Class v1beta1.FeaturestoreServiceClient (2.3.0)

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The service that handles CRUD and List for resources for Featurestore. v1beta1

Package

@google-cloud/aiplatform

Constructors

(constructor)(opts, gaxInstance)

constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);

Construct an instance of FeaturestoreServiceClient.

Parameters
NameDescription
opts ClientOptions
gaxInstance typeof gax | typeof gax.fallback

: loaded instance of google-gax. Useful if you need to avoid loading the default gRPC version and want to use the fallback HTTP implementation. Load only fallback version and pass it to the constructor: ``` const gax = require('google-gax/build/src/fallback'); // avoids loading google-gax with gRPC const client = new FeaturestoreServiceClient({fallback: 'rest'}, gax); ```

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;
    }>;

iamClient

iamClient: IamClient;

innerApiCalls

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

locationsClient

locationsClient: LocationsClient;

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
NameDescription
project string
location string
dataset string
dataItem string
annotation string
Returns
TypeDescription
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
NameDescription
project string
location string
dataset string
annotationSpec string
Returns
TypeDescription
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
NameDescription
project string
location string
metadataStore string
artifact string
Returns
TypeDescription
string

{string} Resource name string.

batchCreateFeatures(request, options)

batchCreateFeatures(request?: protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a batch of Features in a given EntityType.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IBatchCreateFeaturesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchCreateFeatures(request, callback)

batchCreateFeatures(request: protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchPredictionJobPath(project, location, batchPredictionJob)

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

Return a fully-qualified batchPredictionJob resource name string.

Parameters
NameDescription
project string
location string
batchPredictionJob string
Returns
TypeDescription
string

{string} Resource name string.

batchReadFeatureValues(request, options)

batchReadFeatureValues(request?: protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IBatchReadFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchReadFeatureValues(request, callback)

batchReadFeatureValues(request: protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

cancelOperation(request, options, callback)

cancelOperation(request: protos.google.longrunning.CancelOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>, callback?: Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>): Promise<protos.google.protobuf.Empty>;

Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED. Clients can use or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an value with a of 1, corresponding to Code.CANCELLED.

Parameters
NameDescription
request protos.google.longrunning.CancelOperationRequest

The request object that will be sent.

options gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.

callback Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>

The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call.

Returns
TypeDescription
Promise<protos.google.protobuf.Empty>
Example

const client = longrunning.operationsClient();
await client.cancelOperation({name: ''});

checkBatchCreateFeaturesProgress(name)

checkBatchCreateFeaturesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.BatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.BatchCreateFeaturesOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.BatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.BatchReadFeatureValuesOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.EntityType, protos.google.cloud.aiplatform.v1beta1.CreateEntityTypeOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.EntityType, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.Feature, protos.google.cloud.aiplatform.v1beta1.CreateFeatureOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Feature, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.Featurestore, protos.google.cloud.aiplatform.v1beta1.CreateFeaturestoreOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Featurestore, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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();

checkDeleteFeatureValuesProgress(name)

checkDeleteFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.DeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.DeleteFeatureValuesOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.DeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.DeleteFeatureValuesOperationMetadata>>

{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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Select feature values to be deleted by specifying entities.
   */
  // const selectEntity = {}
  /**
   *  Select feature values to be deleted by specifying time range and
   *  features.
   */
  // const selectTimeRangeAndFeature = {}
  /**
   *  Required. The resource name of the EntityType grouping the Features for which values
   *  are being deleted from. Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
   */
  // const entityType = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1beta1;

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

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

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

  callDeleteFeatureValues();

checkExportFeatureValuesProgress(name)

checkExportFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.ExportFeatureValuesOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.ImportFeatureValuesOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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
  /**
   *  If true, API doesn't start ingestion analysis pipeline.
   */
  // const disableIngestionAnalysis = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // 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.v1beta1.Featurestore, protos.google.cloud.aiplatform.v1beta1.UpdateFeaturestoreOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Featurestore, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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`
   *    * `online_serving_config.scaling`
   */
  // const updateMask = {}

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // 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
TypeDescription
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
NameDescription
project string
location string
metadataStore string
context string
Returns
TypeDescription
string

{string} Resource name string.

createEntityType(request, options)

createEntityType(request?: protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new EntityType in a given Featurestore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.ICreateEntityTypeRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createEntityType(request, callback)

createEntityType(request: protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createFeature(request, options)

createFeature(request?: protos.google.cloud.aiplatform.v1beta1.ICreateFeatureRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.ICreateFeatureOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new Feature in a given EntityType.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeatureRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.ICreateFeatureRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeatureRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createFeature(request, callback)

createFeature(request: protos.google.cloud.aiplatform.v1beta1.ICreateFeatureRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeatureRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createFeaturestore(request, options)

createFeaturestore(request?: protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a new Featurestore in a given project and location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.ICreateFeaturestoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createFeaturestore(request, callback)

createFeaturestore(request: protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

customJobPath(project, location, customJob)

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

Return a fully-qualified customJob resource name string.

Parameters
NameDescription
project string
location string
customJob string
Returns
TypeDescription
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
NameDescription
project string
location string
dataset string
dataItem string
Returns
TypeDescription
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
NameDescription
project string
location string
dataLabelingJob string
Returns
TypeDescription
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
NameDescription
project string
location string
dataset string
Returns
TypeDescription
string

{string} Resource name string.

deleteEntityType(request, options)

deleteEntityType(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteEntityTypeRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteEntityTypeRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IDeleteEntityTypeRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteEntityTypeRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteEntityType(request, callback)

deleteEntityType(request: protos.google.cloud.aiplatform.v1beta1.IDeleteEntityTypeRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteEntityTypeRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeature(request, options)

deleteFeature(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a single Feature.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IDeleteFeatureRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeature(request, callback)

deleteFeature(request: protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeaturestore(request, options)

deleteFeaturestore(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteFeaturestoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeaturestoreRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IDeleteFeaturestoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeaturestoreRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeaturestore(request, callback)

deleteFeaturestore(request: protos.google.cloud.aiplatform.v1beta1.IDeleteFeaturestoreRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeaturestoreRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeatureValues(request, options)

deleteFeatureValues(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Delete Feature values from Featurestore.

The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done.

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>, 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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Select feature values to be deleted by specifying entities.
   */
  // const selectEntity = {}
  /**
   *  Select feature values to be deleted by specifying time range and
   *  features.
   */
  // const selectTimeRangeAndFeature = {}
  /**
   *  Required. The resource name of the EntityType grouping the Features for which values
   *  are being deleted from. Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
   */
  // const entityType = 'abc123'

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1beta1;

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

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

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

  callDeleteFeatureValues();

deleteFeatureValues(request, options, callback)

deleteFeatureValues(request: protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteFeatureValues(request, callback)

deleteFeatureValues(request: protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteOperation(request, options, callback)

deleteOperation(request: protos.google.longrunning.DeleteOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>): Promise<protos.google.protobuf.Empty>;

Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
NameDescription
request protos.google.longrunning.DeleteOperationRequest

The request object that will be sent.

options gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.

callback Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>

The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call.

Returns
TypeDescription
Promise<protos.google.protobuf.Empty>
Example

const client = longrunning.operationsClient();
await client.deleteOperation({name: ''});

deploymentResourcePoolPath(project, location, deploymentResourcePool)

deploymentResourcePoolPath(project: string, location: string, deploymentResourcePool: string): string;

Return a fully-qualified deploymentResourcePool resource name string.

Parameters
NameDescription
project string
location string
deploymentResourcePool string
Returns
TypeDescription
string

{string} Resource name string.

endpointPath(project, location, endpoint)

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

Return a fully-qualified endpoint resource name string.

Parameters
NameDescription
project string
location string
endpoint string
Returns
TypeDescription
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
NameDescription
project string
location string
featurestore string
entityType string
Returns
TypeDescription
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
NameDescription
project string
location string
metadataStore string
execution string
Returns
TypeDescription
string

{string} Resource name string.

exportFeatureValues(request, options)

exportFeatureValues(request?: protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IExportFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

exportFeatureValues(request, callback)

exportFeatureValues(request: protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
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
NameDescription
project string
location string
featurestore string
entityType string
feature string
Returns
TypeDescription
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
NameDescription
project string
location string
featurestore string
Returns
TypeDescription
string

{string} Resource name string.

getEntityType(request, options)

getEntityType(request?: protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IEntityType,
        protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest | undefined,
        {} | undefined
    ]>;

Gets details of a single EntityType.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IGetEntityTypeRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getEntityType(request, callback)

getEntityType(request: protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IEntityType, protos.google.cloud.aiplatform.v1beta1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getFeature(request, options)

getFeature(request?: protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IFeature,
        protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest | undefined,
        {} | undefined
    ]>;

Gets details of a single Feature.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IGetFeatureRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getFeature(request, callback)

getFeature(request: protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IFeature, protos.google.cloud.aiplatform.v1beta1.IGetFeatureRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getFeaturestore(request, options)

getFeaturestore(request?: protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IFeaturestore,
        (protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest | undefined),
        {} | undefined
    ]>;

Gets details of a single Featurestore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IFeaturestore, (protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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').v1beta1;

  // 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.v1beta1.IGetFeaturestoreRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getFeaturestore(request, callback)

getFeaturestore(request: protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IFeaturestore, protos.google.cloud.aiplatform.v1beta1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getIamPolicy(request, options, callback)

getIamPolicy(request: IamProtos.google.iam.v1.GetIamPolicyRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.Policy>;

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

Parameters
NameDescription
request IamProtos.google.iam.v1.GetIamPolicyRequest

The request object that will be sent.

options gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details.

callback Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>

The function which will be called with the result of the API call.

