Class v1.FeaturestoreServiceClient (1.15.0)

Version 1.15.0

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The service that handles CRUD and List for resources for Featurestore. v1

Package

@google-cloud/aiplatform

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Construct an instance of FeaturestoreServiceClient.

Parameter

Name	Description
opts	ClientOptions

Properties

apiEndpoint

static get apiEndpoint(): string;

The DNS address for this API service - same as servicePath(), exists for compatibility reasons.

auth

auth: gax.GoogleAuth;

descriptors

descriptors: Descriptors;

featurestoreServiceStub

featurestoreServiceStub?: Promise<{
        [name: string]: Function;
    }>;

innerApiCalls

innerApiCalls: {
        [name: string]: Function;
    };

operationsClient

operationsClient: gax.OperationsClient;

pathTemplates

pathTemplates: {
        [name: string]: gax.PathTemplate;
    };

port

static get port(): number;

The port for this API service.

scopes

static get scopes(): string[];

The scopes needed to make gRPC calls for every method defined in this service.

servicePath

static get servicePath(): string;

The DNS address for this API service.

warn

warn: (code: string, message: string, warnType?: string) => void;

Methods

annotationPath(project, location, dataset, dataItem, annotation)

annotationPath(project: string, location: string, dataset: string, dataItem: string, annotation: string): string;

Return a fully-qualified annotation resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
dataItem	string
annotation	string

Returns

Type	Description
string	{string} Resource name string.

annotationSpecPath(project, location, dataset, annotationSpec)

annotationSpecPath(project: string, location: string, dataset: string, annotationSpec: string): string;

Return a fully-qualified annotationSpec resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
annotationSpec	string

Returns

Type	Description
string	{string} Resource name string.

artifactPath(project, location, metadataStore, artifact)

artifactPath(project: string, location: string, metadataStore: string, artifact: string): string;

Return a fully-qualified artifact resource name string.

Parameters

Name	Description
project	string
location	string
metadataStore	string
artifact	string

Returns

Type	Description
string	{string} Resource name string.

batchCreateFeatures(request, options)

batchCreateFeatures(request?: protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a batch of Features in a given EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the EntityType to create the batch of Features under.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The request message specifying the Features to create. All Features must be
   *  created under the same parent EntityType. The `parent` field in each child
   *  request message can be omitted. If `parent` is set in a child request, then
   *  the value must match the `parent` value in this request message.
   */
  // const requests = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callBatchCreateFeatures() {
    // Construct request
    const request = {
      parent,
      requests,
    };

    // Run request
    const [operation] = await aiplatformClient.batchCreateFeatures(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callBatchCreateFeatures();

batchCreateFeatures(request, options, callback)

batchCreateFeatures(request: protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

batchCreateFeatures(request, callback)

batchCreateFeatures(request: protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

batchPredictionJobPath(project, location, batchPredictionJob)

batchPredictionJobPath(project: string, location: string, batchPredictionJob: string): string;

Return a fully-qualified batchPredictionJob resource name string.

Parameters

Name	Description
project	string
location	string
batchPredictionJob	string

Returns

Type	Description
string	{string} Resource name string.

batchReadFeatureValues(request, options)

batchReadFeatureValues(request?: protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Batch reads Feature values from a Featurestore.

This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Each read instance consists of exactly one read timestamp and one or more
   *  entity IDs identifying entities of the corresponding EntityTypes whose
   *  Features are requested.
   *  Each output instance contains Feature values of requested entities
   *  concatenated together as of the read time.
   *  An example read instance may be `foo_entity_id, bar_entity_id,
   *  2020-01-01T10:00:00.123Z`.
   *  An example output instance may be `foo_entity_id, bar_entity_id,
   *  2020-01-01T10:00:00.123Z, foo_entity_feature1_value,
   *  bar_entity_feature2_value`.
   *  Timestamp in each read instance must be millisecond-aligned.
   *  `csv_read_instances` are read instances stored in a plain-text CSV file.
   *  The header should be:
   *      ENTITY_TYPE_ID1, ENTITY_TYPE_ID2, ..., timestamp
   *  The columns can be in any order.
   *  Values in the timestamp column must use the RFC 3339 format, e.g.
   *  `2012-07-30T10:43:17.123Z`.
   */
  // const csvReadInstances = {}
  /**
   *  Similar to csv_read_instances, but from BigQuery source.
   */
  // const bigqueryReadInstances = {}
  /**
   *  Required. The resource name of the Featurestore from which to query Feature values.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const featurestore = 'abc123'
  /**
   *  Required. Specifies output location and format.
   */
  // const destination = {}
  /**
   *  When not empty, the specified fields in the *_read_instances source will be
   *  joined as-is in the output, in addition to those fields from the
   *  Featurestore Entity.
   *  For BigQuery source, the type of the pass-through values will be
   *  automatically inferred. For CSV source, the pass-through values will be
   *  passed as opaque bytes.
   */
  // const passThroughFields = 1234
  /**
   *  Required. Specifies EntityType grouping Features to read values of and settings.
   *  Each EntityType referenced in
   *  BatchReadFeatureValuesRequest.entity_type_specs  must have a column
   *  specifying entity IDs in the EntityType in
   *  BatchReadFeatureValuesRequest.request   .
   */
  // const entityTypeSpecs = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callBatchReadFeatureValues() {
    // Construct request
    const request = {
      featurestore,
      destination,
      entityTypeSpecs,
    };

    // Run request
    const [operation] = await aiplatformClient.batchReadFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callBatchReadFeatureValues();

batchReadFeatureValues(request, options, callback)

batchReadFeatureValues(request: protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

batchReadFeatureValues(request, callback)

batchReadFeatureValues(request: protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

checkBatchCreateFeaturesProgress(name)

checkBatchCreateFeaturesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata>>;

Check the status of the long running operation returned by batchCreateFeatures().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the EntityType to create the batch of Features under.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The request message specifying the Features to create. All Features must be
   *  created under the same parent EntityType. The `parent` field in each child
   *  request message can be omitted. If `parent` is set in a child request, then
   *  the value must match the `parent` value in this request message.
   */
  // const requests = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callBatchCreateFeatures() {
    // Construct request
    const request = {
      parent,
      requests,
    };

    // Run request
    const [operation] = await aiplatformClient.batchCreateFeatures(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callBatchCreateFeatures();

checkBatchReadFeatureValuesProgress(name)

checkBatchReadFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata>>;

Check the status of the long running operation returned by batchReadFeatureValues().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Each read instance consists of exactly one read timestamp and one or more
   *  entity IDs identifying entities of the corresponding EntityTypes whose
   *  Features are requested.
   *  Each output instance contains Feature values of requested entities
   *  concatenated together as of the read time.
   *  An example read instance may be `foo_entity_id, bar_entity_id,
   *  2020-01-01T10:00:00.123Z`.
   *  An example output instance may be `foo_entity_id, bar_entity_id,
   *  2020-01-01T10:00:00.123Z, foo_entity_feature1_value,
   *  bar_entity_feature2_value`.
   *  Timestamp in each read instance must be millisecond-aligned.
   *  `csv_read_instances` are read instances stored in a plain-text CSV file.
   *  The header should be:
   *      ENTITY_TYPE_ID1, ENTITY_TYPE_ID2, ..., timestamp
   *  The columns can be in any order.
   *  Values in the timestamp column must use the RFC 3339 format, e.g.
   *  `2012-07-30T10:43:17.123Z`.
   */
  // const csvReadInstances = {}
  /**
   *  Similar to csv_read_instances, but from BigQuery source.
   */
  // const bigqueryReadInstances = {}
  /**
   *  Required. The resource name of the Featurestore from which to query Feature values.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const featurestore = 'abc123'
  /**
   *  Required. Specifies output location and format.
   */
  // const destination = {}
  /**
   *  When not empty, the specified fields in the *_read_instances source will be
   *  joined as-is in the output, in addition to those fields from the
   *  Featurestore Entity.
   *  For BigQuery source, the type of the pass-through values will be
   *  automatically inferred. For CSV source, the pass-through values will be
   *  passed as opaque bytes.
   */
  // const passThroughFields = 1234
  /**
   *  Required. Specifies EntityType grouping Features to read values of and settings.
   *  Each EntityType referenced in
   *  BatchReadFeatureValuesRequest.entity_type_specs  must have a column
   *  specifying entity IDs in the EntityType in
   *  BatchReadFeatureValuesRequest.request   .
   */
  // const entityTypeSpecs = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callBatchReadFeatureValues() {
    // Construct request
    const request = {
      featurestore,
      destination,
      entityTypeSpecs,
    };

