Git hooks are useful for identifying simple issues before submission to code review. We run hooks on every commit to automatically generate helm chart README.md
file from README.md.gotmpl
file. Before you can run git hooks, you need to have the pre-commit package manager installed as follows:
# Using pip
pip install pre-commit
# Using conda
conda install -c conda-forge pre-commit
# Using Homebrew
brew install pre-commit
To set up the pre-commit hooks, run the following command:
pre-commit install
pre-commit install-hooks
In case you want to build the operator from the source code, e.g., to test a fix or a feature you write, you can do so following the instructions below.
The easiest way to build the operator without worrying about its dependencies is to just build an image using the Dockerfile.
docker build -t <image-tag> .
The operator image is built upon a base Spark image that defaults to spark:3.5.0
. If you want to use your own Spark image (e.g., an image with a different version of Spark or some custom dependencies), specify the argument SPARK_IMAGE
as the following example shows:
docker build --build-arg SPARK_IMAGE=<your Spark image> -t <image-tag> .
If you want to use the operator on OpenShift clusters, first make sure you have Docker version 18.09.3 or above, then build your operator image using the OpenShift-specific Dockerfile.
export DOCKER_BUILDKIT=1
docker build -t <image-tag> -f Dockerfile.rh .
If you'd like to build/test the spark-operator locally, follow the instructions below:
mkdir -p $GOPATH/src/github.com/kubeflow
cd $GOPATH/src/github.com/kubeflow
git clone [email protected]:kubeflow/spark-operator.git
cd spark-operator
To update the auto-generated code, run the following command. (This step is only required if the CRD types have been changed):
hack/update-codegen.sh
To update the auto-generated CRD definitions, run the following command. After doing so, you must update the list of required fields under each ports
field to add the protocol
field to the list. Skipping this step will make the CRDs incompatible with Kubernetes v1.18+.
GO111MODULE=off go get -u sigs.k8s.io/controller-tools/cmd/controller-gen
controller-gen crd:trivialVersions=true,maxDescLen=0,crdVersions=v1beta1 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:
hack/verify-codegen.sh
To build the operator, run the following command:
GOOS=linux go build -o spark-operator
To run unit tests, run the following command:
go test ./...
When you update the API, or specifically the SparkApplication
and ScheduledSparkApplication
specifications, the API specification doc needs to be updated. To update the API specification doc, run the following command:
make build-api-docs
Running the above command will update the file docs/api-docs.md
.
$ make helm-lint
Linting charts...
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Charts to be processed:
------------------------------------------------------------------------------------------------------------------------
spark-operator => (version: "1.2.4", path: "charts/spark-operator-chart")
------------------------------------------------------------------------------------------------------------------------
Linting chart "spark-operator => (version: \"1.2.4\", path: \"charts/spark-operator-chart\")"
Checking chart "spark-operator => (version: \"1.2.4\", path: \"charts/spark-operator-chart\")" for a version bump...
Old chart version: 1.2.1
New chart version: 1.2.4
Chart version ok.
Validating /Users/user/go/src/github.com/kubeflow/spark-operator/charts/spark-operator-chart/Chart.yaml...
Validation success! 👍
Validating maintainers...
Linting chart with values file "charts/spark-operator-chart/ci/ci-values.yaml"...
==> Linting charts/spark-operator-chart
[INFO] Chart.yaml: icon is recommended
1 chart(s) linted, 0 chart(s) failed
------------------------------------------------------------------------------------------------------------------------
✔︎ spark-operator => (version: "1.2.4", path: "charts/spark-operator-chart")
------------------------------------------------------------------------------------------------------------------------
All charts linted successfully
First, you need to install helm chart unit test plugin as follows:
helm plugin install https://github.com/helm-unittest/helm-unittest.git
For more information about how to write helm chart unit tests, please refer to helm-unittest.
Then, run make helm-unittest
to run the helm chart unit tests:
$ make helm-unittest
### Chart [ spark-operator ] charts/spark-operator-chart
PASS Test spark operator deployment charts/spark-operator-chart/tests/deployment_test.yaml
PASS Test spark operator rbac charts/spark-operator-chart/tests/rbac_test.yaml
PASS Test spark operator service account charts/spark-operator-chart/tests/serviceaccount_test.yaml
PASS Test spark rbac charts/spark-operator-chart/tests/spark-rbac_test.yaml
PASS Test spark service account charts/spark-operator-chart/tests/spark-serviceaccount_test.yaml
PASS Test spark operator webhook service charts/spark-operator-chart/tests/webhook-service_test.yaml
Charts: 1 passed, 1 total
Test Suites: 6 passed, 6 total
Tests: 46 passed, 46 total
Snapshot: 0 passed, 0 total
Time: 107.861083ms
The Helm chart README.md
file is generated by helm-docs tool. If you want to update the Helm docs, remember to modify README.md.gotmpl
rather than README.md
, then run make helm-docs
to generate the README.md
file:
$ make helm-docs
INFO[2024-04-14T07:29:26Z] Found Chart directories [charts/spark-operator-chart]
INFO[2024-04-14T07:29:26Z] Generating README Documentation for chart charts/spark-operator-chart
Note that if git pre-commit hooks are set up, helm-docs
will automatically run before committing any changes. If there are any changes to the README.md
file, the commit process will be aborted.