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https://issues.apache.org/jira/browse/SPARK-43342?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dongjoon Hyun closed SPARK-43342.
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> Revert SPARK-39006 Show a directional error message for executor PVC dynamic
> allocation failure
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-43342
> URL: https://issues.apache.org/jira/browse/SPARK-43342
> Project: Spark
> Issue Type: Bug
> Components: Kubernetes
> Affects Versions: 3.4.0
> Reporter: Oleg Frenkel
> Assignee: Qian Sun
> Priority: Major
> Fix For: 3.4.1
>
>
> When using static PVC with Spark 3.4, spark PI example fails with the error
> below. Previous versions of Spark worked well.
> {code:java}
> 23/04/26 13:22:02 INFO ExecutorPodsAllocator: Going to request 5 executors
> from Kubernetes for ResourceProfile Id: 0, target: 5, known: 0,
> sharedSlotFromPendingPods: 2147483647. 23/04/26 13:22:02 INFO
> BasicExecutorFeatureStep: Decommissioning not enabled, skipping shutdown
> script 23/04/26 13:22:02 ERROR ExecutorPodsSnapshotsStoreImpl: Going to stop
> due to IllegalArgumentException java.lang.IllegalArgumentException: PVC
> ClaimName: a1pvc should contain OnDemand or SPARK_EXECUTOR_ID when requiring
> multiple executors at
> org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.checkPVCClaimName(MountVolumesFeatureStep.scala:135)
> at
> org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.$anonfun$constructVolumes$4(MountVolumesFeatureStep.scala:75)
> at
> scala.collection.TraversableLike.$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:58)
> at
> org.apache.spark.deploy.k8s.features.MountVolumesFeatureStep.configurePod(MountVolumesFeatureStep.scala:35)
> at
> org.apache.spark.scheduler.cluster.k8s.KubernetesExecutorBuilder.$anonfun$buildFromFeatures$5(KubernetesExecutorBuilder.scala:83)
> at
> scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
> at
> scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
> at scala.collection.immutable.List.foldLeft(List.scala:91) at
> org.apache.spark.scheduler.cluster.k8s.KubernetesExecutorBuilder.buildFromFeatures(KubernetesExecutorBuilder.scala:82)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$requestNewExecutors$1(ExecutorPodsAllocator.scala:430)
> at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:158)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.requestNewExecutors(ExecutorPodsAllocator.scala:417)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$onNewSnapshots$36(ExecutorPodsAllocator.scala:370)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$onNewSnapshots$36$adapted(ExecutorPodsAllocator.scala:363)
> at
> scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at
> scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.onNewSnapshots(ExecutorPodsAllocator.scala:363)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$start$3(ExecutorPodsAllocator.scala:134)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$start$3$adapted(ExecutorPodsAllocator.scala:134)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber.org$apache$spark$scheduler$cluster$k8s$ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber$$processSnapshotsInternal(ExecutorPodsSnapshotsStoreImpl.scala:143)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl$SnapshotsSubscriber.processSnapshots(ExecutorPodsSnapshotsStoreImpl.scala:131)
> at
> org.apache.spark.scheduler.cluster.k8s.ExecutorPodsSnapshotsStoreImpl.$anonfun$addSubscriber$1(ExecutorPodsSnapshotsStoreImpl.scala:85)
> at
> java.base/java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:539)
> at
> java.base/java.util.concurrent.FutureTask.runAndReset(FutureTask.java:305)
> at
> java.base/java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:305)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
> at java.base/java.lang.Thread.run(Thread.java:833) {code}
> How to reproduce:
> # Create statically provisioned PV, for example nfs PV:
> [https://kubernetes.io/docs/concepts/storage/volumes/#nfs]
> # Create PVC that binds to PV above.
> # Run Spark PI example: $SPARK_HOME/bin/spark-submit --master
> k8s://kubernetes.default.svc --properties-file spark.properties
> $SPARK_HOME/examples/src/main/python/pi.py 10
> spark.properties contents:
> {code:java}
> spark.executor.instances=5
> spark.kubernetes.executor.volumes.persistentVolumeClaim.nfs1.mount.path=/isilon/mnts
> spark.kubernetes.executor.volumes.persistentVolumeClaim.nfs1.mount.readOnly=false
> spark.kubernetes.executor.volumes.persistentVolumeClaim.nfs1.options.claimName=a1pvc
> spark.kubernetes.driver.volumes.persistentVolumeClaim.nfs1.options.claimName=a1pvc
> spark.kubernetes.driver.volumes.persistentVolumeClaim.nfs1.mount.readOnly=false
> spark.kubernetes.driver.volumes.persistentVolumeClaim.nfs1.mount.path=/isilon/mnts
> {code}
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