Thomas Graves created SPARK-38379: ------------------------------------- Summary: Kubernetes: NoSuchElementException: spark.app.id when using PersistentVolumes Key: SPARK-38379 URL: https://issues.apache.org/jira/browse/SPARK-38379 Project: Spark Issue Type: Bug Components: Kubernetes Affects Versions: 3.2.1 Reporter: Thomas Graves
I'm using Spark 3.2.1 on a kubernetes cluster and starting a spark-shell in client mode. I'm using persistent local volumes to mount nvme under /data in the executors and on startup the driver always throws the warning below. using these options: --conf spark.kubernetes.executor.volumes.persistentVolumeClaim.spark-local-dir-1.options.claimName=OnDemand \ --conf spark.kubernetes.executor.volumes.persistentVolumeClaim.spark-local-dir-1.options.storageClass=fast-disks \ --conf spark.kubernetes.executor.volumes.persistentVolumeClaim.spark-local-dir-1.options.sizeLimit=500Gi \ --conf spark.kubernetes.executor.volumes.persistentVolumeClaim.spark-local-dir-1.mount.path=/data \ --conf spark.kubernetes.executor.volumes.persistentVolumeClaim.spark-local-dir-1.mount.readOnly=false {code:java} 22/03/01 20:21:22 WARN ExecutorPodsSnapshotsStoreImpl: Exception when notifying snapshot subscriber. java.util.NoSuchElementException: spark.app.id at org.apache.spark.SparkConf.$anonfun$get$1(SparkConf.scala:245) at scala.Option.getOrElse(Option.scala:189) at org.apache.spark.SparkConf.get(SparkConf.scala:245) at org.apache.spark.SparkConf.getAppId(SparkConf.scala:450) at org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.$anonfun$constructVolumes$4(MountVolumesFeatureStep.scala:88) at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286) at scala.collection.Iterator.foreach(Iterator.scala:943) at scala.collection.Iterator.foreach$(Iterator.scala:943) at scala.collection.AbstractIterator.foreach(Iterator.scala:1431) at scala.collection.IterableLike.foreach(IterableLike.scala:74) at scala.collection.IterableLike.foreach$(IterableLike.scala:73) at scala.collection.AbstractIterable.foreach(Iterable.scala:56) at scala.collection.TraversableLike.map(TraversableLike.scala:286) at scala.collection.TraversableLike.map$(TraversableLike.scala:279) at scala.collection.AbstractTraversable.map(Traversable.scala:108) at org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.constructVolumes(MountVolumesFeatureStep.scala:57) at org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.configurePod(MountVolumesFeatureStep.scala:34) at org.apache.spark.scheduler.cluster.k8s.KubernetesExecutorBuilder.$anonfun$buildFromFeatures$4(KubernetesExecutorBuilder.scala:64) at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126) at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122) at scala.collection.immutable.List.foldLeft(List.scala:91) at org.apache.spark.scheduler.cluster.k8s.KubernetesExecutorBuilder.buildFromFeatures(KubernetesExecutorBuilder.scala:63) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$requestNewExecutors$1(ExecutorPodsAllocator.scala:391) at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:158) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.requestNewExecutors(ExecutorPodsAllocator.scala:382) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$onNewSnapshots$36(ExecutorPodsAllocator.scala:346) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$onNewSnapshots$36$adapted(ExecutorPodsAllocator.scala:339) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.onNewSnapshots(ExecutorPodsAllocator.scala:339) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$start$3(ExecutorPodsAllocator.scala:117) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$start$3$adapted(ExecutorPodsAllocator.scala:117) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber.org$apache$spark$scheduler$cluster$k8s$ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber$$processSnapshotsInternal(ExecutorPodsSnapshotsStoreImpl.scala:138) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber.processSnapshots(ExecutorPodsSnapshotsStoreImpl.scala:126) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl.$anonfun$addSubscriber$1(ExecutorPodsSnapshotsStoreImpl.scala:81) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294) 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) {code} -- This message was sent by Atlassian Jira (v8.20.1#820001) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org