chore(spark): align e2e harness with upstream Helm chart defaults

.github/workflows/test-spark-examples.yaml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        kubernetes-version: ["1.32.0"]
+        kubernetes-version: ["1.32.11", "1.33.7", "1.34.3", "1.35.0"]
 
     steps:
       - name: Free disk space (Ubuntu runner)
@@ -48,46 +48,26 @@ jobs:
           curl -Lo ./kubectl "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl" && chmod +x ./kubectl && sudo mv ./kubectl /usr/local/bin/kubectl
           curl -sSfL https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash
 
-      - name: Checkout spark-operator
-        uses: actions/checkout@v6
-        with:
-          repository: kubeflow/spark-operator
-          path: spark-operator
-          fetch-depth: 1
-
-      - name: Build Spark Operator image
-        run: |
-          docker build -t ghcr.io/kubeflow/spark-operator/controller:local ./spark-operator
-        timeout-minutes: 10
-
       - name: Setup Kind cluster with Spark Operator
         run: |
           make test-e2e-setup-cluster K8S_VERSION=${{ matrix.kubernetes-version }}
         env:
           SPARK_TEST_CLUSTER: spark-test
           SPARK_TEST_NAMESPACE: spark-test
-          SPARK_OPERATOR_IMAGE_TAG: local
         timeout-minutes: 15
 
-      - name: Build and load Spark E2E runner image (in-cluster)
-        run: |
-          docker build -f hack/Dockerfile.spark-e2e-runner -t spark-e2e-runner:local .
-          kind load docker-image spark-e2e-runner:local --name spark-test
-        timeout-minutes: 5
-
       - name: Run example validation tests
         run: uv run pytest test/e2e/spark/test_spark_examples.py -v --tb=short
         env:
           SPARK_TEST_CLUSTER: spark-test
           SPARK_TEST_NAMESPACE: spark-test
           SPARK_E2E_DEBUG: "1"
-          SPARK_E2E_RUN_IN_CLUSTER: "1"
-          SPARK_E2E_RUNNER_IMAGE: spark-e2e-runner:local
         timeout-minutes: 15
 
       - name: Collect logs on failure
         if: failure()
         run: |
           kubectl get pods -n spark-test
           kubectl get sparkconnect -n spark-test 2>/dev/null || true
+          kubectl get sparkapplication -n spark-test 2>/dev/null || true
           kubectl logs -n spark-test -l app.kubernetes.io/component=server --tail=100 || true

examples/spark/README.md

@@ -16,7 +16,6 @@ For the full documentation, see [Interactive Sessions](https://sdk.kubeflow.org/
 - **spark_connect_simple.py** - Basic SparkClient usage with simple API
 - **spark_advanced_options.py** - Advanced configuration with Driver/Executor objects
 - **demo_existing_sparkconnect.py** - Connect to existing SparkConnect cluster
-- **connect_existing_session.py** - Connect to an existing Spark Connect session through `base_url`
 - **test_connect_url.py** - Test URL-based connection to Spark Connect
 
 ### Batch Jobs