    // Run request
    const [operation] = await aiplatformClient.batchReadFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callBatchReadFeatureValues();

checkCreateEntityTypeProgress(name)

checkCreateEntityTypeProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.EntityType, protos.google.cloud.aiplatform.v1.CreateEntityTypeOperationMetadata>>;

Check the status of the long running operation returned by createEntityType().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.EntityType, protos.google.cloud.aiplatform.v1.CreateEntityTypeOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Featurestore to create EntityTypes.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const parent = 'abc123'
  /**
   *  The EntityType to create.
   */
  // const entityType = {}
  /**
   *  Required. The ID to use for the EntityType, which will become the final component of
   *  the EntityType's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within a featurestore.
   */
  // const entityTypeId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateEntityType() {
    // Construct request
    const request = {
      parent,
      entityTypeId,
    };

    // Run request
    const [operation] = await aiplatformClient.createEntityType(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateEntityType();

checkCreateFeatureProgress(name)

checkCreateFeatureProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Feature, protos.google.cloud.aiplatform.v1.CreateFeatureOperationMetadata>>;

Check the status of the long running operation returned by createFeature().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.Feature, protos.google.cloud.aiplatform.v1.CreateFeatureOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the EntityType to create a Feature.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Feature to create.
   */
  // const feature = {}
  /**
   *  Required. The ID to use for the Feature, which will become the final component of
   *  the Feature's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within an EntityType.
   */
  // const featureId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateFeature() {
    // Construct request
    const request = {
      parent,
      feature,
      featureId,
    };

    // Run request
    const [operation] = await aiplatformClient.createFeature(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateFeature();

checkCreateFeaturestoreProgress(name)

checkCreateFeaturestoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata>>;

Check the status of the long running operation returned by createFeaturestore().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to create Featurestores.
   *  Format:
   *  `projects/{project}/locations/{location}'`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Featurestore to create.
   */
  // const featurestore = {}
  /**
   *  Required. The ID to use for this Featurestore, which will become the final component
   *  of the Featurestore's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within the project and location.
   */
  // const featurestoreId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateFeaturestore() {
    // Construct request
    const request = {
      parent,
      featurestore,
      featurestoreId,
    };

    // Run request
    const [operation] = await aiplatformClient.createFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateFeaturestore();

checkDeleteEntityTypeProgress(name)

checkDeleteEntityTypeProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteEntityType().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the EntityType to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const name = 'abc123'
  /**
   *  If set to true, any Features for this EntityType will also be deleted.
   *  (Otherwise, the request will only work if the EntityType has no Features.)
   */
  // const force = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteEntityType() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteEntityType(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteEntityType();

checkDeleteFeatureProgress(name)

checkDeleteFeatureProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteFeature().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Features to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteFeature() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteFeature(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteFeature();

checkDeleteFeaturestoreProgress(name)

checkDeleteFeaturestoreProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteFeaturestore().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Featurestore to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const name = 'abc123'
  /**
   *  If set to true, any EntityTypes and Features for this Featurestore will
   *  also be deleted. (Otherwise, the request will only work if the Featurestore
   *  has no EntityTypes.)
   */
  // const force = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteFeaturestore() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteFeaturestore();

checkExportFeatureValuesProgress(name)

checkExportFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata>>;

Check the status of the long running operation returned by exportFeatureValues().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Exports the latest Feature values of all entities of the EntityType
   *  within a time range.
   */
  // const snapshotExport = {}
  /**
   *  Exports all historical values of all entities of the EntityType within a
   *  time range
   */
  // const fullExport = {}
  /**
   *  Required. The resource name of the EntityType from which to export Feature values.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const entityType = 'abc123'
  /**
   *  Required. Specifies destination location and format.
   */
  // const destination = {}
  /**
   *  Required. Selects Features to export values of.
   */
  // const featureSelector = {}
  /**
   *  Per-Feature export settings.
   */
  // const settings = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callExportFeatureValues() {
    // Construct request
    const request = {
      entityType,
      destination,
      featureSelector,
    };

    // Run request
    const [operation] = await aiplatformClient.exportFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callExportFeatureValues();

checkImportFeatureValuesProgress(name)

checkImportFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata>>;

Check the status of the long running operation returned by importFeatureValues().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   */
  // const avroSource = {}
  /**
   */
  // const bigquerySource = {}
  /**
   */
  // const csvSource = {}
  /**
   *  Source column that holds the Feature timestamp for all Feature
   *  values in each entity.
   */
  // const featureTimeField = 'abc123'
  /**
   *  Single Feature timestamp for all entities being imported. The
   *  timestamp must not have higher than millisecond precision.
   */
  // const featureTime = {}
  /**
   *  Required. The resource name of the EntityType grouping the Features for which values
   *  are being imported. Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
   */
  // const entityType = 'abc123'
  /**
   *  Source column that holds entity IDs. If not provided, entity IDs are
   *  extracted from the column named `entity_id`.
   */
  // const entityIdField = 'abc123'
  /**
   *  Required. Specifications defining which Feature values to import from the entity. The
   *  request fails if no feature_specs are provided, and having multiple
   *  feature_specs for one Feature is not allowed.
   */
  // const featureSpecs = 1234
  /**
   *  If set, data will not be imported for online serving. This
   *  is typically used for backfilling, where Feature generation timestamps are
   *  not in the timestamp range needed for online serving.
   */
  // const disableOnlineServing = true
  /**
   *  Specifies the number of workers that are used to write data to the
   *  Featurestore. Consider the online serving capacity that you require to
   *  achieve the desired import throughput without interfering with online
   *  serving. The value must be positive, and less than or equal to 100.
   *  If not set, defaults to using 1 worker. The low count ensures minimal
   *  impact on online serving performance.
   */
  // const workerCount = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callImportFeatureValues() {
    // Construct request
    const request = {
      entityType,
      featureSpecs,
    };

    // Run request
    const [operation] = await aiplatformClient.importFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callImportFeatureValues();

checkUpdateFeaturestoreProgress(name)

checkUpdateFeaturestoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.UpdateFeaturestoreOperationMetadata>>;

Check the status of the long running operation returned by updateFeaturestore().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.UpdateFeaturestoreOperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The Featurestore's `name` field is used to identify the Featurestore to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const featurestore = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  Featurestore resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `labels`
   *    * `online_serving_config.fixed_node_count`
   */
  // const updateMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callUpdateFeaturestore() {
    // Construct request
    const request = {
      featurestore,
    };

    // Run request
    const [operation] = await aiplatformClient.updateFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callUpdateFeaturestore();

close()

close(): Promise<void>;

Terminate the gRPC channel and close the client.

The client will no longer be usable and all future behavior is undefined.

Returns

Type	Description
Promise<void>	{Promise} A promise that resolves when the client is closed.

contextPath(project, location, metadataStore, context)

contextPath(project: string, location: string, metadataStore: string, context: string): string;

Return a fully-qualified context resource name string.

