Generate CRD specs, bump to v1beta2

README.md

@@ -14,7 +14,7 @@
 
 The Kubernetes Operator for Apache Spark is under active development, but backward compatibility of the APIs is guaranteed for beta releases. 
 
-**If you are currently using the `v1alpha1` version of the APIs in your manifests, please update them to use the `v1beta1` version by changing `apiVersion: "sparkoperator.k8s.io/v1alpha1"` to `apiVersion: "sparkoperator.k8s.io/v1beta1"`. You will also need to delete the `v1alpha1` version of the CustomResourceDefinitions named `sparkapplications.sparkoperator.k8s.io` and `scheduledsparkapplications.sparkoperator.k8s.io`, and replace them with the `v1beta1` version either by installing the latest version of the operator or by running `kubectl create -f manifest/spark-operator-crds.yaml`.**
+**If you are currently using the `v1alpha1` or `v1beta1` version of the APIs in your manifests, please update them to use the `v1beta2` version by changing `apiVersion: "sparkoperator.k8s.io/<version>"` to `apiVersion: "sparkoperator.k8s.io/v1beta2"`. You will also need to delete the `previous` version of the CustomResourceDefinitions named `sparkapplications.sparkoperator.k8s.io` and `scheduledsparkapplications.sparkoperator.k8s.io`, and replace them with the `v1beta2` version either by installing the latest version of the operator or by running `kubectl create -f manifest/crds`.**
 
 Customization of Spark pods, e.g., mounting arbitrary volumes and setting pod affinity, is currently experimental and implemented using a Kubernetes
 [Mutating Admission Webhook](https://kubernetes.io/docs/reference/access-authn-authz/extensible-admission-controllers/), which became beta in Kubernetes 1.9. 

docs/api.md

@@ -1,7 +1,7 @@
 # SparkApplication API
 
 The Kubernetes Operator for Apache Spark uses  [CustomResourceDefinitions](https://kubernetes.io/docs/concepts/api-extension/custom-resources/) named `SparkApplication` and `ScheduledSparkApplication` for specifying one-time Spark applications and Spark applications
-that are supposed to run on a standard [cron](https://en.wikipedia.org/wiki/Cron) schedule. Similarly to other kinds of Kubernetes resources, they consist of a specification in a `Spec` field and a `Status` field. The definitions are organized in the following structure. The v1beta1 version of the API definition is implemented [here](../pkg/apis/sparkoperator.k8s.io/v1beta1/types.go).
+that are supposed to run on a standard [cron](https://en.wikipedia.org/wiki/Cron) schedule. Similarly to other kinds of Kubernetes resources, they consist of a specification in a `Spec` field and a `Status` field. The definitions are organized in the following structure. The v1beta2 version of the API definition is implemented [here](../pkg/apis/sparkoperator.k8s.io/v1beta2/types.go).
 
 ```
 ScheduledSparkApplication

docs/developer-guide.md

@@ -51,6 +51,7 @@ Before building the operator the first time, run the following commands to get t
 $ go get -u k8s.io/code-generator/cmd/client-gen
 $ go get -u k8s.io/code-generator/cmd/deepcopy-gen
 $ go get -u k8s.io/code-generator/cmd/defaulter-gen
+$ go get -u sigs.k8s.io/controller-tools/cmd/contoller-gen
 ```
 
 To update the auto-generated code, run the following command. (This step is only required if the CRD types have been changed):
@@ -59,6 +60,12 @@ To update the auto-generated code, run the following command. (This step is only
 $ go generate
 ```
 
+To update the auto-generated CRD definitions, run the following command:
+
+```bash
+$ controller-gen crd:trivialVersions=true,maxDescLen=0 paths="./pkg/apis/sparkoperator.k8s.io/v1beta2" output:crd:artifacts:config=./manifest/crds/
+```
+
 You can verify the current auto-generated code is up to date with:
 
 ```bash

docs/gcp.md

@@ -43,7 +43,7 @@ The ones set in `core-site.xml` apply to all applications using the image. Also
 variable `GCS_PROJECT_ID` must be set when using the image at `gcr.io/ynli-k8s/spark:v2.3.0-gcs`.
 
 ```yaml
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: foo-gcs-bg
@@ -58,7 +58,7 @@ spec:
     "google.cloud.auth.service.account.enable": "true"
     "google.cloud.auth.service.account.json.keyfile": "/mnt/secrets/key.json"
   driver:
-    cores: 0.1
+    cores: 1
     secrets:
     - name: "gcs-bq"
       path: "/mnt/secrets"

docs/quick-start-guide.md

@@ -69,15 +69,15 @@ $ kubectl get sparkapplications spark-pi -o=yaml
 This will show something similar to the following:
 
 ```yaml
-apiVersion: sparkoperator.k8s.io/v1beta1
+apiVersion: sparkoperator.k8s.io/v1beta2
 kind: SparkApplication
 metadata:
   ...
 spec:
   deps: {}
   driver:
-    coreLimit: 200m
-    cores: 0.1
+    coreLimit: 1200m
+    cores: 1
     labels:
       version: 2.3.0
     memory: 512m

