我试图读取一个 parquet 文件,这是目前在AWS S3和获得以下错误。
17/12/19 11:27:40 DEBUG DAGScheduler: ShuffleMapTask finished on 0
17/12/19 11:27:40 DEBUG DAGScheduler: submitStage(ResultStage 2)
17/12/19 11:27:40 DEBUG DAGScheduler: missing: List(ShuffleMapStage 1)
17/12/19 11:27:40 DEBUG DAGScheduler: submitStage(ShuffleMapStage 1)
17/12/19 11:27:40 DEBUG TaskSchedulerImpl: parentName: , name: TaskSet_1, runningTasks: 2
17/12/19 11:27:40 WARN TaskSetManager: Lost task 2.0 in stage 1.0 (TID 4, ip-xxx-xxx-xxx-xxx.ec2.internal): com.amazonaws.services.s3.model.AmazonS3Exception: Status Code: 403, AWS Service: Amazon S3, AWS Request ID: xxxxxxx, AWS Error Code: null, AWS Error Message: Forbidden, S3 Extended Request ID: xxxxxxxx/xxxxxxxxx=
at com.amazonaws.http.AmazonHttpClient.handleErrorResponse(AmazonHttpClient.java:798)
at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:421)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528)
at com.amazonaws.services.s3.AmazonS3Client.getObjectMetadata(AmazonS3Client.java:976)
at com.amazonaws.services.s3.AmazonS3Client.getObjectMetadata(AmazonS3Client.java:956)
at org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:688)
at org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:71)
at org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:385)
at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:157)
at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
at org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.<init>(SqlNewHadoopRDD.scala:180)
at org.apache.spark.rdd.SqlNewHadoopRDD.compute(SqlNewHadoopRDD.scala:126)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
17/12/19 11:27:40 DEBUG DAGScheduler: submitStage(ResultStage 2)
在Spark中启用调试日志后,我现在可以在将Spark作业提交到S3时看到NPE。
17/12/19 11:27:39 INFO SparkContext: Starting job: count at TestRead.scala:54
17/12/19 11:27:39 INFO DAGScheduler: Registering RDD 4 (count at TestRead.scala:54)
17/12/19 11:27:39 INFO DAGScheduler: Got job 1 (count at TestRead.scala:54) with 1 output partitions
17/12/19 11:27:39 INFO DAGScheduler: Final stage: ResultStage 2 (count at TestRead.scala:54)
17/12/19 11:27:39 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 1)
17/12/19 11:27:39 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 1)
17/12/19 11:27:39 DEBUG DAGScheduler: submitStage(ResultStage 2)
17/12/19 11:27:39 DEBUG DAGScheduler: missing: List(ShuffleMapStage 1)
17/12/19 11:27:39 DEBUG DAGScheduler: submitStage(ShuffleMapStage 1)
17/12/19 11:27:39 DEBUG DAGScheduler: missing: List()
17/12/19 11:27:39 INFO DAGScheduler: Submitting ShuffleMapStage 1 (MapPartitionsRDD[4] at count at TestRead.scala:54), which has no missing parents
17/12/19 11:27:39 DEBUG DAGScheduler: submitMissingTasks(ShuffleMapStage 1)
17/12/19 11:27:39 DEBUG ParquetRelation$$anonfun$buildInternalScan$1$$anon$1: Failed to use InputSplit#getLocationInfo.
