Question

我在CDH 5.8.3群集上使用Spark 1.6.0编写Spark Streaming应用程序。应用程序非常简单：它从Kafka读取，它对DStream / RDD进行一些转换，然后将它们输出到Hive表。我还尝试使用sqlContext放置一些愚蠢的示例代码，但错误仍然存在。

我的问题是我无法在DStream的foreachRDD语句中使用HiveContext。

我的代码如下所示：

val sc = new SparkContext()
val sqlContext = new HiveContext(sc)
val ssc = new StreamingContext(sc, Minutes(sparkBatchInterval))
ssc.checkpoint(CHECKPOINT_DIR)
ssc.sparkContext.setLogLevel("WARN")
val kafkaParams = Map[String, String]("metadata.broker.list" -> brokersList, "auto.offset.reset" -> "smallest")
KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](ssc, kafkaParams, Set(kafkaTopic))
val validatedAndPersisted = dstream.transform( rdd => {...}).persist(StorageLevel.MEMORY_AND_DISK_SER)
  val recordsToBeIngested = ...
  recordsToBeIngested.foreachRDD(rdd=> {
  rdd.persist(StorageLevel.MEMORY_AND_DISK)

  val ingestCount = rdd.count
  if(ingestCount>0) {
    sqlContext.tables("sc4").show() //here actually I shoud have a insertInto
  }
}

我得到的错误就是这个：

Exception in thread "main" java.lang.NullPointerException
    at org.apache.spark.sql.hive.client.ClientWrapper.conf(ClientWrapper.scala:205)
    at org.apache.spark.sql.hive.HiveContext.hiveconf$lzycompute(HiveContext.scala:554)
    at org.apache.spark.sql.hive.HiveContext.hiveconf(HiveContext.scala:553)
    at org.apache.spark.sql.hive.HiveContext$$anonfun$configure$1.apply(HiveContext.scala:540)
    at org.apache.spark.sql.hive.HiveContext$$anonfun$configure$1.apply(HiveContext.scala:539)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.AbstractTraversable.map(Traversable.scala:105)
    at org.apache.spark.sql.hive.HiveContext.configure(HiveContext.scala:539)
    at org.apache.spark.sql.hive.HiveContext.metadataHive$lzycompute(HiveContext.scala:252)
    at org.apache.spark.sql.hive.HiveContext.metadataHive(HiveContext.scala:239)
    at org.apache.spark.sql.hive.HiveContext$$anon$2.<init>(HiveContext.scala:459)
    at org.apache.spark.sql.hive.HiveContext.catalog$lzycompute(HiveContext.scala:459)
    at org.apache.spark.sql.hive.HiveContext.catalog(HiveContext.scala:458)
    at org.apache.spark.sql.hive.HiveContext$$anon$3.<init>(HiveContext.scala:475)
    at org.apache.spark.sql.hive.HiveContext.analyzer$lzycompute(HiveContext.scala:475)
    at org.apache.spark.sql.hive.HiveContext.analyzer(HiveContext.scala:474)
    at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
    at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
    at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:52)
    at org.apache.spark.sql.SQLContext.tables(SQLContext.scala:855)
    at myPackage.Ingestion$$anonfun$createStreamingContext$1.apply(Ingestion.scala:173)
    at myPackage.Ingestion$$anonfun$createStreamingContext$1.apply(Ingestion.scala:166)
    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)

您是否知道这可能是导致此错误的原因或我该如何解决？

谢谢你，马可

Answer 1

我自己找到了答案。问题是由于我在StreamingContext之前创建了HiveContext。在StreamingContext创建之后移动创建解决了问题。

Spark Streaming HiveContext NullPointerException

1 个答案: