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authorRajamohan Raj <rajamohan.raj@intel.com>2019-03-11 23:53:41 +0000
committerRajamohan Mohan Raj <rajamohan.raj@intel.com>2019-03-13 23:40:21 +0000
commitb94b8b3ff5f403d9460f97acb7c2a553a42498f7 (patch)
treeb0fd552f7a24bb6c2ff912fe338369cdd73be4a3 /vnfs/DAaaS/operator/charts/sparkoperator/README.md
parente8f7e027283f8630733fb423d834e7d828d0db11 (diff)
Helm charts for spark and hdfs
Tasks accomplished in this patch: https://jira.onap.org/browse/ONAPARC-445 - Create helm chart for Spark on K8S operator and add it to operator. https://jira.onap.org/browse/ONAPARC-446 - Create helm charts for HDFS https://jira.onap.org/browse/ONAPARC-447 - Create Spark application helm chart as part of application pacakge https://jira.onap.org/browse/ONAPARC-448 - Add Anaconda with tensorflow, keras, horovod support to Spark image Change-Id: Icb4adeaa8a0aa445614f91203d7793e4e4f304c1 Issue-ID: ONAPARC-391 Signed-off-by: Rajamohan Raj <rajamohan.raj@intel.com>
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+### Helm Chart for Spark Operator
+
+This is the Helm chart for the [Spark-on-Kubernetes Operator](https://github.com/GoogleCloudPlatform/spark-on-k8s-operator).
+
+#### Prerequisites
+
+The Operator requires Kubernetes version 1.8 and above because it relies on garbage collection of custom resources. If customization of driver and executor pods (through mounting custom ConfigMaps and volumes) is desired, then the [Mutating Admission Webhook](https://github.com/GoogleCloudPlatform/spark-on-k8s-operator/blob/master/docs/quick-start-guide.md#using-the-mutating-admission-webhook) needs to be enabled and it only became beta in Kubernetes 1.9.
+
+#### Installing the chart
+
+The chart can be installed by running:
+
+```bash
+$ helm repo add incubator http://storage.googleapis.com/kubernetes-charts-incubator
+$ helm install incubator/sparkoperator --namespace spark-operator
+```
+
+Note that you need to use the `--namespace` flag during `helm install` to specify in which namespace you want to install the operator. The namespace can be existing or not. When it's not available, Helm would take care of creating the namespace. Note that this namespace has no relation to the namespace where you would like to deploy Spark jobs (i.e. the setting `sparkJobNamespace` shown in the table below). They can be the same namespace or different ones.
+
+#### Configuration
+
+The following table lists the configurable parameters of the Spark operator chart and their default values.
+
+| Parameter | Description | Default |
+| ------------------------- | ------------------------------------------------------------ | -------------------------------------- |
+| `operatorImageName` | The name of the operator image | `gcr.io/spark-operator/spark-operator` |
+| `operatorVersion` | The version of the operator to install | `v2.4.0-v1beta1-latest` |
+| `imagePullPolicy` | Docker image pull policy | `IfNotPresent` |
+| `sparkJobNamespace` | K8s namespace where Spark jobs are to be deployed | `default` |
+| `enableWebhook` | Whether to enable mutating admission webhook | false |
+| `enableMetrics` | Whether to expose metrics to be scraped by Premetheus | true |
+| `controllerThreads` | Number of worker threads used by the SparkApplication controller | 10 |
+| `ingressUrlFormat` | Ingress URL format | "" |
+| `installCrds` | Whether to install CRDs | true |
+| `metricsPort` | Port for the metrics endpoint | 10254 |
+| `metricsEndpoint` | Metrics endpoint | "/metrics" |
+| `metricsPrefix` | Prefix for the metrics | "" |
+| `resyncInterval` | Informer resync interval in seconds | 30 |
+| `webhookPort` | Service port of the webhook server | 8080 |
+
+Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`.
+