Parameters

Name	Description
project	string
location	string
metadataStore	string
context	string

Returns

Type	Description
string	{string} Resource name string.

createEntityType(request, options)

createEntityType(request?: protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new EntityType in a given Featurestore.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Featurestore to create EntityTypes.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const parent = 'abc123'
  /**
   *  The EntityType to create.
   */
  // const entityType = {}
  /**
   *  Required. The ID to use for the EntityType, which will become the final component of
   *  the EntityType's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within a featurestore.
   */
  // const entityTypeId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateEntityType() {
    // Construct request
    const request = {
      parent,
      entityTypeId,
    };

    // Run request
    const [operation] = await aiplatformClient.createEntityType(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateEntityType();

createEntityType(request, options, callback)

createEntityType(request: protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createEntityType(request, callback)

createEntityType(request: protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createFeature(request, options)

createFeature(request?: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new Feature in a given EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeatureRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the EntityType to create a Feature.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Feature to create.
   */
  // const feature = {}
  /**
   *  Required. The ID to use for the Feature, which will become the final component of
   *  the Feature's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within an EntityType.
   */
  // const featureId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateFeature() {
    // Construct request
    const request = {
      parent,
      feature,
      featureId,
    };

    // Run request
    const [operation] = await aiplatformClient.createFeature(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateFeature();

createFeature(request, options, callback)

createFeature(request: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeatureRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createFeature(request, callback)

createFeature(request: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeatureRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createFeaturestore(request, options)

createFeaturestore(request?: protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new Featurestore in a given project and location.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to create Featurestores.
   *  Format:
   *  `projects/{project}/locations/{location}'`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Featurestore to create.
   */
  // const featurestore = {}
  /**
   *  Required. The ID to use for this Featurestore, which will become the final component
   *  of the Featurestore's resource name.
   *  This value may be up to 60 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within the project and location.
   */
  // const featurestoreId = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callCreateFeaturestore() {
    // Construct request
    const request = {
      parent,
      featurestore,
      featurestoreId,
    };

    // Run request
    const [operation] = await aiplatformClient.createFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateFeaturestore();

createFeaturestore(request, options, callback)

createFeaturestore(request: protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createFeaturestore(request, callback)

createFeaturestore(request: protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

customJobPath(project, location, customJob)

customJobPath(project: string, location: string, customJob: string): string;

Return a fully-qualified customJob resource name string.

Parameters

Name	Description
project	string
location	string
customJob	string

Returns

Type	Description
string	{string} Resource name string.

dataItemPath(project, location, dataset, dataItem)

dataItemPath(project: string, location: string, dataset: string, dataItem: string): string;

Return a fully-qualified dataItem resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
dataItem	string

Returns

Type	Description
string	{string} Resource name string.

dataLabelingJobPath(project, location, dataLabelingJob)

dataLabelingJobPath(project: string, location: string, dataLabelingJob: string): string;

Return a fully-qualified dataLabelingJob resource name string.

Parameters

Name	Description
project	string
location	string
dataLabelingJob	string

Returns

Type	Description
string	{string} Resource name string.

datasetPath(project, location, dataset)

datasetPath(project: string, location: string, dataset: string): string;

Return a fully-qualified dataset resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string

Returns

Type	Description
string	{string} Resource name string.

deleteEntityType(request, options)

deleteEntityType(request?: protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a single EntityType. The EntityType must not have any Features or force must be set to true for the request to succeed.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the EntityType to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const name = 'abc123'
  /**
   *  If set to true, any Features for this EntityType will also be deleted.
   *  (Otherwise, the request will only work if the EntityType has no Features.)
   */
  // const force = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteEntityType() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteEntityType(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteEntityType();

deleteEntityType(request, options, callback)

deleteEntityType(request: protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteEntityType(request, callback)

deleteEntityType(request: protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteFeature(request, options)

deleteFeature(request?: protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a single Feature.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Features to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteFeature() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteFeature(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteFeature();

deleteFeature(request, options, callback)

deleteFeature(request: protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteFeature(request, callback)

deleteFeature(request: protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteFeaturestore(request, options)

deleteFeaturestore(request?: protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or force must be set to true for the request to succeed.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Featurestore to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const name = 'abc123'
  /**
   *  If set to true, any EntityTypes and Features for this Featurestore will
   *  also be deleted. (Otherwise, the request will only work if the Featurestore
   *  has no EntityTypes.)
   */
  // const force = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callDeleteFeaturestore() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteFeaturestore();

deleteFeaturestore(request, options, callback)

deleteFeaturestore(request: protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteFeaturestore(request, callback)

deleteFeaturestore(request: protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

endpointPath(project, location, endpoint)

endpointPath(project: string, location: string, endpoint: string): string;

Return a fully-qualified endpoint resource name string.

Parameters

Name	Description
project	string
location	string
endpoint	string

Returns

Type	Description
string	{string} Resource name string.

entityTypePath(project, location, featurestore, entityType)

entityTypePath(project: string, location: string, featurestore: string, entityType: string): string;

Return a fully-qualified entityType resource name string.

Parameters

Name	Description
project	string
location	string
featurestore	string
entityType	string

Returns

Type	Description
string	{string} Resource name string.

executionPath(project, location, metadataStore, execution)

executionPath(project: string, location: string, metadataStore: string, execution: string): string;

Return a fully-qualified execution resource name string.

Parameters

Name	Description
project	string
location	string
metadataStore	string
execution	string

Returns

Type	Description
string	{string} Resource name string.

exportFeatureValues(request, options)

exportFeatureValues(request?: protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Exports Feature values from all the entities of a target EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Exports the latest Feature values of all entities of the EntityType
   *  within a time range.
   */
  // const snapshotExport = {}
  /**
   *  Exports all historical values of all entities of the EntityType within a
   *  time range
   */
  // const fullExport = {}
  /**
   *  Required. The resource name of the EntityType from which to export Feature values.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const entityType = 'abc123'
  /**
   *  Required. Specifies destination location and format.
   */
  // const destination = {}
  /**
   *  Required. Selects Features to export values of.
   */
  // const featureSelector = {}
  /**
   *  Per-Feature export settings.
   */
  // const settings = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callExportFeatureValues() {
    // Construct request
    const request = {
      entityType,
      destination,
      featureSelector,
    };

    // Run request
    const [operation] = await aiplatformClient.exportFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callExportFeatureValues();

exportFeatureValues(request, options, callback)

exportFeatureValues(request: protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportFeatureValues(request, callback)

exportFeatureValues(request: protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

featurePath(project, location, featurestore, entityType, feature)

featurePath(project: string, location: string, featurestore: string, entityType: string, feature: string): string;

Return a fully-qualified feature resource name string.

Parameters

Name	Description
project	string
location	string
featurestore	string
entityType	string
feature	string

Returns

Type	Description
string	{string} Resource name string.

featurestorePath(project, location, featurestore)

featurestorePath(project: string, location: string, featurestore: string): string;

Return a fully-qualified featurestore resource name string.

