@pulumi/databricks
Version:
A Pulumi package for creating and managing databricks cloud resources.
140 lines • 7.61 kB
JavaScript
;
// *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
Object.defineProperty(exports, "__esModule", { value: true });
exports.getNodeTypeOutput = exports.getNodeType = void 0;
const pulumi = require("@pulumi/pulumi");
const utilities = require("./utilities");
/**
* > **Note** If you have a fully automated setup with workspaces created by databricks.MwsWorkspaces or azurerm_databricks_workspace, please make sure to add dependsOn attribute in order to prevent _default auth: cannot configure default credentials_ errors.
*
* Gets the smallest node type for databricks.Cluster that fits search criteria, like amount of RAM or number of cores. [AWS](https://databricks.com/product/aws-pricing/instance-types) or [Azure](https://azure.microsoft.com/en-us/pricing/details/databricks/). Internally data source fetches [node types](https://docs.databricks.com/dev-tools/api/latest/clusters.html#list-node-types) available per cloud, similar to executing `databricks clusters list-node-types`, and filters it to return the smallest possible node with criteria.
*
* > **Note** This is experimental functionality, which aims to simplify things. In case of wrong parameters given (e.g. `minGpus = 876`) or no nodes matching, data source will return cloud-default node type, even though it doesn't match search criteria specified by data source arguments: [i3.xlarge](https://aws.amazon.com/ec2/instance-types/i3/) for AWS or [Standard_D3_v2](https://docs.microsoft.com/en-us/azure/cloud-services/cloud-services-sizes-specs#dv2-series) for Azure.
*
* ## Example Usage
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as databricks from "@pulumi/databricks";
*
* const withGpu = databricks.getNodeType({
* localDisk: true,
* minCores: 16,
* gbPerCore: 1,
* minGpus: 1,
* });
* const gpuMl = databricks.getSparkVersion({
* gpu: true,
* ml: true,
* });
* const research = new databricks.Cluster("research", {
* clusterName: "Research Cluster",
* sparkVersion: gpuMl.then(gpuMl => gpuMl.id),
* nodeTypeId: withGpu.then(withGpu => withGpu.id),
* autoterminationMinutes: 20,
* autoscale: {
* minWorkers: 1,
* maxWorkers: 50,
* },
* });
* ```
*
* ## Related Resources
*
* The following resources are used in the same context:
*
* * End to end workspace management guide.
* * databricks.Cluster to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html).
* * databricks.ClusterPolicy to create a databricks.Cluster policy, which limits the ability to create clusters based on a set of rules.
* * databricks.InstancePool to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
* * databricks.Job to manage [Databricks Jobs](https://docs.databricks.com/jobs.html) to run non-interactive code in a databricks_cluster.
*/
function getNodeType(args, opts) {
args = args || {};
opts = pulumi.mergeOptions(utilities.resourceOptsDefaults(), opts || {});
return pulumi.runtime.invoke("databricks:index/getNodeType:getNodeType", {
"category": args.category,
"fleet": args.fleet,
"gbPerCore": args.gbPerCore,
"graviton": args.graviton,
"id": args.id,
"isIoCacheEnabled": args.isIoCacheEnabled,
"localDisk": args.localDisk,
"localDiskMinSize": args.localDiskMinSize,
"minCores": args.minCores,
"minGpus": args.minGpus,
"minMemoryGb": args.minMemoryGb,
"photonDriverCapable": args.photonDriverCapable,
"photonWorkerCapable": args.photonWorkerCapable,
"supportPortForwarding": args.supportPortForwarding,
}, opts);
}
exports.getNodeType = getNodeType;
/**
* > **Note** If you have a fully automated setup with workspaces created by databricks.MwsWorkspaces or azurerm_databricks_workspace, please make sure to add dependsOn attribute in order to prevent _default auth: cannot configure default credentials_ errors.
*
* Gets the smallest node type for databricks.Cluster that fits search criteria, like amount of RAM or number of cores. [AWS](https://databricks.com/product/aws-pricing/instance-types) or [Azure](https://azure.microsoft.com/en-us/pricing/details/databricks/). Internally data source fetches [node types](https://docs.databricks.com/dev-tools/api/latest/clusters.html#list-node-types) available per cloud, similar to executing `databricks clusters list-node-types`, and filters it to return the smallest possible node with criteria.
*
* > **Note** This is experimental functionality, which aims to simplify things. In case of wrong parameters given (e.g. `minGpus = 876`) or no nodes matching, data source will return cloud-default node type, even though it doesn't match search criteria specified by data source arguments: [i3.xlarge](https://aws.amazon.com/ec2/instance-types/i3/) for AWS or [Standard_D3_v2](https://docs.microsoft.com/en-us/azure/cloud-services/cloud-services-sizes-specs#dv2-series) for Azure.
*
* ## Example Usage
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as databricks from "@pulumi/databricks";
*
* const withGpu = databricks.getNodeType({
* localDisk: true,
* minCores: 16,
* gbPerCore: 1,
* minGpus: 1,
* });
* const gpuMl = databricks.getSparkVersion({
* gpu: true,
* ml: true,
* });
* const research = new databricks.Cluster("research", {
* clusterName: "Research Cluster",
* sparkVersion: gpuMl.then(gpuMl => gpuMl.id),
* nodeTypeId: withGpu.then(withGpu => withGpu.id),
* autoterminationMinutes: 20,
* autoscale: {
* minWorkers: 1,
* maxWorkers: 50,
* },
* });
* ```
*
* ## Related Resources
*
* The following resources are used in the same context:
*
* * End to end workspace management guide.
* * databricks.Cluster to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html).
* * databricks.ClusterPolicy to create a databricks.Cluster policy, which limits the ability to create clusters based on a set of rules.
* * databricks.InstancePool to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
* * databricks.Job to manage [Databricks Jobs](https://docs.databricks.com/jobs.html) to run non-interactive code in a databricks_cluster.
*/
function getNodeTypeOutput(args, opts) {
args = args || {};
opts = pulumi.mergeOptions(utilities.resourceOptsDefaults(), opts || {});
return pulumi.runtime.invokeOutput("databricks:index/getNodeType:getNodeType", {
"category": args.category,
"fleet": args.fleet,
"gbPerCore": args.gbPerCore,
"graviton": args.graviton,
"id": args.id,
"isIoCacheEnabled": args.isIoCacheEnabled,
"localDisk": args.localDisk,
"localDiskMinSize": args.localDiskMinSize,
"minCores": args.minCores,
"minGpus": args.minGpus,
"minMemoryGb": args.minMemoryGb,
"photonDriverCapable": args.photonDriverCapable,
"photonWorkerCapable": args.photonWorkerCapable,
"supportPortForwarding": args.supportPortForwarding,
}, opts);
}
exports.getNodeTypeOutput = getNodeTypeOutput;
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