ExperimentsAPI (Databricks SDK for Java 0.94.0 API)

java.lang.Object
- com.databricks.sdk.service.ml.ExperimentsAPI

```
@Generated
public class ExperimentsAPI
extends Object
```
Experiments are the primary unit of organization in MLflow; all MLflow runs belong to an experiment. Each experiment lets you visualize, search, and compare runs, as well as download run artifacts or metadata for analysis in other tools. Experiments are maintained in a Databricks hosted MLflow tracking server.
Experiments are located in the workspace file tree. You manage experiments using the same tools you use to manage other workspace objects such as folders, notebooks, and libraries.

Constructor Summary

Constructors
Constructor and Description

ExperimentsAPI(ApiClient apiClient)
Regular-use constructor

ExperimentsAPI(ExperimentsService mock)
Constructor for mocks

Constructors
Constructor and Description
`ExperimentsAPI(ApiClient apiClient)` Regular-use constructor
`ExperimentsAPI(ExperimentsService mock)` Constructor for mocks

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`CreateExperimentResponse`	`createExperiment(CreateExperiment request)` Creates an experiment with a name.
`CreateLoggedModelResponse`	`createLoggedModel(CreateLoggedModelRequest request)` Create a logged model.
`CreateRunResponse`	`createRun(CreateRun request)` Creates a new run within an experiment.
`void`	`deleteExperiment(DeleteExperiment request)` Marks an experiment and associated metadata, runs, metrics, params, and tags for deletion.
`void`	`deleteLoggedModel(DeleteLoggedModelRequest request)` Delete a logged model.
`void`	`deleteLoggedModel(String modelId)`
`void`	`deleteLoggedModelTag(DeleteLoggedModelTagRequest request)` Delete a tag on a logged model.
`void`	`deleteLoggedModelTag(String modelId, String tagKey)`
`void`	`deleteRun(DeleteRun request)` Marks a run for deletion.
`DeleteRunsResponse`	`deleteRuns(DeleteRuns request)` Bulk delete runs in an experiment that were created prior to or at the specified timestamp.
`void`	`deleteTag(DeleteTag request)` Deletes a tag on a run.
`FinalizeLoggedModelResponse`	`finalizeLoggedModel(FinalizeLoggedModelRequest request)` Finalize a logged model.
`GetExperimentByNameResponse`	`getByName(GetByNameRequest request)` Gets metadata for an experiment.
`GetExperimentByNameResponse`	`getByName(String experimentName)`
`GetExperimentResponse`	`getExperiment(GetExperimentRequest request)` Gets metadata for an experiment.
`GetExperimentResponse`	`getExperiment(String experimentId)`
`Iterable<Metric>`	`getHistory(GetHistoryRequest request)` Gets a list of all values for the specified metric for a given run.
`Iterable<Metric>`	`getHistory(String metricKey)`
`GetLoggedModelResponse`	`getLoggedModel(GetLoggedModelRequest request)` Get a logged model.
`GetLoggedModelResponse`	`getLoggedModel(String modelId)`
`GetExperimentPermissionLevelsResponse`	`getPermissionLevels(GetExperimentPermissionLevelsRequest request)` Gets the permission levels that a user can have on an object.
`GetExperimentPermissionLevelsResponse`	`getPermissionLevels(String experimentId)`
`ExperimentPermissions`	`getPermissions(GetExperimentPermissionsRequest request)` Gets the permissions of an experiment.
`ExperimentPermissions`	`getPermissions(String experimentId)`
`GetRunResponse`	`getRun(GetRunRequest request)` Gets the metadata, metrics, params, and tags for a run.
`GetRunResponse`	`getRun(String runId)`
`ExperimentsService`	`impl()`
`Iterable<FileInfo>`	`listArtifacts(ListArtifactsRequest request)` List artifacts for a run.
`Iterable<Experiment>`	`listExperiments(ListExperimentsRequest request)` Gets a list of all experiments.
`void`	`logBatch(LogBatch request)` Logs a batch of metrics, params, and tags for a run.
`void`	`logInputs(LogInputs request)` Logs inputs, such as datasets and models, to an MLflow Run.
`void`	`logLoggedModelParams(LogLoggedModelParamsRequest request)` Logs params for a logged model.
`void`	`logMetric(LogMetric request)` Log a metric for a run.
`void`	`logModel(LogModel request)` Note: the [Create a logged model](/api/workspace/experiments/createloggedmodel) API replaces this endpoint.
`void`	`logOutputs(LogOutputsRequest request)` Logs outputs, such as models, from an MLflow Run.
`void`	`logParam(LogParam request)` Logs a param used for a run.
`void`	`restoreExperiment(RestoreExperiment request)` Restore an experiment marked for deletion.
`void`	`restoreRun(RestoreRun request)` Restores a deleted run.