Parameters

Name	Description
project	string
location	string
featurestore	string

Returns

Type	Description
string	{string} Resource name string.

getEntityType(request, options)

getEntityType(request?: protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IEntityType,
        protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | undefined,
        {} | undefined
    ]>;

Gets details of a single EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [EntityType]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the EntityType resource.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callGetEntityType() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getEntityType(request);
    console.log(response);
  }

  callGetEntityType();

getEntityType(request, options, callback)

getEntityType(request: protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest
options	CallOptions
callback	Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getEntityType(request, callback)

getEntityType(request: protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest
callback	Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getFeature(request, options)

getFeature(request?: protos.google.cloud.aiplatform.v1.IGetFeatureRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeature,
        protos.google.cloud.aiplatform.v1.IGetFeatureRequest | undefined,
        {} | undefined
    ]>;

Gets details of a single Feature.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeatureRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Feature]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Feature resource.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callGetFeature() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getFeature(request);
    console.log(response);
  }

  callGetFeature();

getFeature(request, options, callback)

getFeature(request: protos.google.cloud.aiplatform.v1.IGetFeatureRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeatureRequest
options	CallOptions
callback	Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getFeature(request, callback)

getFeature(request: protos.google.cloud.aiplatform.v1.IGetFeatureRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeatureRequest
callback	Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getFeaturestore(request, options)

getFeaturestore(request?: protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeaturestore,
        protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | undefined,
        {} | undefined
    ]>;

Gets details of a single Featurestore.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Featurestore]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Featurestore resource.
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callGetFeaturestore() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getFeaturestore(request);
    console.log(response);
  }

  callGetFeaturestore();

getFeaturestore(request, options, callback)

getFeaturestore(request: protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest
options	CallOptions
callback	Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getFeaturestore(request, callback)

getFeaturestore(request: protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest
callback	Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getProjectId()

getProjectId(): Promise<string>;

Returns

Type	Description
Promise<string>

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;

Parameter

Name	Description
callback	Callback<string, undefined, undefined>

Returns

Type	Description
void

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

hyperparameterTuningJobPath(project: string, location: string, hyperparameterTuningJob: string): string;

Return a fully-qualified hyperparameterTuningJob resource name string.

Parameters

Name	Description
project	string
location	string
hyperparameterTuningJob	string

Returns

Type	Description
string	{string} Resource name string.

importFeatureValues(request, options)

importFeatureValues(request?: protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Imports Feature values into the Featurestore from a source storage.

The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done.

If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done.

There are also scenarios where the caller can cause inconsistency.

• Source data for import contains multiple distinct Feature values for the same entity ID and timestamp. - Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy. - Online serving cluster is under-provisioned.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   */
  // const avroSource = {}
  /**
   */
  // const bigquerySource = {}
  /**
   */
  // const csvSource = {}
  /**
   *  Source column that holds the Feature timestamp for all Feature
   *  values in each entity.
   */
  // const featureTimeField = 'abc123'
  /**
   *  Single Feature timestamp for all entities being imported. The
   *  timestamp must not have higher than millisecond precision.
   */
  // const featureTime = {}
  /**
   *  Required. The resource name of the EntityType grouping the Features for which values
   *  are being imported. Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
   */
  // const entityType = 'abc123'
  /**
   *  Source column that holds entity IDs. If not provided, entity IDs are
   *  extracted from the column named `entity_id`.
   */
  // const entityIdField = 'abc123'
  /**
   *  Required. Specifications defining which Feature values to import from the entity. The
   *  request fails if no feature_specs are provided, and having multiple
   *  feature_specs for one Feature is not allowed.
   */
  // const featureSpecs = 1234
  /**
   *  If set, data will not be imported for online serving. This
   *  is typically used for backfilling, where Feature generation timestamps are
   *  not in the timestamp range needed for online serving.
   */
  // const disableOnlineServing = true
  /**
   *  Specifies the number of workers that are used to write data to the
   *  Featurestore. Consider the online serving capacity that you require to
   *  achieve the desired import throughput without interfering with online
   *  serving. The value must be positive, and less than or equal to 100.
   *  If not set, defaults to using 1 worker. The low count ensures minimal
   *  impact on online serving performance.
   */
  // const workerCount = 1234

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callImportFeatureValues() {
    // Construct request
    const request = {
      entityType,
      featureSpecs,
    };

    // Run request
    const [operation] = await aiplatformClient.importFeatureValues(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callImportFeatureValues();

importFeatureValues(request, options, callback)

importFeatureValues(request: protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

importFeatureValues(request, callback)

importFeatureValues(request: protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

indexEndpointPath(project, location, indexEndpoint)

indexEndpointPath(project: string, location: string, indexEndpoint: string): string;

Return a fully-qualified indexEndpoint resource name string.

Parameters

Name	Description
project	string
location	string
indexEndpoint	string

Returns

Type	Description
string	{string} Resource name string.

indexPath(project, location, index)

indexPath(project: string, location: string, index: string): string;

Return a fully-qualified index resource name string.

Parameters

Name	Description
project	string
location	string
index	string

Returns

Type	Description
string	{string} Resource name string.

initialize()

initialize(): Promise<{
        [name: string]: Function;
    }>;

Initialize the client. Performs asynchronous operations (such as authentication) and prepares the client. This function will be called automatically when any class method is called for the first time, but if you need to initialize it before calling an actual method, feel free to call initialize() directly.

You can await on this method if you want to make sure the client is initialized.

Returns

Type	Description
Promise<{ [name: string]: Function; }>	{Promise} A promise that resolves to an authenticated service stub.

listEntityTypes(request, options)

listEntityTypes(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IEntityType[],
        protos.google.cloud.aiplatform.v1.IListEntityTypesRequest | null,
        protos.google.cloud.aiplatform.v1.IListEntityTypesResponse
    ]>;

Lists EntityTypes in a given Featurestore.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListEntityTypesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[ protos.google.cloud.aiplatform.v1.IEntityType[], protos.google.cloud.aiplatform.v1.IListEntityTypesRequest | null, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [EntityType]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listEntityTypesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listEntityTypes(request, options, callback)

listEntityTypes(request: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>

Returns

Type	Description
void

listEntityTypes(request, callback)

listEntityTypes(request: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>

Returns

Type	Description
void

listEntityTypesAsync(request, options)

listEntityTypesAsync(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IEntityType>;

Equivalent to listEntityTypes, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListEntityTypesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.aiplatform.v1.IEntityType>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [EntityType]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Featurestore to list EntityTypes.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const parent = 'abc123'
  /**
   *  Lists the EntityTypes that match the filter expression. The following
   *  filters are supported:
   *  * `create_time`: Supports `=`, `!=`, `<`, `="">`, `>=`, and `<=` comparisons.="" *="" values="" must="" be="" in="" rfc="" 3339="" format.="" *="" *="" `update_time`:="" supports="" `="`," `!="`,"><`, `="">`, `>=`, and `<=` comparisons.="" *="" values="" must="" be="" in="" rfc="" 3339="" format.="" *="" *="" `labels`:="" supports="" key-value="" equality="" as="" well="" as="" key="" presence.="" *="" examples:="" *="" *="" `create_time=""> \"2020-01-31T15:30:00.000000Z\" OR
   *       update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created
   *       or updated after 2020-01-31T15:30:00.000000Z.
   *  * `labels.active = yes AND labels.env = prod` --> EntityTypes having both
   *      (active: yes) and (env: prod) labels.
   *  * `labels.env: *` --> Any EntityType which has a label with 'env' as the
   *    key.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of EntityTypes to return. The service may return fewer
   *  than this value. If unspecified, at most 1000 EntityTypes will be returned.
   *  The maximum value is 1000; any value greater than 1000 will be coerced to
   *  1000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  FeaturestoreService.ListEntityTypes google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListEntityTypes google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported fields:
   *    * `entity_type_id`
   *    * `create_time`
   *    * `update_time`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callListEntityTypes() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listEntityTypesAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListEntityTypes();

listEntityTypesStream(request, options)

listEntityTypesStream(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListEntityTypesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [EntityType] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listEntityTypesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listFeatures(request, options)

listFeatures(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeature[],
        protos.google.cloud.aiplatform.v1.IListFeaturesRequest | null,
        protos.google.cloud.aiplatform.v1.IListFeaturesResponse
    ]>;

Lists Features in a given EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[ protos.google.cloud.aiplatform.v1.IFeature[], protos.google.cloud.aiplatform.v1.IListFeaturesRequest | null, protos.google.cloud.aiplatform.v1.IListFeaturesResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Feature]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listFeaturesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listFeatures(request, options, callback)

listFeatures(request: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturesRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>

