experiments

Creates, updates, deletes, gets or lists an experiments resource.

Overview

Name	experiments
Type	Resource
Id	databricks_workspace.machinelearning.experiments

Fields

The following fields are returned by SELECT queries:

searchexperiments

Name	Datatype	Description
name	string
experiment_id	string
artifact_location	string
creation_time	integer
last_update_time	integer
lifecycle_stage	string
tags	array

listexperiments

Name	Datatype	Description
name	string
experiment_id	string
artifact_location	string
creation_time	integer
last_update_time	integer
lifecycle_stage	string
tags	array

getexperiment

Name	Datatype	Description
name	string
experiment_id	string
artifact_location	string
creation_time	integer
last_update_time	integer
lifecycle_stage	string
tags	array

getbyname

Name	Datatype	Description
name	string
experiment_id	string
artifact_location	string
creation_time	integer
last_update_time	integer
lifecycle_stage	string
tags	array

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
searchexperiments	select	deployment_name		Searches for experiments that satisfy specified search criteria.
listexperiments	select	deployment_name		Gets a list of all experiments.
getexperiment	select	deployment_name		Gets metadata for an experiment. This method works on deleted experiments.
getbyname	select	deployment_name		Gets metadata for an experiment.
createexperiment	insert	deployment_name		Creates an experiment with a name. Returns the ID of the newly created experiment. Validates that another experiment with the same name does not already exist and fails if another experiment with the same name already exists.
updateexperiment	update	deployment_name		Updates experiment metadata.
deleteexperiment	delete	deployment_name		Marks an experiment and associated metadata, runs, metrics, params, and tags for deletion. If the experiment uses FileStore, artifacts associated with experiment are also deleted.
restoreexperiment	exec	deployment_name		Restore an experiment marked for deletion. This also restores associated metadata, runs, metrics, params, and tags. If experiment uses FileStore, underlying artifacts associated with experiment are also restored.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
deployment_name	string	The Databricks Workspace Deployment Name (default: dbc-abcd0123-a1bc)

SELECT examples

searchexperiments

Searches for experiments that satisfy specified search criteria.

SELECT
name,
experiment_id,
artifact_location,
creation_time,
last_update_time,
lifecycle_stage,
tags
FROM databricks_workspace.machinelearning.experiments
WHERE deployment_name = '{{ deployment_name }}' -- required;

listexperiments

Gets a list of all experiments.

SELECT
name,
experiment_id,
artifact_location,
creation_time,
last_update_time,
lifecycle_stage,
tags
FROM databricks_workspace.machinelearning.experiments
WHERE deployment_name = '{{ deployment_name }}' -- required;

getexperiment

Gets metadata for an experiment. This method works on deleted experiments.

SELECT
name,
experiment_id,
artifact_location,
creation_time,
last_update_time,
lifecycle_stage,
tags
FROM databricks_workspace.machinelearning.experiments
WHERE deployment_name = '{{ deployment_name }}' -- required;

getbyname

Gets metadata for an experiment.

SELECT
name,
experiment_id,
artifact_location,
creation_time,
last_update_time,
lifecycle_stage,
tags
FROM databricks_workspace.machinelearning.experiments
WHERE deployment_name = '{{ deployment_name }}' -- required;

INSERT examples

createexperiment

Creates an experiment with a name. Returns the ID of the newly created experiment. Validates that another experiment with the same name does not already exist and fails if another experiment with the same name already exists.

INSERT INTO databricks_workspace.machinelearning.experiments (
data__name,
data__artifact_location,
data__tags,
deployment_name
)
SELECT 
'{{ name }}',
'{{ artifact_location }}',
'{{ tags }}',
'{{ deployment_name }}'
RETURNING
experiment_id
;

Manifest

# Description fields are for documentation purposes
- name: experiments
  props:
    - name: deployment_name
      value: string
      description: Required parameter for the experiments resource.
    - name: name
      value: required
    - name: artifact_location
      value: string
    - name: tags
      value: Array of object

UPDATE examples

updateexperiment

Updates experiment metadata.

UPDATE databricks_workspace.machinelearning.experiments
SET 
data__experiment_id = '{{ experiment_id }}',
data__new_name = '{{ new_name }}'
WHERE 
deployment_name = '{{ deployment_name }}' --required;

DELETE examples

deleteexperiment

Marks an experiment and associated metadata, runs, metrics, params, and tags for deletion. If the experiment uses FileStore, artifacts associated with experiment are also deleted.

DELETE FROM databricks_workspace.machinelearning.experiments
WHERE deployment_name = '{{ deployment_name }}' --required;

Lifecycle Methods

restoreexperiment

Restore an experiment marked for deletion. This also restores associated metadata, runs, metrics, params, and tags. If experiment uses FileStore, underlying artifacts associated with experiment are also restored.

EXEC databricks_workspace.machinelearning.experiments.restoreexperiment 
@deployment_name='{{ deployment_name }}' --required 
@@json=
'{
"experiment_id": "{{ experiment_id }}"
}';