
                </executions>
            </plugin>

            <!-- Use scala-maven-plugin for Scala support -->
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <goals>
                            <!-- Need to specify this explicitly, otherwise plugin won't be called when doing e.g. mvn compile -->
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

</project>

回答1:


It seems to be related to the version of Java. I have the following version on the cluster, but then how can I deploy my code and how to avoid the erro with java.time.temporal.TemporalField?:

java.time was added in Java 8. Search for any uses of java.time. in your code. Current Spark version requires Java 7 and Kafka too, so they shouldn't be the problem (but check any other libraries you use).




回答2:


Caused by: java.io.NotSerializableException: org.testconsumer.kafka.KafkaEventsConsumer

Your error trace clearly shows what is the problem. KafkaProducer is not serialized so You have to annotate your kafka classes @transient or you can get help from this



来源：https://stackoverflow.com/questions/40849850/java-lang-classnotfoundexception-java-time-temporal-temporalfield-when-running

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