This is an automated email from the ASF dual-hosted git repository.

dongjoon-hyun pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/spark.git


The following commit(s) were added to refs/heads/master by this push:
     new 0700340fa6fc [SPARK-58334][K8S][DOC] Introduce Apache Spark K8s 
Operator in `running-on-kubernetes.md`
0700340fa6fc is described below

commit 0700340fa6fc54f1f625b49503c205eab44394eb
Author: Dongjoon Hyun <[email protected]>
AuthorDate: Fri Jul 24 17:30:46 2026 -0700

    [SPARK-58334][K8S][DOC] Introduce Apache Spark K8s Operator in 
`running-on-kubernetes.md`
    
    ### What changes were proposed in this pull request?
    
    This PR aims to introduce `Apache Spark Kubernetes Operator` in 
`running-on-kubernetes.md` by adding a short section after `How it works` 
section.
    
    - What the operator is: a separate Apache Spark project that deploys and 
manages Spark
      workloads declaratively via `SparkApp` and `SparkCluster` custom 
resources.
    - Its relationship with the `spark-submit` based submission covered by this 
document:
      the two approaches are complementary and the operator runs on top of the 
same native
      Kubernetes scheduler backend.
    - Links to the operator repository and examples, consistent with the 
existing links in
      `docs/index.md`.
    
    ### Why are the changes needed?
    
    `Apache Spark Kubernetes Operator` v1.0.0 is going to be released Tomorrow. 
Currently, it is only mentioned in `docs/index.md`. Users who land directly on 
`running-on-kubernetes.md`, the main documentation page for running Spark on 
Kubernetes, have no way to discover the operator. This closes that 
discoverability gap while keeping the detailed operator usage out of scope 
(deferred to the operator repository).
    
    ### Does this PR introduce _any_ user-facing change?
    
    No. This is a documentation-only change.
    
    ### How was this patch tested?
    
    Manually check.
    
    ### Was this patch authored or co-authored using generative AI tooling?
    
    Generated-by: Claude Fable 5
    
    Closes #57512 from dongjoon-hyun/SPARK-58334.
    
    Authored-by: Dongjoon Hyun <[email protected]>
    Signed-off-by: Dongjoon Hyun <[email protected]>
---
 docs/running-on-kubernetes.md | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/docs/running-on-kubernetes.md b/docs/running-on-kubernetes.md
index 23bc44c46751..af730de8a517 100644
--- a/docs/running-on-kubernetes.md
+++ b/docs/running-on-kubernetes.md
@@ -80,6 +80,20 @@ driver and executor pods on a subset of available nodes 
through a [node selector
 using the configuration property for it. It will be possible to use more 
advanced
 scheduling hints like [node/pod 
affinities](https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity)
 in a future release.
 
+# Spark Kubernetes Operator
+
+In addition to the `spark-submit` based submission described in this document, 
users can deploy and
+manage Spark workloads declaratively via [operator 
patterns](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/)
+by using [Apache Spark Kubernetes 
Operator](https://github.com/apache/spark-kubernetes-operator),
+a separate Apache Spark project. The operator provides two custom resources:
+
+* 
[SparkApp](https://github.com/apache/spark-kubernetes-operator/blob/main/examples/pi-python.yaml):
 deploy Spark apps on top of Kubernetes
+* 
[SparkCluster](https://github.com/apache/spark-kubernetes-operator/blob/main/examples/cluster.yaml):
 deploy Spark clusters on top of Kubernetes
+
+The two approaches are complementary because the operator runs Spark 
applications on top of the same
+native Kubernetes scheduler backend described in this document. Please refer 
to the operator
+repository for its detailed documentation and usage.
+
 # Submitting Applications to Kubernetes
 
 ## Docker Images


---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to