The second parameter to the callback is an object representing [Policy].

Returns
TypeDescription
Promise<IamProtos.google.iam.v1.Policy>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Policy]. The promise has a method named "cancel" which cancels the ongoing API call.

getLocation(request, options, callback)

getLocation(request: LocationProtos.google.cloud.location.IGetLocationRequest, options?: gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>, callback?: Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>): Promise<LocationProtos.google.cloud.location.ILocation>;

Gets information about a location.

Parameters
NameDescription
request LocationProtos.google.cloud.location.IGetLocationRequest

The request object that will be sent.

options gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>

Call options. See CallOptions for more details.

callback Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
Promise<LocationProtos.google.cloud.location.ILocation>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Location]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

const [response] = await client.getLocation(request);

getOperation(request, options, callback)

getOperation(request: protos.google.longrunning.GetOperationRequest, options?: gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>): Promise<[protos.google.longrunning.Operation]>;

Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.

Parameters
NameDescription
request protos.google.longrunning.GetOperationRequest

The request object that will be sent.

options gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.

callback Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>

The function which will be called with the result of the API call.

The second parameter to the callback is an object representing [google.longrunning.Operation]. {Promise} - The promise which resolves to an array. The first element of the array is an object representing [google.longrunning.Operation]. The promise has a method named "cancel" which cancels the ongoing API call.

Returns
TypeDescription
Promise<[protos.google.longrunning.Operation]>
Example

const client = longrunning.operationsClient();
const name = '';
const [response] = await client.getOperation({name});
// doThingsWith(response)

getProjectId()

getProjectId(): Promise<string>;
Returns
TypeDescription
Promise<string>

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;
Parameter
NameDescription
callback Callback<string, undefined, undefined>
Returns
TypeDescription
void

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

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

Return a fully-qualified hyperparameterTuningJob resource name string.

Parameters
NameDescription
project string
location string
hyperparameterTuningJob string
Returns
TypeDescription
string

{string} Resource name string.

importFeatureValues(request, options)

importFeatureValues(request?: protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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
  /**
   *  If true, API doesn't start ingestion analysis pipeline.
   */
  // const disableIngestionAnalysis = true

  // Imports the Aiplatform library
  const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // 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.v1beta1.IImportFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

importFeatureValues(request, callback)

importFeatureValues(request: protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1beta1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

indexEndpointPath(project, location, indexEndpoint)

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

Return a fully-qualified indexEndpoint resource name string.

Parameters
NameDescription
project string
location string
indexEndpoint string
Returns
TypeDescription
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
NameDescription
project string
location string
index string
Returns
TypeDescription
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
TypeDescription
Promise<{ [name: string]: Function; }>

{Promise} A promise that resolves to an authenticated service stub.

listEntityTypes(request, options)

listEntityTypes(request?: protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IEntityType[],
        protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListEntityTypesResponse
    ]>;

Lists EntityTypes in a given Featurestore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IEntityType[], protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest | null, protos.google.cloud.aiplatform.v1beta1.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.v1beta1.IListEntityTypesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1beta1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IEntityType>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1beta1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IEntityType>
Returns
TypeDescription
void

listEntityTypes(request, callback)

listEntityTypes(request: protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1beta1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IEntityType>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1beta1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IEntityType>
Returns
TypeDescription
void

listEntityTypesAsync(request, options)

listEntityTypesAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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.v1beta1.FeaturestoreService.ListEntityTypes  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListEntityTypes google.cloud.aiplatform.v1beta1.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').v1beta1;

  // 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.v1beta1.IListEntityTypesRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListEntityTypesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.v1beta1.IListFeaturesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IFeature[],
        protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListFeaturesResponse
    ]>;

Lists Features in a given EntityType.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IFeature[], protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest | null, protos.google.cloud.aiplatform.v1beta1.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.v1beta1.IListFeaturesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>
Returns
TypeDescription
void

listFeatures(request, callback)

listFeatures(request: protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>
Returns
TypeDescription
void

listFeaturesAsync(request, options)

listFeaturesAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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.v1beta1.FeaturestoreService.ListFeatures  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeatures google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.listfeaturesrequest.latest_stats_count,="" return="" all="" *="" existing="" stats.="" */="" const="" lateststatscount="1234" imports="" the="" aiplatform="" library="" const="" {featurestoreserviceclient}="require('@google-cloud/aiplatform').v1beta1;" 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.v1beta1.IListFeaturesRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.v1beta1.IListFeaturestoresRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IFeaturestore[],
        protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresResponse
    ]>;