Returns

Type	Description
void

listFeatures(request, callback)

listFeatures(request: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturesRequest
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>

Returns

Type	Description
void

listFeaturesAsync(request, options)

listFeaturesAsync(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature>;

Equivalent to listFeatures, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Feature]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to list Features.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const parent = 'abc123'
  /**
   *  Lists the Features that match the filter expression. The following
   *  filters are supported:
   *  * `value_type`: Supports = and != comparisons.
   *  * `create_time`: Supports =, !=, <,>, >=, and <= comparisons.="" values="" must="" *="" be="" in="" rfc="" 3339="" format.="" *="" *="" `update_time`:="" supports="," !=","><,>, >=, and <= comparisons.="" values="" must="" *="" be="" in="" rfc="" 3339="" format.="" *="" *="" `labels`:="" supports="" key-value="" equality="" as="" well="" as="" key="" presence.="" *="" examples:="" *="" *="" `value_type="DOUBLE`" --=""> Features whose type is DOUBLE.
   *  * `create_time > \"2020-01-31T15:30:00.000000Z\" OR
   *       update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created
   *       or updated after 2020-01-31T15:30:00.000000Z.
   *  * `labels.active = yes AND labels.env = prod` --> Features having both
   *      (active: yes) and (env: prod) labels.
   *  * `labels.env: *` --> Any Feature which has a label with 'env' as the
   *    key.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of Features to return. The service may return fewer
   *  than this value. If unspecified, at most 1000 Features will be returned.
   *  The maximum value is 1000; any value greater than 1000 will be coerced to
   *  1000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  FeaturestoreService.ListFeatures google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeatures google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported fields:
   *    * `feature_id`
   *    * `value_type`
   *    * `create_time`
   *    * `update_time`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  If set, return the most recent ListFeaturesRequest.latest_stats_count google.cloud.aiplatform.v1.ListFeaturesRequest.latest_stats_count 
   *  of stats for each Feature in response. Valid value is 0, 10. If number of
   *  stats exists < listfeaturesrequest.latest_stats_count="" google.cloud.aiplatform.v1.listfeaturesrequest.latest_stats_count,="" return="" all="" *="" existing="" stats.="" */="" const="" lateststatscount="1234" imports="" the="" aiplatform="" library="" const="" {featurestoreserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" featurestoreserviceclient();="" async="" function="" calllistfeatures()="" {="" construct="" request="" const="" request="{" parent,="" };="" run="" request="" const="" iterable="await" aiplatformclient.listfeaturesasync(request);="" for="" await="" (const="" response="" of="" iterable)="" {="" console.log(response);="" }="" }="" calllistfeatures();="">

listFeaturesStream(request, options)

listFeaturesStream(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [Feature] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listFeaturesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listFeaturestores(request, options)

listFeaturestores(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeaturestore[],
        protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest | null,
        protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse
    ]>;

Lists Featurestores in a given project and location.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[ protos.google.cloud.aiplatform.v1.IFeaturestore[], protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest | null, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Featurestore]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listFeaturestoresAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listFeaturestores(request, options, callback)

listFeaturestores(request: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>

Returns

Type	Description
void

listFeaturestores(request, callback)

listFeaturestores(request: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>

Returns

Type	Description
void

listFeaturestoresAsync(request, options)

listFeaturestoresAsync(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IFeaturestore>;

Equivalent to listFeaturestores, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.aiplatform.v1.IFeaturestore>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Featurestore]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to list Featurestores.
   *  Format:
   *  `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Lists the featurestores that match the filter expression. The following
   *  fields are supported:
   *  * `create_time`: Supports `=`, `!=`, `<`, `="">`, `<=`, and="" `="">=` comparisons.
   *  Values must be
   *    in RFC 3339 format.
   *  * `update_time`: Supports `=`, `!=`, `<`, `="">`, `<=`, and="" `="">=` comparisons.
   *  Values must be
   *    in RFC 3339 format.
   *  * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `<`, `="">`,
   *  `<=`, and="" `="">=` comparisons.
   *  * `labels`: Supports key-value equality and key presence.
   *  Examples:
   *  * `create_time > "2020-01-01" OR update_time > "2020-01-01"`
   *     Featurestores created or updated after 2020-01-01.
   *  * `labels.env = "prod"`
   *     Featurestores with label "env" set to "prod".
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of Featurestores to return. The service may return fewer
   *  than this value. If unspecified, at most 100 Featurestores will be
   *  returned. The maximum value is 100; any value greater than 100 will be
   *  coerced to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  FeaturestoreService.ListFeaturestores google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeaturestores google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported Fields:
   *    * `create_time`
   *    * `update_time`
   *    * `online_serving_config.fixed_node_count`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callListFeaturestores() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listFeaturestoresAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListFeaturestores();

listFeaturestoresStream(request, options)

listFeaturestoresStream(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [Featurestore] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listFeaturestoresAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

locationPath(project, location)

locationPath(project: string, location: string): string;

Return a fully-qualified location resource name string.

Parameters

Name	Description
project	string
location	string

Returns

Type	Description
string	{string} Resource name string.

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

Parse the annotation from Annotation resource.

Parameter

Name	Description
annotationName	string A fully-qualified path representing Annotation resource.

Returns

Type	Description
string | number	{string} A string representing the annotation.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the annotation_spec.

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

Parse the artifact from Artifact resource.

Parameter

Name	Description
artifactName	string A fully-qualified path representing Artifact resource.

Returns

Type	Description
string | number	{string} A string representing the artifact.

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the batch_prediction_job from BatchPredictionJob resource.

Parameter

Name	Description
batchPredictionJobName	string A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
string | number	{string} A string representing the batch_prediction_job.

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

Parse the context from Context resource.

Parameter

Name	Description
contextName	string A fully-qualified path representing Context resource.

Returns

Type	Description
string | number	{string} A string representing the context.

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

Parse the custom_job from CustomJob resource.

Parameter

Name	Description
customJobName	string A fully-qualified path representing CustomJob resource.

Returns

Type	Description
string | number	{string} A string representing the custom_job.

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

Parse the data_item from Annotation resource.

Parameter

Name	Description
annotationName	string A fully-qualified path representing Annotation resource.

Returns

Type	Description
string | number	{string} A string representing the data_item.

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

Parse the data_item from DataItem resource.

Parameter

Name	Description
dataItemName	string A fully-qualified path representing DataItem resource.

Returns

Type	Description
string | number	{string} A string representing the data_item.

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the data_labeling_job from DataLabelingJob resource.

Parameter

Name	Description
dataLabelingJobName	string A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
string | number	{string} A string representing the data_labeling_job.

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

Parse the dataset from Annotation resource.

Parameter

Name	Description
annotationName	string A fully-qualified path representing Annotation resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

Parse the dataset from DataItem resource.

Parameter

Name	Description
dataItemName	string A fully-qualified path representing DataItem resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

Parse the endpoint from Endpoint resource.

Parameter

Name	Description
endpointName	string A fully-qualified path representing Endpoint resource.

Returns

Type	Description
string | number	{string} A string representing the endpoint.

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

Parse the entity_type from EntityType resource.

Parameter

Name	Description
entityTypeName	string A fully-qualified path representing EntityType resource.

Returns

Type	Description
string | number	{string} A string representing the entity_type.

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: string): string | number;

Parse the entity_type from Feature resource.

Parameter

Name	Description
featureName	string A fully-qualified path representing Feature resource.

Returns

Type	Description
string | number	{string} A string representing the entity_type.

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the evaluation from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the evaluation.

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the evaluation from ModelEvaluationSlice resource.

Parameter

Name	Description
modelEvaluationSliceName	string A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
string | number	{string} A string representing the evaluation.

