首页   技术笔记   网址导航   Json在线解析   二维码   Ip地址查询   在线流程图  
新用户注册 | 会员登录
当前位置:  开发笔记 > 编程语言 > 正文

将Scala代码部署到Spark时的ClassNotFoundException anonfun

作者：yzh148448 | 2023-06-11 17:35
如何解决《将Scala代码部署到Spark时的ClassNotFoundExceptionanonfun》经验，为你挑选了1个好方法。

我是Apache Spark的新手,我正在尝试将一段简单的scala代码部署到Spark.

注意:我正在尝试连接到我通过我的java参数配置的现有正在运行的集群:spark.master=spark://MyHostName:7077

环境

使用scala 2.10构建Spark 1.5.1

Spark 在我的本地计算机上运行独立模式

操作系统:Mac OS El Captain

JVM:JDK 1.8.0_60

IDE:IntelliJ IDEA社区14.1.5

Scala版本:2.10.4

sbt:0.13.8

码

import org.apache.spark.{SparkConf, SparkContext}
object HelloSpark {
  def main(args: Array[String]) {
    val logFile = "/README.md"
    val conf = new SparkConf().setAppName("Simple Application")
    val sc = new SparkContext(conf)
    val logData = sc.textFile(logFile, 2).cache()
    val numAs = logData.filter(line => line.contains("a")).count()
    println("%s done!".format(numAs))
  }
}

build.sbt

name := "data-streamer210"

version := "1.0"

scalaVersion := "2.10.4"

libraryDependencies ++= Seq(
  "org.apache.spark" % "spark-core_2.10" % "1.5.1",
  "org.apache.spark" % "spark-streaming_2.10" % "1.5.1",
  "org.apache.spark" % "spark-mllib_2.10" % "1.5.1",
  "org.apache.spark" % "spark-bagel_2.10" % "1.5.1",
  "org.apache.spark" % "spark-streaming-twitter_2.10" % "1.5.1"
)

错误

15/10/19 19:40:09 INFO SparkContext: Starting job: count at HelloSpark.scala:14
15/10/19 19:40:09 INFO DAGScheduler: Got job 0 (count at HelloSpark.scala:14) with 2 output partitions
15/10/19 19:40:09 INFO DAGScheduler: Final stage: ResultStage 0(count at HelloSpark.scala:14)
15/10/19 19:40:09 INFO DAGScheduler: Parents of final stage: List()
15/10/19 19:40:09 INFO DAGScheduler: Missing parents: List()
15/10/19 19:40:09 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[2] at filter at HelloSpark.scala:14), which has no missing parents
15/10/19 19:40:09 INFO MemoryStore: ensureFreeSpace(3192) called with curMem=120313, maxMem=2061647216
15/10/19 19:40:09 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 3.1 KB, free 1966.0 MB)
15/10/19 19:40:09 INFO MemoryStore: ensureFreeSpace(1892) called with curMem=123505, maxMem=2061647216
15/10/19 19:40:09 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 1892.0 B, free 1966.0 MB)
15/10/19 19:40:09 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 127.0.0.1:50941 (size: 1892.0 B, free: 1966.1 MB)
15/10/19 19:40:09 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:861
15/10/19 19:40:09 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 0 (MapPartitionsRDD[2] at filter at HelloSpark.scala:14)
15/10/19 19:40:09 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks
15/10/19 19:40:10 INFO SparkDeploySchedulerBackend: Registered executor: AkkaRpcEndpointRef(Actor[akka.tcp://sparkExecutor@127.0.0.1:50951/user/Executor#-147774947]) with ID 0
15/10/19 19:40:10 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:10 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:10 INFO SparkDeploySchedulerBackend: Registered executor: AkkaRpcEndpointRef(Actor[akka.tcp://sparkExecutor@127.0.0.1:50952/user/Executor#1450479604]) with ID 2
15/10/19 19:40:10 INFO SparkDeploySchedulerBackend: Registered executor: AkkaRpcEndpointRef(Actor[akka.tcp://sparkExecutor@127.0.0.1:50957/user/Executor#1447408721]) with ID 1
15/10/19 19:40:10 INFO SparkDeploySchedulerBackend: Registered executor: AkkaRpcEndpointRef(Actor[akka.tcp://sparkExecutor@127.0.0.1:50955/user/Executor#1397136754]) with ID 3
15/10/19 19:40:10 INFO BlockManagerMasterEndpoint: Registering block manager 127.0.0.1:50963 with 530.0 MB RAM, BlockManagerId(0, 127.0.0.1, 50963)
15/10/19 19:40:10 INFO BlockManagerMasterEndpoint: Registering block manager 127.0.0.1:50964 with 530.0 MB RAM, BlockManagerId(2, 127.0.0.1, 50964)
15/10/19 19:40:10 INFO BlockManagerMasterEndpoint: Registering block manager 127.0.0.1:50965 with 530.0 MB RAM, BlockManagerId(1, 127.0.0.1, 50965)
15/10/19 19:40:10 INFO BlockManagerMasterEndpoint: Registering block manager 127.0.0.1:50966 with 530.0 MB RAM, BlockManagerId(3, 127.0.0.1, 50966)
15/10/19 19:40:11 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 127.0.0.1:50963 (size: 1892.0 B, free: 530.0 MB)
15/10/19 19:40:11 WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1, 127.0.0.1): java.lang.ClassNotFoundException: HelloSpark$$anonfun$1
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    at java.lang.Class.forName0(Native Method)
    at java.lang.Class.forName(Class.java:348)
    at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
    at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613)
    at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