`RestoreRunsResponse`	`restoreRuns(RestoreRuns request)` Bulk restore runs in an experiment that were deleted no earlier than the specified timestamp.
`Iterable<Experiment>`	`searchExperiments(SearchExperiments request)` Searches for experiments that satisfy specified search criteria.
`SearchLoggedModelsResponse`	`searchLoggedModels(SearchLoggedModelsRequest request)` Search for Logged Models that satisfy specified search criteria.
`Iterable<Run>`	`searchRuns(SearchRuns request)` Searches for runs that satisfy expressions.
`void`	`setExperimentTag(SetExperimentTag request)` Sets a tag on an experiment.
`void`	`setLoggedModelTags(SetLoggedModelTagsRequest request)` Set tags for a logged model.
`ExperimentPermissions`	`setPermissions(ExperimentPermissionsRequest request)` Sets permissions on an object, replacing existing permissions if they exist.
`void`	`setTag(SetTag request)` Sets a tag on a run.
`void`	`updateExperiment(UpdateExperiment request)` Updates experiment metadata.
`ExperimentPermissions`	`updatePermissions(ExperimentPermissionsRequest request)` Updates the permissions on an experiment.
`UpdateRunResponse`	`updateRun(UpdateRun request)` Updates run metadata.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - ExperimentsAPI
```
public ExperimentsAPI(ApiClient apiClient)
```
    Regular-use constructor
  - ExperimentsAPI
```
public ExperimentsAPI(ExperimentsService mock)
```
    Constructor for mocks
- Method Detail
  - createExperiment
```
public CreateExperimentResponse createExperiment(CreateExperiment request)
```
    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.
    Throws `RESOURCE_ALREADY_EXISTS` if an experiment with the given name exists.
  - createLoggedModel
```
public CreateLoggedModelResponse createLoggedModel(CreateLoggedModelRequest request)
```
    Create a logged model.
  - createRun
```
public CreateRunResponse createRun(CreateRun request)
```
    Creates a new run within an experiment. A run is usually a single execution of a machine learning or data ETL pipeline. MLflow uses runs to track the `mlflowParam`, `mlflowMetric`, and `mlflowRunTag` associated with a single execution.
  - deleteExperiment
```
public void deleteExperiment(DeleteExperiment request)
```
    Marks an experiment and associated metadata, runs, metrics, params, and tags for deletion. If the experiment uses FileStore, artifacts associated with the experiment are also deleted.
  - deleteLoggedModel
```
public void deleteLoggedModel(String modelId)
```
  - deleteLoggedModel
```
public void deleteLoggedModel(DeleteLoggedModelRequest request)
```
    Delete a logged model.
  - deleteLoggedModelTag
```
public void deleteLoggedModelTag(String modelId,
                                 String tagKey)
```
  - deleteLoggedModelTag
```
public void deleteLoggedModelTag(DeleteLoggedModelTagRequest request)
```
    Delete a tag on a logged model.
  - deleteRun
```
public void deleteRun(DeleteRun request)
```
    Marks a run for deletion.
  - deleteRuns
```
public DeleteRunsResponse deleteRuns(DeleteRuns request)
```
    Bulk delete runs in an experiment that were created prior to or at the specified timestamp. Deletes at most max_runs per request. To call this API from a Databricks Notebook in Python, you can use the client code snippet on
  - deleteTag
```
public void deleteTag(DeleteTag request)
```
    Deletes a tag on a run. Tags are run metadata that can be updated during a run and after a run completes.
  - finalizeLoggedModel
```
public FinalizeLoggedModelResponse finalizeLoggedModel(FinalizeLoggedModelRequest request)
```
    Finalize a logged model.
  - getByName
```
public GetExperimentByNameResponse getByName(String experimentName)
```
  - getByName
```
public GetExperimentByNameResponse getByName(GetByNameRequest request)
```
    Gets metadata for an experiment.
    This endpoint will return deleted experiments, but prefers the active experiment if an active and deleted experiment share the same name. If multiple deleted experiments share the same name, the API will return one of them.
    Throws `RESOURCE_DOES_NOT_EXIST` if no experiment with the specified name exists.
  - getExperiment
```
public GetExperimentResponse getExperiment(String experimentId)
```
  - getExperiment
```
public GetExperimentResponse getExperiment(GetExperimentRequest request)
```
    Gets metadata for an experiment. This method works on deleted experiments.
  - getHistory
```
