Spark提交失败，Hive

时间：2014-12-02 05:38:07

标签： hive apache-spark

我正在尝试使用Scala编写的Spark 1.1.0程序来工作，但我很难用它。我有一个非常简单的Hive查询：

select json, score from data

当我从spark-shell运行以下命令时，一切正常（我需要在驱动程序类路径中使用MYSQL_CONN，因为我使用Hive和MySQL元数据存储）

bin/spark-shell --master $SPARK_URL --driver-class-path $MYSQL_CONN

import org.apache.spark.sql.hive.HiveContext
val sqlContext = new HiveContext(sc)
sqlContext.sql("select json from data").map(t => t.getString(0)).take(10).foreach(println)

我得到十行json就像我想要的那样。但是，当我使用spark-submit运行时，如下所示我遇到了问题

bin/spark-submit --master $SPARK_URL --class spark.Main --driver-class-path $MYSQL_CONN target/spark-testing-1.0-SNAPSHOT.jar

这是我的整个Spark程序

package spark

import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.{SparkContext, SparkConf}

object Main {
  def main(args: Array[String]) {
    val sc = new SparkContext(new SparkConf().setAppName("Gathering Data"))
    val sqlContext = new HiveContext(sc)
    sqlContext.sql("select json from data").map(t => t.getString(0)).take(10).foreach(println)
  }
}

这是结果堆栈

14/12/01 21:30:04 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, match1hd17.dc1): java.lang.ClassNotFoundException: spark.Main$$anonfun$main$1
        java.net.URLClassLoader$1.run(URLClassLoader.java:200)
        java.security.AccessController.doPrivileged(Native Method)
        java.net.URLClassLoader.findClass(URLClassLoader.java:188)
        java.lang.ClassLoader.loadClass(ClassLoader.java:307)
        java.lang.ClassLoader.loadClass(ClassLoader.java:252)
        java.lang.ClassLoader.loadClassInternal(ClassLoader.java:320)
        java.lang.Class.forName0(Native Method)
        java.lang.Class.forName(Class.java:247)
        org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:59)
        java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1575)
        java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1496)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1732)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1947)
        java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1871)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1753)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1947)
        java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1871)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1753)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.readObject(ObjectInputStream.java:351)
        org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:62)
        org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:87)
        org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:57)
        org.apache.spark.scheduler.Task.run(Task.scala:54)
        org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
        java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
        java.lang.Thread.run(Thread.java:619)
14/12/01 21:30:10 ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
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 3, match1hd12.dc1m): java.lang.ClassNotFoundException: spark.Main$$anonfun$main$1
        java.net.URLClassLoader$1.run(URLClassLoader.java:200)
        java.security.AccessController.doPrivileged(Native Method)
        java.net.URLClassLoader.findClass(URLClassLoader.java:188)
        java.lang.ClassLoader.loadClass(ClassLoader.java:307)
        java.lang.ClassLoader.loadClass(ClassLoader.java:252)
        java.lang.ClassLoader.loadClassInternal(ClassLoader.java:320)
        java.lang.Class.forName0(Native Method)
        java.lang.Class.forName(Class.java:247)
        org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:59)
        java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1575)
        java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1496)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1732)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1947)
        java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1871)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1753)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1947)
        java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1871)
        java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1753)
        java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1329)
        java.io.ObjectInputStream.readObject(ObjectInputStream.java:351)
        org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:62)
        org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:87)
        org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:57)
        org.apache.spark.scheduler.Task.run(Task.scala:54)
        org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
        java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
        java.lang.Thread.run(Thread.java:619)
Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1185)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1174)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1173)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1173)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
    at akka.actor.ActorCell.invoke(ActorCell.scala:456)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
    at akka.dispatch.Mailbox.run(Mailbox.scala:219)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)

我已经花了好几个小时，我不知道为什么这只适用于spark-shell。我查看了各个节点上的stderr输出，它们具有相同的神秘错误消息。如果有人能够解释为什么这只适用于火花壳而不是火花提交那将是非常棒的。

由于

更新：

我一直在玩，下面的程序运行正常。

package spark

import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.{SparkContext, SparkConf}

object Main {
  def main(args: Array[String]) {
    val sc = new SparkContext(new SparkConf().setAppName("Gathering Data"))
    val sqlContext = new HiveContext(sc)
    sqlContext.sql("select json from data").take(10).map(t => t.getString(0)).foreach(println)
  }
}

显然，这不会对大量数据起作用，但它表明问题似乎出现在ScehmaRDD.map（）函数中。

1 个答案:

答案 0 :(得分：0)

似乎火花上下文初始化存在问题。

请尝试以下代码：

val sparkConf = new SparkConf().setAppName("Gathering Data");
val sc = new SparkContext(sparkConf);
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