15/10/19 19:40:11 INFO TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 1]
15/10/19 19:40:11 INFO TaskSetManager: Starting task 0.1 in stage 0.0 (TID 2, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO TaskSetManager: Starting task 1.1 in stage 0.0 (TID 3, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 127.0.0.1:50966 (size: 1892.0 B, free: 530.0 MB)
15/10/19 19:40:11 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 127.0.0.1:50964 (size: 1892.0 B, free: 530.0 MB)
15/10/19 19:40:11 INFO TaskSetManager: Lost task 1.1 in stage 0.0 (TID 3) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 2]
15/10/19 19:40:11 INFO TaskSetManager: Starting task 1.2 in stage 0.0 (TID 4, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO TaskSetManager: Lost task 1.2 in stage 0.0 (TID 4) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 3]
15/10/19 19:40:11 INFO TaskSetManager: Lost task 0.1 in stage 0.0 (TID 2) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 4]
15/10/19 19:40:11 INFO TaskSetManager: Starting task 0.2 in stage 0.0 (TID 5, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO TaskSetManager: Starting task 1.3 in stage 0.0 (TID 6, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO TaskSetManager: Lost task 0.2 in stage 0.0 (TID 5) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 5]
15/10/19 19:40:11 INFO TaskSetManager: Starting task 0.3 in stage 0.0 (TID 7, 127.0.0.1, PROCESS_LOCAL, 2160 bytes)
15/10/19 19:40:11 INFO TaskSetManager: Lost task 0.3 in stage 0.0 (TID 7) on executor 127.0.0.1: java.lang.ClassNotFoundException (HelloSpark$$anonfun$1) [duplicate 6]
15/10/19 19:40:11 ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
15/10/19 19:40:11 INFO TaskSchedulerImpl: Cancelling stage 0
15/10/19 19:40:11 INFO TaskSchedulerImpl: Stage 0 was cancelled
15/10/19 19:40:11 INFO DAGScheduler: ResultStage 0 (count at HelloSpark.scala:14) failed in 2.613 s
15/10/19 19:40:11 INFO DAGScheduler: Job 0 failed: count at HelloSpark.scala:14, took 2.716305 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 7, 127.0.0.1): java.lang.ClassNotFoundException: HelloSpark$$anonfun$1
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    at java.lang.Class.forName0(Native Method)
    at java.lang.Class.forName(Class.java:348)
    at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
    at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613)
    at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1822)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1835)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1848)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1919)
    at org.apache.spark.rdd.RDD.count(RDD.scala:1121)
    at HelloSpark$.main(HelloSpark.scala:14)
    at HelloSpark.main(HelloSpark.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
Caused by: java.lang.ClassNotFoundException: HelloSpark$$anonfun$1
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    at java.lang.Class.forName0(Native Method)
    at java.lang.Class.forName(Class.java:348)
    at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
    at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613)
    at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
15/10/19 19:40:11 INFO SparkContext: Invoking stop() from shutdown hook
15/10/19 19:40:11 WARN TaskSetManager: Lost task 1.3 in stage 0.0 (TID 6, 127.0.0.1): org.apache.spark.TaskKilledException
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:204)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