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

Parse the execution from Execution resource.

Parameter

Name	Description
executionName	string A fully-qualified path representing Execution resource.

Returns

Type	Description
string | number	{string} A string representing the execution.

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the experiment from TensorboardExperiment resource.

Parameter

Name	Description
tensorboardExperimentName	string A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
string | number	{string} A string representing the experiment.

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the experiment from TensorboardRun resource.

Parameter

Name	Description
tensorboardRunName	string A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
string | number	{string} A string representing the experiment.

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the experiment from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the experiment.

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

Parse the feature from Feature resource.

Parameter

Name	Description
featureName	string A fully-qualified path representing Feature resource.

Returns

Type	Description
string | number	{string} A string representing the feature.

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

Parse the featurestore from EntityType resource.

Parameter

Name	Description
entityTypeName	string A fully-qualified path representing EntityType resource.

Returns

Type	Description
string | number	{string} A string representing the featurestore.

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

Parse the featurestore from Feature resource.

Parameter

Name	Description
featureName	string A fully-qualified path representing Feature resource.

Returns

Type	Description
string | number	{string} A string representing the featurestore.

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

Parse the featurestore from Featurestore resource.

Parameter

Name	Description
featurestoreName	string A fully-qualified path representing Featurestore resource.

Returns

Type	Description
string | number	{string} A string representing the featurestore.

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.

Parameter

Name	Description
hyperparameterTuningJobName	string A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
string | number	{string} A string representing the hyperparameter_tuning_job.

matchIndexEndpointFromIndexEndpointName(indexEndpointName)

matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the index_endpoint from IndexEndpoint resource.

Parameter

Name	Description
indexEndpointName	string A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
string | number	{string} A string representing the index_endpoint.

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

Parse the index from Index resource.

Parameter

Name	Description
indexName	string A fully-qualified path representing Index resource.

Returns

Type	Description
string | number	{string} A string representing the index.

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

Parse the location from Annotation resource.

Parameter

Name	Description
annotationName	string A fully-qualified path representing Annotation resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

Parse the location from Artifact resource.

Parameter

Name	Description
artifactName	string A fully-qualified path representing Artifact resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the location from BatchPredictionJob resource.

Parameter

Name	Description
batchPredictionJobName	string A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

Parse the location from Context resource.

Parameter

Name	Description
contextName	string A fully-qualified path representing Context resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

Parse the location from CustomJob resource.

Parameter

Name	Description
customJobName	string A fully-qualified path representing CustomJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

Parse the location from DataItem resource.

Parameter

Name	Description
dataItemName	string A fully-qualified path representing DataItem resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the location from DataLabelingJob resource.

Parameter

Name	Description
dataLabelingJobName	string A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

Parse the location from Endpoint resource.

Parameter

Name	Description
endpointName	string A fully-qualified path representing Endpoint resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

Parse the location from EntityType resource.

Parameter

Name	Description
entityTypeName	string A fully-qualified path representing EntityType resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

Parse the location from Execution resource.

Parameter

Name	Description
executionName	string A fully-qualified path representing Execution resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

Parse the location from Feature resource.

Parameter

Name	Description
featureName	string A fully-qualified path representing Feature resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

Parse the location from Featurestore resource.

Parameter

Name	Description
featurestoreName	string A fully-qualified path representing Featurestore resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the location from HyperparameterTuningJob resource.

Parameter

Name	Description
hyperparameterTuningJobName	string A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the location from IndexEndpoint resource.

Parameter

Name	Description
indexEndpointName	string A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

Parse the location from Index resource.

Parameter

Name	Description
indexName	string A fully-qualified path representing Index resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter

Name	Description
locationName	string A fully-qualified path representing Location resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the location from MetadataSchema resource.

Parameter

Name	Description
metadataSchemaName	string A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the location from MetadataStore resource.

Parameter

Name	Description
metadataStoreName	string A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the location from ModelDeploymentMonitoringJob resource.

Parameter

Name	Description
modelDeploymentMonitoringJobName	string A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the location from ModelEvaluationSlice resource.

Parameter

Name	Description
modelEvaluationSliceName	string A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

Parse the location from PipelineJob resource.

Parameter

Name	Description
pipelineJobName	string A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the location from SpecialistPool resource.

Parameter

Name	Description
specialistPoolName	string A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

Parse the location from Study resource.

Parameter

Name	Description
studyName	string A fully-qualified path representing Study resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the location from TensorboardExperiment resource.

Parameter

Name	Description
tensorboardExperimentName	string A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

Parse the location from Tensorboard resource.

Parameter

Name	Description
tensorboardName	string A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the location from TensorboardRun resource.

Parameter

Name	Description
tensorboardRunName	string A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the location from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the location from TrainingPipeline resource.

Parameter

Name	Description
trainingPipelineName	string A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

Parse the location from Trial resource.

Parameter

Name	Description
trialName	string A fully-qualified path representing Trial resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_schema from MetadataSchema resource.

Parameter

Name	Description
metadataSchemaName	string A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_schema.

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

Parse the metadata_store from Artifact resource.

Parameter

Name	Description
artifactName	string A fully-qualified path representing Artifact resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_store.

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

Parse the metadata_store from Context resource.

Parameter

Name	Description
contextName	string A fully-qualified path representing Context resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_store.

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

Parse the metadata_store from Execution resource.

Parameter

Name	Description
executionName	string A fully-qualified path representing Execution resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_store from MetadataSchema resource.

Parameter

Name	Description
metadataSchemaName	string A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the metadata_store from MetadataStore resource.

Parameter

Name	Description
metadataStoreName	string A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
string | number	{string} A string representing the metadata_store.

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the model_deployment_monitoring_job from ModelDeploymentMonitoringJob resource.

Parameter

Name	Description
modelDeploymentMonitoringJobName	string A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
string | number	{string} A string representing the model_deployment_monitoring_job.

matchModelFromModelEvaluationName(modelEvaluationName)

matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the model.

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the model from ModelEvaluationSlice resource.

Parameter

Name	Description
modelEvaluationSliceName	string A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
string | number	{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the model.

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

Parse the pipeline_job from PipelineJob resource.

Parameter

Name	Description
pipelineJobName	string A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
string | number	{string} A string representing the pipeline_job.

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

Parse the project from Annotation resource.

Parameter

Name	Description
annotationName	string A fully-qualified path representing Annotation resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

Parse the project from Artifact resource.

Parameter

Name	Description
artifactName	string A fully-qualified path representing Artifact resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the project from BatchPredictionJob resource.

Parameter

Name	Description
batchPredictionJobName	string A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

Parse the project from Context resource.

Parameter

Name	Description
contextName	string A fully-qualified path representing Context resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

Parse the project from CustomJob resource.

Parameter

Name	Description
customJobName	string A fully-qualified path representing CustomJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

Parse the project from DataItem resource.

Parameter

Name	Description
dataItemName	string A fully-qualified path representing DataItem resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the project from DataLabelingJob resource.

Parameter

Name	Description
dataLabelingJobName	string A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromEndpointName(endpointName)

matchProjectFromEndpointName(endpointName: string): string | number;

Parse the project from Endpoint resource.

Parameter

Name	Description
endpointName	string A fully-qualified path representing Endpoint resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

Parse the project from EntityType resource.

Parameter

Name	Description
entityTypeName	string A fully-qualified path representing EntityType resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

Parse the project from Execution resource.

Parameter

Name	Description
executionName	string A fully-qualified path representing Execution resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromFeatureName(featureName)

matchProjectFromFeatureName(featureName: string): string | number;

Parse the project from Feature resource.

Parameter

Name	Description
featureName	string A fully-qualified path representing Feature resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

Parse the project from Featurestore resource.

Parameter

Name	Description
featurestoreName	string A fully-qualified path representing Featurestore resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the project from HyperparameterTuningJob resource.

