Lucca Sergi created SPARK-46310:
-----------------------------------
Summary: Cannot deploy Spark application using VolcanoFeatureStep
to specify podGroupTemplate file
Key: SPARK-46310
URL: https://issues.apache.org/jira/browse/SPARK-46310
Project: Spark
Issue Type: Bug
Components: Kubernetes
Affects Versions: 3.4.1
Reporter: Lucca Sergi
I'm trying to deploy a Spark application (version 3.4.1) on Kubernetes using
Volcano as the scheduler. I define a VolcanoJob that represents the Spark
driver - it has only one task, whose pod specification includes the driver
container, which invokes the spark-submit command.
Following the official Spark documentation (available on "[Using Volcano as
Customized Scheduler for Spark on
Kubernetes|https://spark.apache.org/docs/latest/running-on-kubernetes.html#using-volcano-as-customized-scheduler-for-spark-on-kubernetes]";),
I define the necessary configuration parameters to make use of Volcano as the
scheduler for my Spark workload:
{code:java}
/opt/spark/bin/spark-submit --name "volcano-spark-1" --deploy-mode="client" \
--class "org.apache.spark.examples.SparkPi" \
--conf spark.executor.instances="1" \
--conf
spark.kubernetes.driver.pod.featureSteps="org.apache.spark.deploy.k8s.features.VolcanoFeatureStep"
\
--conf
spark.kubernetes.executor.pod.featureSteps="org.apache.spark.deploy.k8s.features.VolcanoFeatureStep"
\
--conf
spark.kubernetes.scheduler.volcano.podGroupTemplateFile="/var/template/podgroup.yaml"
\
file:///opt/spark/examples/jars/spark-examples_2.12-3.4.1.jar
{code}
In the block above, I omitted some Kubernetes configuration parameters that
aren't important for this example. The parameter
*{{spark.kubernetes.scheduler.volcano.podGroupTemplateFile}}* points to a file
mounted in the driver container. It has a content as follows:
{code:yaml}
apiVersion: scheduling.volcano.sh/v1beta1
kind: PodGroup
metadata:
name: pod-group-test
spec:
minResources:
cpu: "2"
memory: "2Gi"
queue: some-existing-queue
{code}
I manually verified that this file "/var/template/podgroup.yaml" exists in the
container before the "spark-submit" command is issued. I also granted all the
necessary RBAC permissions so that the driver pod can interact with Kubernetes
objects (pods, VolcanoJobs, podgroups, queues, etc.).
When I execute this VolcanoJob, I see only the driver pod being created, and
when inspecting its logs, I see the following error:
{code:java}
io.fabric8.kubernetes.client.KubernetesClientException: Failure executing: POST
at:
https://api.<masked-environment-endpoint>/api/v1/namespaces/04522055-15b3-40d8-ba07-22b1a2a5ffcc/pods.
Message: admission webhook "validatepod.volcano.sh" denied the request: failed
to get PodGroup for pod
<04522055-15b3-40d8-ba07-22b1a2a5ffcc/volcano-spark-1-driver-0-exec-789>:
podgroups.scheduling.volcano.sh
"spark-5ad570e340934d3997065fa6d504910e-podgroup" not found. Received status:
Status(apiVersion=v1, code=400, details=null, kind=Status, message=admission
webhook "validatepod.volcano.sh" denied the request: failed to get PodGroup for
pod <04522055-15b3-40d8-ba07-22b1a2a5ffcc/volcano-spark-1-driver-0-exec-789>:
podgroups.scheduling.volcano.sh
"spark-5ad570e340934d3997065fa6d504910e-podgroup" not found,
metadata=ListMeta(_continue=null, remainingItemCount=null,
resourceVersion=null, selfLink=null, additionalProperties={}), reason=null,
status=Failure, additionalProperties={}).
at
io.fabric8.kubernetes.client.KubernetesClientException.copyAsCause(KubernetesClientException.java:238)
at
io.fabric8.kubernetes.client.dsl.internal.OperationSupport.waitForResult(OperationSupport.java:538)
at
io.fabric8.kubernetes.client.dsl.internal.OperationSupport.handleResponse(OperationSupport.java:558)
at
io.fabric8.kubernetes.client.dsl.internal.OperationSupport.handleCreate(OperationSupport.java:349)
at
io.fabric8.kubernetes.client.dsl.internal.BaseOperation.handleCreate(BaseOperation.java:711)
at
io.fabric8.kubernetes.client.dsl.internal.BaseOperation.handleCreate(BaseOperation.java:93)
at
io.fabric8.kubernetes.client.dsl.internal.CreateOnlyResourceOperation.create(CreateOnlyResourceOperation.java:42)
at
io.fabric8.kubernetes.client.dsl.internal.BaseOperation.create(BaseOperation.java:1113)
at
io.fabric8.kubernetes.client.dsl.internal.BaseOperation.create(BaseOperation.java:93)
at
org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$requestNewExecutors$1(ExecutorPodsAllocator.scala:440)
at scala.collection.immutable.Range.foreach$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$1(ExecutorPodsSnapshotsStoreImpl.scala:85)
at
java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:182)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:296)
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:838)
{code}
The error seems to be triggered when the driver attempts to deploy the
executors of my Spark application. In the error message, it says that the
podGroup "spark-5ad570e340934d3997065fa6d504910e-podgroup" cannot be found
(pointed out by the Volcano admission hook).
I was expecting that the driver and executors would be assigned to the same
PodGroup object, created by the VolcanoFeatureStep using the template file that
I provided through the configuration parameter
"{*}{{spark.kubernetes.scheduler.volcano.podGroupTemplateFile}}{*}". With that,
I would have a proper batch scheduling of my Spark application, as driver and
executor pods would reside in the same pod group, and would be scheduled
together by Volcano. But instead, only the driver pod is deployed, and the
error seen above is found on its logs.
The documentation "[Using Volcano as Customized Scheduler for Spark on
Kubernetes|https://spark.apache.org/docs/latest/running-on-kubernetes.html#using-volcano-as-customized-scheduler-for-spark-on-kubernetes]";
leads me to understand that by providing the PodGroup template file, my Spark
application (i.e., driver and executors) would be allocated in the same
PodGroup object, following the specification I provided. That doesn't seem to
be the case, and it looks like the PodGroup isn't created following the
provided template, nor can the executors be created.
Some more details about the environment I used:
- Volcano Version: v1.8.0
- Spark Version: 3.4.1
- Kubernetes version: v1.26.7
- Cloud provider: GCP
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