15/10/19 19:40:11 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
15/10/19 19:40:11 INFO SparkUI: Stopped Spark web UI at http://127.0.0.1:4040
15/10/19 19:40:11 INFO DAGScheduler: Stopping DAGScheduler
15/10/19 19:40:11 INFO SparkDeploySchedulerBackend: Shutting down all executors
15/10/19 19:40:11 INFO SparkDeploySchedulerBackend: Asking each executor to shut down
15/10/19 19:40:11 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
15/10/19 19:40:11 INFO MemoryStore: MemoryStore cleared
15/10/19 19:40:11 INFO BlockManager: BlockManager stopped
15/10/19 19:40:11 INFO BlockManagerMaster: BlockManagerMaster stopped
15/10/19 19:40:11 INFO SparkContext: Successfully stopped SparkContext
15/10/19 19:40:11 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
15/10/19 19:40:11 INFO ShutdownHookManager: Shutdown hook called
15/10/19 19:40:11 INFO ShutdownHookManager: Deleting directory /private/var/folders/q9/m_d81ms107n09tj8k5wbzfb40000gp/T/spark-53ce9474-5488-4d50-bfb6-c58ddeed7640

Process finished with exit code 1

marios.. 18

从IntelliJ运行Spark时,您可以连接到"本地"spark JVM或远程集群.

如果将master设置为本地(例如setMaster("local[*]")),那么您在本地范围/项目中拥有的任何代码都将可用于您刚刚创建的临时本地(单个JVM)集群.一切都在本地运行,并在测试结束时退出(如果运行单元测试),或者当您在IntelliJ中作为应用程序运行时退出应用程序.

但是,如果将master设置为指向远程集群(比如说setMaster("spark://localhost:7077")),则需要确保集群可以访问新代码(在您的情况下,它需要访问您要传递给的闭包filter).

当我想在正在运行的Spark集群上执行一段新代码时,我通常会通过在Uber Jar中打包我的应用程序(参见sbt-assembly),然后将其作为参数传递给spark-submit(请参阅更多详细信息)点击链接).



1> marios..：

从IntelliJ运行Spark时,您可以连接到"本地"spark JVM或远程集群.

如果将master设置为本地(例如setMaster("local[*]")),那么您在本地范围/项目中拥有的任何代码都将可用于您刚刚创建的临时本地(单个JVM)集群.一切都在本地运行,并在测试结束时退出(如果运行单元测试),或者当您在IntelliJ中作为应用程序运行时退出应用程序.

但是,如果将master设置为指向远程集群(比如说setMaster("spark://localhost:7077")),则需要确保集群可以访问新代码(在您的情况下,它需要访问您要传递给的闭包filter).

当我想在正在运行的Spark集群上执行一段新代码时,我通常会通过在Uber Jar中打包我的应用程序(参见sbt-assembly),然后将其作为参数传递给spark-submit(请参阅更多详细信息)点击链接).

@HosangJeon,我很高兴它有所帮助.Spark自然可以在多个JVM上运行.每个JVM都需要拥有所有代码,以便可以加载类调用它们上的方法等等.您需要有一种方法将代码(您的类)交付给集群中的所有JVM.Spark提交是一种简单的方法.
推荐阅读
devbox
yzh148448
这个屌丝很懒，什么也没留下！
关注作者
Tags | 热门标签
RankList | 热门文章
DevBox开发工具箱 | 专业的在线开发工具网站    京公网安备 11010802040832号  |  京ICP备19059560号-6
Copyright © 1998 - 2020 DevBox.CN. All Rights Reserved devBox.cn 开发工具箱 版权所有