Parameter

Name	Description
hyperparameterTuningJobName	string A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the project from IndexEndpoint resource.

Parameter

Name	Description
indexEndpointName	string A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

Parse the project from Index resource.

Parameter

Name	Description
indexName	string A fully-qualified path representing Index resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter

Name	Description
locationName	string A fully-qualified path representing Location resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the project from MetadataSchema resource.

Parameter

Name	Description
metadataSchemaName	string A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the project from MetadataStore resource.

Parameter

Name	Description
metadataStoreName	string A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the project from ModelDeploymentMonitoringJob resource.

Parameter

Name	Description
modelDeploymentMonitoringJobName	string A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the project from ModelEvaluationSlice resource.

Parameter

Name	Description
modelEvaluationSliceName	string A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

Parse the project from PipelineJob resource.

Parameter

Name	Description
pipelineJobName	string A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

Parse the project from Project resource.

Parameter

Name	Description
projectName	string A fully-qualified path representing Project resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the project from SpecialistPool resource.

Parameter

Name	Description
specialistPoolName	string A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

Parse the project from Study resource.

Parameter

Name	Description
studyName	string A fully-qualified path representing Study resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the project from TensorboardExperiment resource.

Parameter

Name	Description
tensorboardExperimentName	string A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

Parse the project from Tensorboard resource.

Parameter

Name	Description
tensorboardName	string A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the project from TensorboardRun resource.

Parameter

Name	Description
tensorboardRunName	string A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the project from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTrainingPipelineName(trainingPipelineName)

matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the project from TrainingPipeline resource.

Parameter

Name	Description
trainingPipelineName	string A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTrialName(trialName)

matchProjectFromTrialName(trialName: string): string | number;

Parse the project from Trial resource.

Parameter

Name	Description
trialName	string A fully-qualified path representing Trial resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchRunFromTensorboardRunName(tensorboardRunName)

matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the run from TensorboardRun resource.

Parameter

Name	Description
tensorboardRunName	string A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
string | number	{string} A string representing the run.

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the run from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the run.

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the slice from ModelEvaluationSlice resource.

Parameter

Name	Description
modelEvaluationSliceName	string A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
string | number	{string} A string representing the slice.

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the specialist_pool from SpecialistPool resource.

Parameter

Name	Description
specialistPoolName	string A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
string | number	{string} A string representing the specialist_pool.

matchStudyFromStudyName(studyName)

matchStudyFromStudyName(studyName: string): string | number;

Parse the study from Study resource.

Parameter

Name	Description
studyName	string A fully-qualified path representing Study resource.

Returns

Type	Description
string | number	{string} A string representing the study.

matchStudyFromTrialName(trialName)

matchStudyFromTrialName(trialName: string): string | number;

Parse the study from Trial resource.

Parameter

Name	Description
trialName	string A fully-qualified path representing Trial resource.

Returns

Type	Description
string | number	{string} A string representing the study.

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the tensorboard from TensorboardExperiment resource.

Parameter

Name	Description
tensorboardExperimentName	string A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
string | number	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardName(tensorboardName)

matchTensorboardFromTensorboardName(tensorboardName: string): string | number;

Parse the tensorboard from Tensorboard resource.

Parameter

Name	Description
tensorboardName	string A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
string | number	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardRunName(tensorboardRunName)

matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the tensorboard from TensorboardRun resource.

Parameter

Name	Description
tensorboardRunName	string A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
string | number	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the tensorboard from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the tensorboard.

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the time_series from TensorboardTimeSeries resource.

Parameter

Name	Description
tensorboardTimeSeriesName	string A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
string | number	{string} A string representing the time_series.

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the training_pipeline from TrainingPipeline resource.

Parameter

Name	Description
trainingPipelineName	string A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
string | number	{string} A string representing the training_pipeline.

matchTrialFromTrialName(trialName)

matchTrialFromTrialName(trialName: string): string | number;

Parse the trial from Trial resource.

Parameter

Name	Description
trialName	string A fully-qualified path representing Trial resource.

Returns

Type	Description
string | number	{string} A string representing the trial.

metadataSchemaPath(project, location, metadataStore, metadataSchema)

metadataSchemaPath(project: string, location: string, metadataStore: string, metadataSchema: string): string;

Return a fully-qualified metadataSchema resource name string.

Parameters

Name	Description
project	string
location	string
metadataStore	string
metadataSchema	string

Returns

Type	Description
string	{string} Resource name string.

metadataStorePath(project, location, metadataStore)

metadataStorePath(project: string, location: string, metadataStore: string): string;

Return a fully-qualified metadataStore resource name string.

Parameters

Name	Description
project	string
location	string
metadataStore	string

Returns

Type	Description
string	{string} Resource name string.

modelDeploymentMonitoringJobPath(project, location, modelDeploymentMonitoringJob)

modelDeploymentMonitoringJobPath(project: string, location: string, modelDeploymentMonitoringJob: string): string;

Return a fully-qualified modelDeploymentMonitoringJob resource name string.

Parameters

Name	Description
project	string
location	string
modelDeploymentMonitoringJob	string

Returns

Type	Description
string	{string} Resource name string.

modelEvaluationPath(project, location, model, evaluation)

modelEvaluationPath(project: string, location: string, model: string, evaluation: string): string;

Return a fully-qualified modelEvaluation resource name string.

Parameters

Name	Description
project	string
location	string
model	string
evaluation	string

Returns

Type	Description
string	{string} Resource name string.

modelEvaluationSlicePath(project, location, model, evaluation, slice)

modelEvaluationSlicePath(project: string, location: string, model: string, evaluation: string, slice: string): string;

Return a fully-qualified modelEvaluationSlice resource name string.

Parameters

Name	Description
project	string
location	string
model	string
evaluation	string
slice	string

Returns

Type	Description
string	{string} Resource name string.

modelPath(project, location, model)

modelPath(project: string, location: string, model: string): string;

Return a fully-qualified model resource name string.

Parameters

Name	Description
project	string
location	string
model	string

Returns

Type	Description
string	{string} Resource name string.

pipelineJobPath(project, location, pipelineJob)

pipelineJobPath(project: string, location: string, pipelineJob: string): string;

Return a fully-qualified pipelineJob resource name string.

Parameters

Name	Description
project	string
location	string
pipelineJob	string

Returns

Type	Description
string	{string} Resource name string.

projectPath(project)

projectPath(project: string): string;

Return a fully-qualified project resource name string.

Parameter

Name	Description
project	string

Returns

Type	Description
string	{string} Resource name string.

searchFeatures(request, options)

searchFeatures(request?: protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeature[],
        protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest | null,
        protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse
    ]>;

Searches Features matching a query in a given project.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[ protos.google.cloud.aiplatform.v1.IFeature[], protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest | null, protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Feature]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using searchFeaturesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

searchFeatures(request, options, callback)

searchFeatures(request: protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>

Returns

Type	Description
void

searchFeatures(request, callback)

searchFeatures(request: protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest
callback	PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>

Returns

Type	Description
void

searchFeaturesAsync(request, options)

searchFeaturesAsync(request?: protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature>;

