通过spark作业服务器运行作业

gkn4icbw 于 2021-05-29 发布在 Hadoop

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我已经为namenode和resourcemanager设置了一个带有ha的3节点hadoop集群。我还在一台namenode机器上安装了spark作业服务器。
我已经测试了运行job服务器的测试示例，比如wordcount示例和longpi job，它运行得非常完美，没有任何问题。我还可以从远程主机发出curl命令，通过spark作业服务器读取结果。
但是，当我将“spark-examples-1.6.0-hadoop2.6.0.jar”上传到spark job server/jars并尝试运行sparkpi job时失败了，

[hduser@ptfhadoop02v lib]$ curl -d "" 'ptfhadoop01v:8090/jobs?appName=SparkPi&classPath=org.apache.spark.examples.SparkPi'
{
  "status": "ERROR",
  "result": {
    "message": "Ask timed out on [Actor[akka://JobServer/user/context-supervisor/ece2be39-org.apache.spark.examples.SparkPi#-630965857]] after [10000 ms]",
    "errorClass": "akka.pattern.AskTimeoutException",
    "stack":["akka.pattern.PromiseActorRef$$anonfun$1.apply$mcV$sp(AskSupport.scala:334)", "akka.actor.Scheduler$$anon$7.run(Scheduler.scala:117)", "scala.concurrent.Future$InternalCallbackExecutor$.scala$concurrent$Future$InternalCallbackExecutor$$unbatchedExecute(Future.scala:694)", "scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:691)", "akka.actor.LightArrayRevolverScheduler$TaskHolder.executeTask(Scheduler.scala:467)", "akka.actor.LightArrayRevolverScheduler$$anon$8.executeBucket$1(Scheduler.scala:419)", "akka.actor.LightArrayRevolverScheduler$$anon$8.nextTick(Scheduler.scala:423)", "akka.actor.LightArrayRevolverScheduler$$anon$8.run(Scheduler.scala:375)", "java.lang.Thread.run(Thread.java:745)"]
  }

我还尝试手动将sparkpi.scala作业放置在/usr/local/hadoop/spark jobserver/job server tests/src/spark.jobserver下，并使用sbt构建包，但它抛出了相同的错误。
版本信息

[hduser@ptfhadoop01v spark.jobserver]$ sbt sbtVersion
[info] Set current project to spark-jobserver (in build file:/usr/local/hadoop/spark-jobserver/job-server-tests/src/spark.jobserver/)
[info] 0.13.11

Spark Version - spark-1.6.0
Scala Version - 2.10.4

关于如何消除这个错误并从spark-examples jar文件中获取输出有什么建议吗

hadoop scala apache-spark spark-jobserver

来源：https://stackoverflow.com/questions/37315573/running-jobs-via-spark-job-server

1条答案

按热度按时间

li9yvcax1#

package spark.jobserver

import com.typesafe.config.{Config, ConfigFactory}
import org.apache.spark._
import org.apache.spark.SparkContext._
import scala.math.random

/**Computes an approximation to pi */
object SparkPi extends SparkJob {
  def main(args: Array[String]) {
    val conf = new SparkConf().setMaster("local[4]").setAppName("SparkPi")
    val sc = new SparkContext(conf)
    val config = ConfigFactory.parseString("")
    val results = runJob(sc, config)
    println("Pi is roughly " + results)
 }

  override def validate(sc: SparkContext, config: Config):SparkJobValidation = {
SparkJobValid
  }

  override def runJob(sc: SparkContext, config: Config): Any = {
    val slices = if (args.length > 0) args(0).toInt else 2
    val n = math.min(100000L * slices, Int.MaxValue).toInt
    val count = sc.parallelize(1 until n, slices).map { i =>
    val x = random * 2 - 1
    val y = random * 2 - 1
    if (x*x + y*y < 1) 1 else 0
   }.reduce(_ + _)

 (4.0 * count / n)
  }

}

我通过修改代码来扩展sparkjob，从而成功地让它工作了，感谢您的澄清

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通过spark作业服务器运行作业

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