public Iterable<Metric> getHistory(String metricKey)
```
  - getHistory
```
public Iterable<Metric> getHistory(GetHistoryRequest request)
```
    Gets a list of all values for the specified metric for a given run.
  - getLoggedModel
```
public GetLoggedModelResponse getLoggedModel(String modelId)
```
  - getLoggedModel
```
public GetLoggedModelResponse getLoggedModel(GetLoggedModelRequest request)
```
    Get a logged model.
  - getPermissionLevels
```
public GetExperimentPermissionLevelsResponse getPermissionLevels(String experimentId)
```
  - getPermissionLevels
```
public GetExperimentPermissionLevelsResponse getPermissionLevels(GetExperimentPermissionLevelsRequest request)
```
    Gets the permission levels that a user can have on an object.
  - getPermissions
```
public ExperimentPermissions getPermissions(String experimentId)
```
  - getPermissions
```
public ExperimentPermissions getPermissions(GetExperimentPermissionsRequest request)
```
    Gets the permissions of an experiment. Experiments can inherit permissions from their root object.
  - getRun
```
public GetRunResponse getRun(String runId)
```
  - getRun
```
public GetRunResponse getRun(GetRunRequest request)
```
    Gets the metadata, metrics, params, and tags for a run. In the case where multiple metrics with the same key are logged for a run, return only the value with the latest timestamp.
    If there are multiple values with the latest timestamp, return the maximum of these values.
  - listArtifacts
```
public Iterable<FileInfo> listArtifacts(ListArtifactsRequest request)
```
    List artifacts for a run. Takes an optional `artifact_path` prefix which if specified, the response contains only artifacts with the specified prefix. A maximum of 1000 artifacts will be retrieved for UC Volumes. Please call `/api/2.0/fs/directories{directory_path}` for listing artifacts in UC Volumes, which supports pagination. See [List directory contents | Files API](/api/workspace/files/listdirectorycontents).
  - listExperiments
```
public Iterable<Experiment> listExperiments(ListExperimentsRequest request)
```
    Gets a list of all experiments.
  - logBatch
```
public void logBatch(LogBatch request)
```
    Logs a batch of metrics, params, and tags for a run. If any data failed to be persisted, the server will respond with an error (non-200 status code).
    In case of error (due to internal server error or an invalid request), partial data may be written.
    You can write metrics, params, and tags in interleaving fashion, but within a given entity type are guaranteed to follow the order specified in the request body.
    The overwrite behavior for metrics, params, and tags is as follows:
    * Metrics: metric values are never overwritten. Logging a metric (key, value, timestamp) appends to the set of values for the metric with the provided key.
    * Tags: tag values can be overwritten by successive writes to the same tag key. That is, if multiple tag values with the same key are provided in the same API request, the last-provided tag value is written. Logging the same tag (key, value) is permitted. Specifically, logging a tag is idempotent.
    * Parameters: once written, param values cannot be changed (attempting to overwrite a param value will result in an error). However, logging the same param (key, value) is permitted. Specifically, logging a param is idempotent.
    Request Limits ------------------------------- A single JSON-serialized API request may be up to 1 MB in size and contain:
    * No more than 1000 metrics, params, and tags in total
    * Up to 1000 metrics
    * Up to 100 params
    * Up to 100 tags
    For example, a valid request might contain 900 metrics, 50 params, and 50 tags, but logging 900 metrics, 50 params, and 51 tags is invalid.
    The following limits also apply to metric, param, and tag keys and values:
    * Metric keys, param keys, and tag keys can be up to 250 characters in length
    * Parameter and tag values can be up to 250 characters in length
  - logInputs
```
public void logInputs(LogInputs request)
```
    Logs inputs, such as datasets and models, to an MLflow Run.
  - logLoggedModelParams
```
public void logLoggedModelParams(LogLoggedModelParamsRequest request)
```
    Logs params for a logged model. A param is a key-value pair (string key, string value). Examples include hyperparameters used for ML model training. A param can be logged only once for a logged model, and attempting to overwrite an existing param with a different value will result in an error