Equivalent to searchFeatures, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Feature]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to search Features.
   *  Format:
   *  `projects/{project}/locations/{location}`
   */
  // const location = 'abc123'
  /**
   *  Query string that is a conjunction of field-restricted queries and/or
   *  field-restricted filters.  Field-restricted queries and filters can be
   *  combined using `AND` to form a conjunction.
   *  A field query is in the form FIELD:QUERY. This implicitly checks if QUERY
   *  exists as a substring within Feature's FIELD. The QUERY
   *  and the FIELD are converted to a sequence of words (i.e. tokens) for
   *  comparison. This is done by:
   *    * Removing leading/trailing whitespace and tokenizing the search value.
   *    Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore
   *    `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated
   *    as a wildcard that matches characters within a token.
   *    * Ignoring case.
   *    * Prepending an asterisk to the first and appending an asterisk to the
   *    last token in QUERY.
   *  A QUERY must be either a singular token or a phrase. A phrase is one or
   *  multiple words enclosed in double quotation marks ("). With phrases, the
   *  order of the words is important. Words in the phrase must be matching in
   *  order and consecutively.
   *  Supported FIELDs for field-restricted queries:
   *  * `feature_id`
   *  * `description`
   *  * `entity_type_id`
   *  Examples:
   *  * `feature_id: foo` --> Matches a Feature with ID containing the substring
   *  `foo` (eg. `foo`, `foofeature`, `barfoo`).
   *  * `feature_id: foo*feature` --> Matches a Feature with ID containing the
   *  substring `foo*feature` (eg. `foobarfeature`).
   *  * `feature_id: foo AND description: bar` --> Matches a Feature with ID
   *  containing the substring `foo` and description containing the substring
   *  `bar`.
   *  Besides field queries, the following exact-match filters are
   *  supported. The exact-match filters do not support wildcards. Unlike
   *  field-restricted queries, exact-match filters are case-sensitive.
   *  * `feature_id`: Supports = comparisons.
   *  * `description`: Supports = comparisons. Multi-token filters should be
   *  enclosed in quotes.
   *  * `entity_type_id`: Supports = comparisons.
   *  * `value_type`: Supports = and != comparisons.
   *  * `labels`: Supports key-value equality as well as key presence.
   *  * `featurestore_id`: Supports = comparisons.
   *  Examples:
   *  * `description = "foo bar"` --> Any Feature with description exactly equal
   *  to `foo bar`
   *  * `value_type = DOUBLE` --> Features whose type is DOUBLE.
   *  * `labels.active = yes AND labels.env = prod` --> Features having both
   *      (active: yes) and (env: prod) labels.
   *  * `labels.env: *` --> Any Feature which has a label with `env` as the
   *    key.
   */
  // const query = 'abc123'
  /**
   *  The maximum number of Features to return. The service may return fewer
   *  than this value. If unspecified, at most 100 Features will be returned.
   *  The maximum value is 100; any value greater than 100 will be coerced to
   *  100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  FeaturestoreService.SearchFeatures google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.SearchFeatures google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures, except `page_size`, must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callSearchFeatures() {
    // Construct request
    const request = {
      location,
    };

    // Run request
    const iterable = await aiplatformClient.searchFeaturesAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callSearchFeatures();

searchFeaturesStream(request, options)

searchFeaturesStream(request?: protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.ISearchFeaturesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [Feature] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using searchFeaturesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

specialistPoolPath(project, location, specialistPool)

specialistPoolPath(project: string, location: string, specialistPool: string): string;

Return a fully-qualified specialistPool resource name string.

Parameters

Name	Description
project	string
location	string
specialistPool	string

Returns

Type	Description
string	{string} Resource name string.

studyPath(project, location, study)

studyPath(project: string, location: string, study: string): string;

Return a fully-qualified study resource name string.

Parameters

Name	Description
project	string
location	string
study	string

Returns

Type	Description
string	{string} Resource name string.

tensorboardExperimentPath(project, location, tensorboard, experiment)

tensorboardExperimentPath(project: string, location: string, tensorboard: string, experiment: string): string;

Return a fully-qualified tensorboardExperiment resource name string.

Parameters

Name	Description
project	string
location	string
tensorboard	string
experiment	string

Returns

Type	Description
string	{string} Resource name string.

tensorboardPath(project, location, tensorboard)

tensorboardPath(project: string, location: string, tensorboard: string): string;

Return a fully-qualified tensorboard resource name string.

Parameters

Name	Description
project	string
location	string
tensorboard	string

Returns

Type	Description
string	{string} Resource name string.

tensorboardRunPath(project, location, tensorboard, experiment, run)

tensorboardRunPath(project: string, location: string, tensorboard: string, experiment: string, run: string): string;

Return a fully-qualified tensorboardRun resource name string.

Parameters

Name	Description
project	string
location	string
tensorboard	string
experiment	string
run	string

Returns

Type	Description
string	{string} Resource name string.

tensorboardTimeSeriesPath(project, location, tensorboard, experiment, run, timeSeries)

tensorboardTimeSeriesPath(project: string, location: string, tensorboard: string, experiment: string, run: string, timeSeries: string): string;

Return a fully-qualified tensorboardTimeSeries resource name string.

Parameters

Name	Description
project	string
location	string
tensorboard	string
experiment	string
run	string
timeSeries	string

Returns

Type	Description
string	{string} Resource name string.

trainingPipelinePath(project, location, trainingPipeline)

trainingPipelinePath(project: string, location: string, trainingPipeline: string): string;

Return a fully-qualified trainingPipeline resource name string.

Parameters

Name	Description
project	string
location	string
trainingPipeline	string

Returns

Type	Description
string	{string} Resource name string.

trialPath(project, location, study, trial)

trialPath(project: string, location: string, study: string, trial: string): string;

Return a fully-qualified trial resource name string.

Parameters

Name	Description
project	string
location	string
study	string
trial	string

Returns

Type	Description
string	{string} Resource name string.

updateEntityType(request, options)

updateEntityType(request?: protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IEntityType,
        protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | undefined,
        {} | undefined
    ]>;

Updates the parameters of a single EntityType.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [EntityType]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The EntityType's `name` field is used to identify the EntityType to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const entityType = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  EntityType resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `description`
   *    * `labels`
   *    * `monitoring_config.snapshot_analysis.disabled`
   *    * `monitoring_config.snapshot_analysis.monitoring_interval`
   */
  // const updateMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callUpdateEntityType() {
    // Construct request
    const request = {
      entityType,
    };

    // Run request
    const response = await aiplatformClient.updateEntityType(request);
    console.log(response);
  }

  callUpdateEntityType();

updateEntityType(request, options, callback)

updateEntityType(request: protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest
options	CallOptions
callback	Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateEntityType(request, callback)

updateEntityType(request: protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest
callback	Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IUpdateEntityTypeRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateFeature(request, options)

updateFeature(request?: protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IFeature,
        protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | undefined,
        {} | undefined
    ]>;

Updates the parameters of a single Feature.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Feature]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The Feature's `name` field is used to identify the Feature to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
   */
  // const feature = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  Features resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `description`
   *    * `labels`
   *    * `monitoring_config.snapshot_analysis.disabled`
   *    * `monitoring_config.snapshot_analysis.monitoring_interval`
   */
  // const updateMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callUpdateFeature() {
    // Construct request
    const request = {
      feature,
    };

    // Run request
    const response = await aiplatformClient.updateFeature(request);
    console.log(response);
  }

  callUpdateFeature();

updateFeature(request, options, callback)

updateFeature(request: protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest
options	CallOptions
callback	Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateFeature(request, callback)

updateFeature(request: protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest
callback	Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IUpdateFeatureRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateFeaturestore(request, options)

updateFeaturestore(request?: protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Updates the parameters of a single Featurestore.

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The Featurestore's `name` field is used to identify the Featurestore to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}`
   */
  // const featurestore = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  Featurestore resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `labels`
   *    * `online_serving_config.fixed_node_count`
   */
  // const updateMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new FeaturestoreServiceClient();

  async function callUpdateFeaturestore() {
    // Construct request
    const request = {
      featurestore,
    };

    // Run request
    const [operation] = await aiplatformClient.updateFeaturestore(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callUpdateFeaturestore();

updateFeaturestore(request, options, callback)

updateFeaturestore(request: protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateFeaturestore(request, callback)

updateFeaturestore(request: protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreRequest
callback	Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void