Lists Featurestores in a given project and location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IFeaturestore[], protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest | null, protos.google.cloud.aiplatform.v1beta1.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.v1beta1.IListFeaturestoresRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeaturestore>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeaturestore>
Returns
TypeDescription
void

listFeaturestores(request, callback)

listFeaturestores(request: protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeaturestore>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeaturestore>
Returns
TypeDescription
void

listFeaturestoresAsync(request, options)

listFeaturestoresAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.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

  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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.v1beta1.FeaturestoreService.ListFeaturestores  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeaturestores google.cloud.aiplatform.v1beta1.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').v1beta1;

  // 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.v1beta1.IListFeaturestoresRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListFeaturestoresRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.

listLocationsAsync(request, options)

listLocationsAsync(request: LocationProtos.google.cloud.location.IListLocationsRequest, options?: CallOptions): AsyncIterable<LocationProtos.google.cloud.location.ILocation>;

Lists information about the supported locations for this service. Returns an iterable object.

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

Parameters
NameDescription
request LocationProtos.google.cloud.location.IListLocationsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<LocationProtos.google.cloud.location.ILocation>

{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 [Location]. 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

const iterable = client.listLocationsAsync(request);
for await (const response of iterable) {
  // process response
}

listOperationsAsync(request, options)

listOperationsAsync(request: protos.google.longrunning.ListOperationsRequest, options?: gax.CallOptions): AsyncIterable<protos.google.longrunning.ListOperationsResponse>;

Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns UNIMPLEMENTED. Returns an iterable object.

For-await-of syntax is used with the iterable to recursively get response element on-demand.

Parameters
NameDescription
request protos.google.longrunning.ListOperationsRequest

The request object that will be sent.

options gax.CallOptions

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.

Returns
TypeDescription
AsyncIterable<protos.google.longrunning.ListOperationsResponse>

{Object} An iterable Object that conforms to https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols.

Example

const client = longrunning.operationsClient();
for await (const response of client.listOperationsAsync(request));
// doThingsWith(response)

locationPath(project, location)

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

Return a fully-qualified location resource name string.

Parameters
NameDescription
project string
location string
Returns
TypeDescription
string

{string} Resource name string.

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

Parse the annotation from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation_spec.

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

Parse the artifact from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the artifact.

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the batch_prediction_job from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the batch_prediction_job.

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

Parse the context from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the context.

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

Parse the custom_job from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the custom_job.

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

Parse the data_item from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the data_item.

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

Parse the data_item from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
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
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the data_labeling_job.

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

Parse the dataset from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

Parse the dataset from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromSavedQueryName(savedQueryName)

matchDatasetFromSavedQueryName(savedQueryName: string): string | number;

Parse the dataset from SavedQuery resource.

Parameter
NameDescription
savedQueryName string

A fully-qualified path representing SavedQuery resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the deployment_resource_pool from DeploymentResourcePool resource.

Parameter
NameDescription
deploymentResourcePoolName string

A fully-qualified path representing DeploymentResourcePool resource.

Returns
TypeDescription
string | number

{string} A string representing the deployment_resource_pool.

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

Parse the endpoint from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the endpoint.

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

Parse the entity_type from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: string): string | number;

Parse the entity_type from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the evaluation from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the evaluation from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

Parse the execution from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the execution.

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the experiment from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the experiment from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the experiment from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

Parse the feature from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature.

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

Parse the featurestore from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

Parse the featurestore from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

Parse the featurestore from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
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
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the index_endpoint.

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

Parse the index from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the index.

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

Parse the location from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

Parse the location from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the location from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

Parse the location from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

Parse the location from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

Parse the location from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the location from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the location from DeploymentResourcePool resource.

Parameter
NameDescription
deploymentResourcePoolName string

A fully-qualified path representing DeploymentResourcePool resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

Parse the location from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

Parse the location from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

Parse the location from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

Parse the location from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

Parse the location from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the location from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the location from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

Parse the location from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the location from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the location from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the location from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the location from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

Parse the location from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromSavedQueryName(savedQueryName)

matchLocationFromSavedQueryName(savedQueryName: string): string | number;

Parse the location from SavedQuery resource.

Parameter
NameDescription
savedQueryName string

A fully-qualified path representing SavedQuery resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the location from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

Parse the location from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the location from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

Parse the location from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the location from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the location from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the location from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

Parse the location from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_schema from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_schema.

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

Parse the metadata_store from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

Parse the metadata_store from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

Parse the metadata_store from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_store from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the metadata_store from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
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
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
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
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the model from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

Parse the pipeline_job from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the pipeline_job.

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

Parse the project from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

Parse the project from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the project from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | numb