  - logMetric
```
public void logMetric(LogMetric request)
```
    Log a metric for a run. A metric is a key-value pair (string key, float value) with an associated timestamp. Examples include the various metrics that represent ML model accuracy. A metric can be logged multiple times.
  - logModel
```
public void logModel(LogModel request)
```
    **Note:** the [Create a logged model](/api/workspace/experiments/createloggedmodel) API replaces this endpoint.
    Log a model to an MLflow Run.
  - logOutputs
```
public void logOutputs(LogOutputsRequest request)
```
    Logs outputs, such as models, from an MLflow Run.
  - logParam
```
public void logParam(LogParam request)
```
    Logs a param used for a run. A param is a key-value pair (string key, string value). Examples include hyperparameters used for ML model training and constant dates and values used in an ETL pipeline. A param can be logged only once for a run.
  - restoreExperiment
```
public void restoreExperiment(RestoreExperiment request)
```
    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.
    Throws `RESOURCE_DOES_NOT_EXIST` if experiment was never created or was permanently deleted.
  - restoreRun
```
public void restoreRun(RestoreRun request)
```
    Restores a deleted run. This also restores associated metadata, runs, metrics, params, and tags.
    Throws `RESOURCE_DOES_NOT_EXIST` if the run was never created or was permanently deleted.
  - restoreRuns
```
public RestoreRunsResponse restoreRuns(RestoreRuns request)
```
    Bulk restore runs in an experiment that were deleted no earlier than the specified timestamp. Restores at most max_runs per request. To call this API from a Databricks Notebook in Python, you can use the client code snippet on
  - searchExperiments
```
public Iterable<Experiment> searchExperiments(SearchExperiments request)
```
    Searches for experiments that satisfy specified search criteria.
  - searchLoggedModels
```
public SearchLoggedModelsResponse searchLoggedModels(SearchLoggedModelsRequest request)
```
    Search for Logged Models that satisfy specified search criteria.
  - searchRuns
```
public Iterable<Run> searchRuns(SearchRuns request)
```
    Searches for runs that satisfy expressions.
    Search expressions can use `mlflowMetric` and `mlflowParam` keys.
  - setExperimentTag
```
public void setExperimentTag(SetExperimentTag request)
```
    Sets a tag on an experiment. Experiment tags are metadata that can be updated.
  - setLoggedModelTags
```
public void setLoggedModelTags(SetLoggedModelTagsRequest request)
```
    Set tags for a logged model.
  - setPermissions
```
public ExperimentPermissions setPermissions(ExperimentPermissionsRequest request)
```
    Sets permissions on an object, replacing existing permissions if they exist. Deletes all direct permissions if none are specified. Objects can inherit permissions from their root object.
  - setTag
```
public void setTag(SetTag request)
```
    Sets a tag on a run. Tags are run metadata that can be updated during a run and after a run completes.
  - updateExperiment
```
public void updateExperiment(UpdateExperiment request)
```
    Updates experiment metadata.
  - updatePermissions
```
public ExperimentPermissions updatePermissions(ExperimentPermissionsRequest request)
```
    Updates the permissions on an experiment. Experiments can inherit permissions from their root object.
  - updateRun
```
public UpdateRunResponse updateRun(UpdateRun request)
```
    Updates run metadata.
  - impl
```
public ExperimentsService impl()
```

Class ExperimentsAPI

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

ExperimentsAPI

ExperimentsAPI

Method Detail

createExperiment

createLoggedModel

createRun

deleteExperiment

deleteLoggedModel

deleteLoggedModel

deleteLoggedModelTag

deleteLoggedModelTag

deleteRun

deleteRuns

deleteTag

finalizeLoggedModel

getByName

getByName

getExperiment

getExperiment

getHistory

getHistory

getLoggedModel

getLoggedModel

getPermissionLevels

getPermissionLevels

getPermissions

getPermissions

getRun

getRun

listArtifacts

listExperiments

logBatch

logInputs

logLoggedModelParams

logMetric

logModel

logOutputs

logParam

restoreExperiment

restoreRun

restoreRuns

searchExperiments

searchLoggedModels

searchRuns

setExperimentTag

setLoggedModelTags

setPermissions

setTag

updateExperiment

updatePermissions

updateRun

impl