Databricks v1.14.0, May 23 23

databricks.MlflowExperiment

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This resource allows you to manage MLflow experiments in Databricks.

Access Control

databricks.Permissions can control which groups or individual users can Read, Edit, or Manage individual experiments.

The following resources are often used in the same context:

End to end workspace management guide.
databricks.Directory to manage directories in Databricks Workpace.
databricks.MlflowModel to create MLflow models in Databricks.
databricks.Notebook to manage Databricks Notebooks.
databricks.Notebook data to export a notebook from Databricks Workspace.
databricks.Repo to manage Databricks Repos.

Example Usage

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var me = Databricks.GetCurrentUser.Invoke();

    var @this = new Databricks.MlflowExperiment("this", new()
    {
        ArtifactLocation = "dbfs:/tmp/my-experiment",
        Description = "My MLflow experiment description",
    });

});

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := databricks.GetCurrentUser(ctx, nil, nil)
		if err != nil {
			return err
		}
		_, err = databricks.NewMlflowExperiment(ctx, "this", &databricks.MlflowExperimentArgs{
			ArtifactLocation: pulumi.String("dbfs:/tmp/my-experiment"),
			Description:      pulumi.String("My MLflow experiment description"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.DatabricksFunctions;
import com.pulumi.databricks.MlflowExperiment;
import com.pulumi.databricks.MlflowExperimentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        final var me = DatabricksFunctions.getCurrentUser();

        var this_ = new MlflowExperiment("this", MlflowExperimentArgs.builder()        
            .artifactLocation("dbfs:/tmp/my-experiment")
            .description("My MLflow experiment description")
            .build());

    }
}

import pulumi
import pulumi_databricks as databricks

me = databricks.get_current_user()
this = databricks.MlflowExperiment("this",
    artifact_location="dbfs:/tmp/my-experiment",
    description="My MLflow experiment description")

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const me = databricks.getCurrentUser({});
const _this = new databricks.MlflowExperiment("this", {
    artifactLocation: "dbfs:/tmp/my-experiment",
    description: "My MLflow experiment description",
});

resources:
  this:
    type: databricks:MlflowExperiment
    properties:
      artifactLocation: dbfs:/tmp/my-experiment
      description: My MLflow experiment description
variables:
  me:
    fn::invoke:
      Function: databricks:getCurrentUser
      Arguments: {}

Create MlflowExperiment Resource

new MlflowExperiment(name: string, args?: MlflowExperimentArgs, opts?: CustomResourceOptions);

@overload
def MlflowExperiment(resource_name: str,
                     opts: Optional[ResourceOptions] = None,
                     artifact_location: Optional[str] = None,
                     creation_time: Optional[int] = None,
                     description: Optional[str] = None,
                     experiment_id: Optional[str] = None,
                     last_update_time: Optional[int] = None,
                     lifecycle_stage: Optional[str] = None,
                     name: Optional[str] = None)
@overload
def MlflowExperiment(resource_name: str,
                     args: Optional[MlflowExperimentArgs] = None,
                     opts: Optional[ResourceOptions] = None)

func NewMlflowExperiment(ctx *Context, name string, args *MlflowExperimentArgs, opts ...ResourceOption) (*MlflowExperiment, error)

public MlflowExperiment(string name, MlflowExperimentArgs? args = null, CustomResourceOptions? opts = null)

public MlflowExperiment(String name, MlflowExperimentArgs args)
public MlflowExperiment(String name, MlflowExperimentArgs args, CustomResourceOptions options)

type: databricks:MlflowExperiment
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

name string: The unique name of the resource.
args MlflowExperimentArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args MlflowExperimentArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args MlflowExperimentArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args MlflowExperimentArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args MlflowExperimentArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

MlflowExperiment Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

The MlflowExperiment resource accepts the following input properties:

ArtifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
CreationTime int
Description string: The description of the MLflow experiment.
ExperimentId string
LastUpdateTime int
LifecycleStage string
Name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

ArtifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
CreationTime int
Description string: The description of the MLflow experiment.
ExperimentId string
LastUpdateTime int
LifecycleStage string
Name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation String: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime Integer
description String: The description of the MLflow experiment.
experimentId String
lastUpdateTime Integer
lifecycleStage String
name String: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime number
description string: The description of the MLflow experiment.
experimentId string
lastUpdateTime number
lifecycleStage string
name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifact_location str: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creation_time int
description str: The description of the MLflow experiment.
experiment_id str
last_update_time int
lifecycle_stage str
name str: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation String: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime Number
description String: The description of the MLflow experiment.
experimentId String
lastUpdateTime Number
lifecycleStage String
name String: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

Outputs

All input properties are implicitly available as output properties. Additionally, the MlflowExperiment resource produces the following output properties:

Id string: The provider-assigned unique ID for this managed resource.

Id string: The provider-assigned unique ID for this managed resource.

id String: The provider-assigned unique ID for this managed resource.

id string: The provider-assigned unique ID for this managed resource.

id str: The provider-assigned unique ID for this managed resource.

id String: The provider-assigned unique ID for this managed resource.

Look up Existing MlflowExperiment Resource

Get an existing MlflowExperiment resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: MlflowExperimentState, opts?: CustomResourceOptions): MlflowExperiment

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        artifact_location: Optional[str] = None,
        creation_time: Optional[int] = None,
        description: Optional[str] = None,
        experiment_id: Optional[str] = None,
        last_update_time: Optional[int] = None,
        lifecycle_stage: Optional[str] = None,
        name: Optional[str] = None) -> MlflowExperiment

func GetMlflowExperiment(ctx *Context, name string, id IDInput, state *MlflowExperimentState, opts ...ResourceOption) (*MlflowExperiment, error)

public static MlflowExperiment Get(string name, Input<string> id, MlflowExperimentState? state, CustomResourceOptions? opts = null)

public static MlflowExperiment get(String name, Output<String> id, MlflowExperimentState state, CustomResourceOptions options)

Resource lookup is not supported in YAML

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

resource_name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

The following state arguments are supported:

ArtifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
CreationTime int
Description string: The description of the MLflow experiment.
ExperimentId string
LastUpdateTime int
LifecycleStage string
Name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

ArtifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
CreationTime int
Description string: The description of the MLflow experiment.
ExperimentId string
LastUpdateTime int
LifecycleStage string
Name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation String: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime Integer
description String: The description of the MLflow experiment.
experimentId String
lastUpdateTime Integer
lifecycleStage String
name String: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation string: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime number
description string: The description of the MLflow experiment.
experimentId string
lastUpdateTime number
lifecycleStage string
name string: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifact_location str: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creation_time int
description str: The description of the MLflow experiment.
experiment_id str
last_update_time int
lifecycle_stage str
name str: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

artifactLocation String: Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
creationTime Number
description String: The description of the MLflow experiment.
experimentId String
lastUpdateTime Number
lifecycleStage String
name String: Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs.

Import

The experiment resource can be imported using the id of the experiment bash

 $ pulumi import databricks:index/mlflowExperiment:MlflowExperiment this <experiment-id>

Package Details

Repository: databricks pulumi/pulumi-databricks
License: Apache-2.0
Notes: This Pulumi package is based on the databricks Terraform Provider.