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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2023/05/07 01:28:00 UTC
[jira] [Resolved] (SPARK-43342) Spark in Kubernetes mode throws IllegalArgumentException when using static PVC
[ https://issues.apache.org/jira/browse/SPARK-43342?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun resolved SPARK-43342.
-----------------------------------
Fix Version/s: 3.4.1
Resolution: Fixed
Issue resolved by pull request 41069
[https://github.com/apache/spark/pull/41069]
> Spark in Kubernetes mode throws IllegalArgumentException when using static PVC
> ------------------------------------------------------------------------------
>
> 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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