java.lang.NullPointerException
at scala.collection.mutable.ArrayOps$ofRef$.length$extension(ArrayOps.scala:114)
at scala.collection.mutable.ArrayOps$ofRef.length(ArrayOps.scala:114)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:32)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at org.apache.spark.rdd.HadoopRDD$.convertSplitLocationInfo(HadoopRDD.scala:412)
at org.apache.spark.rdd.SqlNewHadoopRDD.getPreferredLocations(SqlNewHadoopRDD.scala:259)
at org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:257)
at org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:257)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.preferredLocations(RDD.scala:256)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1545)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply$mcVI$sp(DAGScheduler.scala:1556)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply(DAGScheduler.scala:1555)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply(DAGScheduler.scala:1555)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1555)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1553)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1553)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply$mcVI$sp(DAGScheduler.scala:1556)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply(DAGScheduler.scala:1555)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$1.apply(DAGScheduler.scala:1555)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1555)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1553)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1553)
at org.apache.spark.scheduler.DAGScheduler.getPreferredLocs(DAGScheduler.scala:1519)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$14.apply(DAGScheduler.scala:969)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$14.apply(DAGScheduler.scala:969)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at org.apache.spark.scheduler.DAGScheduler.submitMissingTasks(DAGScheduler.scala:969)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:921)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$submitStage$4.apply(DAGScheduler.scala:924)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$submitStage$4.apply(DAGScheduler.scala:923)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:923)
at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:861)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1607)
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$$anon$1.run(EventLoop.scala:48)
17/12/19 11:27:39 DEBUG ParquetRelation$$anonfun$buildInternalScan$1$$anon$1: Failed to use InputSplit#getLocationInfo.
我不知道为什么我会得到这个错误。下面是我的代码:-
val conf = new SparkConf(true).setAppName("TestRead")
conf.set(SPARK_CASS_CONN_HOST, config.cassHost)
conf.set("spark.cassandra.connection.timeout_ms","10000")
val sc = new SparkContext(conf)
sc.hadoopConfiguration.set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
sc.hadoopConfiguration.set("fs.s3a.access.key", config.s3AccessKey)
sc.hadoopConfiguration.set("fs.s3a.secret.key", config.s3SecretKey)
val sqlContext = new SQLContext(sc)
val data = sqlContext.read.parquet(s"s3a://${config.s3bucket}/${config.s3folder}")
println(s"data size is ${data.count()}")
data.show()
if(config.cassWriteToTable){
println("Writing to Cassandra Table")
data.write.mode(SaveMode.Append).format("org.apache.spark.sql.cassandra").options(Map("table" -> config.cassTable, "keyspace" -> config.cassKeyspace)).save()
}
println("Stopping TestRead...")
sc.stop()
我已经在我的build.sbt文件中包含了以下依赖项:-
"org.apache.spark" % "spark-core_2.10" % "1.6.1" % "provided,test" ,
"org.apache.spark" % "spark-sql_2.10" % "1.6.1" % "provided",
"com.typesafe.play" % "play-json_2.10" % "2.4.6" excludeAll(ExclusionRule(organization = "com.fasterxml.jackson.core")),
"mysql" % "mysql-connector-java" % "5.1.39",
"com.amazonaws" % "aws-java-sdk-pom" % "1.11.7" exclude("commons-beanutils","commons-beanutils") exclude("commons-collections","commons-collections") excludeAll ExclusionRule(organization = "javax.servlet")
这里可能有什么问题?
2条答案
按热度按时间cyvaqqii1#
403/禁止:您的登录名无权访问您试图读取的文件。
关于NPE,请在www.example.com上提交一份针对Spark的错误报告issues.apache.org;他们将努力查明谁该受到指责。
不过,在执行此操作之前:确保你使用的是最新的Spark版本,并搜索那个NPE。不需要提交副本,特别是如果已经修复的话。
0mkxixxg2#
我也遇到过类似的问题,通过将Hadoop库从2.7.x升级到2.8.5解决了这个问题。
对于文档(https://hadoop.apache.org/docs/r2.8.5/)
S3A改进:添加了插入任何AWSCredentialsProvider的功能,支持从Hadoop凭据提供程序API读取s3a凭据以及XML配置文件,支持Amazon STS临时凭据
您可能还希望使用“org.apache.hadoop.fs.s3a.TemporaryAWSCredentialsProvider”作为凭据提供程序,并指定除访问和密钥之外的标记。