docs/user-guide.md

@@ -55,7 +55,7 @@ It also has fields for specifying the unified container image (to use for both t
 Below is an example showing part of a `SparkApplication` specification:
 
 ```yaml
-apiVersion: sparkoperator.k8s.io/v1beta1
+apiVersion: sparkoperator.k8s.io/v1beta2
 kind: SparkApplication
 metadata:
   name: spark-pi
@@ -125,7 +125,7 @@ The following is an example driver specification:
 ```yaml
 spec:
   driver:
-    cores: 0.1
+    cores: 1
     coreLimit: 200m
     memory: 512m
     labels:
@@ -514,7 +514,7 @@ client so effectively the driver gets restarted.
 The operator supports running a Spark application on a standard [cron](https://en.wikipedia.org/wiki/Cron) schedule using objects of the `ScheduledSparkApplication` custom resource type. A `ScheduledSparkApplication` object specifies a cron schedule on which the application should run and a `SparkApplication` template from which a `SparkApplication` object for each run of the application is created. The following is an example `ScheduledSparkApplication`:
 
 ```yaml
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: ScheduledSparkApplication
 metadata:
   name: spark-pi-scheduled
@@ -531,7 +531,7 @@ spec:
     mainClass: org.apache.spark.examples.SparkPi
     mainApplicationFile: local:///opt/spark/examples/jars/spark-examples_2.11-2.3.0.jar
     driver:
-      cores: 0.5
+      cores: 1
       memory: 512m
     executor:
       cores: 1

docs/volcano-integration.md

@@ -23,7 +23,7 @@ $ helm install incubator/sparkoperator --namespace spark-operator --set enableBa
 
 Now, we can run a updated version of spark application (with `batchScheduler` configured), for instance:
 ```yaml
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: spark-pi
@@ -45,8 +45,8 @@ spec:
         path: "/tmp"
         type: Directory
   driver:
-    cores: 0.1
-    coreLimit: "200m"
+    cores: 1
+    coreLimit: "1200m"
     memory: "512m"        
     labels:
       version: 2.4.0

examples/spark-pi-configmap.yaml

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: spark-pi
@@ -33,8 +33,8 @@ spec:
       configMap:
         name: dummy-cm
   driver:
-    cores: 0.1
-    coreLimit: "200m"
+    cores: 1
+    coreLimit: "1200m"
     memory: "512m"
     labels:
       version: 2.4.0

examples/spark-pi-prometheus.yaml

@@ -14,7 +14,7 @@
 # limitations under the License.
 #
 
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: spark-pi
@@ -32,8 +32,8 @@ spec:
   restartPolicy:
     type: Never
   driver:
-    cores: 0.1
-    coreLimit: "200m"
+    cores: 1
+    coreLimit: "1200m"
     memory: "512m"
     labels:
       version: 2.4.0

examples/spark-pi-schedule.yaml

@@ -14,7 +14,7 @@
 # limitations under the License.
 #
 
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: ScheduledSparkApplication
 metadata:
   name: spark-pi-scheduled
@@ -32,8 +32,8 @@ spec:
     restartPolicy:
       type: Never
     driver:
-      cores: 0.1
-      coreLimit: "200m"
+      cores: 1
+      coreLimit: "1200m"
       memory: "512m"
       labels:
         version: 2.4.0

examples/spark-pi.yaml

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: spark-pi
@@ -34,8 +34,8 @@ spec:
         path: "/tmp"
         type: Directory
   driver:
-    cores: 0.1
-    coreLimit: "200m"
+    cores: 1
+    coreLimit: "1200m"
     memory: "512m"
     labels:
       version: 2.4.0

examples/spark-py-pi.yaml

@@ -16,7 +16,7 @@
 # Support for Python is experimental, and requires building SNAPSHOT image of Apache Spark,
 # with `imagePullPolicy` set to Always
 
-apiVersion: "sparkoperator.k8s.io/v1beta1"
+apiVersion: "sparkoperator.k8s.io/v1beta2"
 kind: SparkApplication
 metadata:
   name: pyspark-pi
@@ -36,8 +36,8 @@ spec:
     onSubmissionFailureRetries: 5
     onSubmissionFailureRetryInterval: 20
   driver:
-    cores: 0.1
-    coreLimit: "200m"
+    cores: 1
+    coreLimit: "1200m"
     memory: "512m"
     labels:
       version: 2.4.0

hack/update-codegen.sh

@@ -27,7 +27,7 @@ CODEGEN_PKG=${CODEGEN_PKG:-$(cd ${SCRIPT_ROOT}; ls -d -1 ./vendor/k8s.io/code-ge
 #                  instead of the $GOPATH directly. For normal projects this can be dropped.
 ${CODEGEN_PKG}/generate-groups.sh "all" \
   github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/client github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/apis \
-  sparkoperator.k8s.io:v1alpha1,v1beta1 \
+  sparkoperator.k8s.io:v1alpha1,v1beta1,v1beta2 \
   --go-header-file "$(dirname ${BASH_SOURCE})/custom-boilerplate.go.txt" \
   --output-base "$(dirname ${BASH_SOURCE})/../../../.."
 

main.go

@@ -48,7 +48,6 @@ import (
 	operatorConfig "github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/config"
 	"github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/controller/scheduledsparkapplication"
 	"github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/controller/sparkapplication"
-	"github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/crd"
 	"github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/util"
 	"github.com/GoogleCloudPlatform/spark-on-k8s-operator/pkg/webhook"
 )
@@ -155,13 +154,6 @@ func main() {
 		batchSchedulerMgr = batchscheduler.NewSchedulerManager(config)
 	}
 
-	if *installCRDs {
-		err = crd.CreateOrUpdateCRDs(apiExtensionsClient)
-		if err != nil {
-			glog.Fatal(err)
-		}
-	}
-
 	crInformerFactory := buildCustomResourceInformerFactory(crClient)
 	podInformerFactory := buildPodInformerFactory(kubeClient)