Class v1beta1.FeaturestoreServiceClient (3.13.0)

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 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: true}, gax); ```

Properties

apiEndpoint

get apiEndpoint(): string;

The DNS address for this API service.

apiEndpoint

static get apiEndpoint(): string;

The DNS address for this API service - same as servicePath.

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.

universeDomain

get universeDomain(): string;

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 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 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 = [1,2,3,4]

  // 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 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 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 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 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 = [1,2,3,4]
  /**
   *  Required. Specifies EntityType grouping Features to read values of and
   *  settings.
   */
  // const entityTypeSpecs = [1,2,3,4]
  /**
   *  Optional. Excludes Feature values with feature generation timestamp before
   *  this timestamp. If not set, retrieve oldest values kept in Feature Store.
   *  Timestamp, if present, must not have higher than millisecond precision.
   */
  // const startTime = {}

  // 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 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 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 CancelOperationRequest

The request object that will be sent.

options 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 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 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 = [1,2,3,4]

  // 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 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 = [1,2,3,4]
  /**
   *  Required. Specifies EntityType grouping Features to read values of and
   *  settings.
   */
  // const entityTypeSpecs = [1,2,3,4]
  /**
   *  Optional. Excludes Feature values with feature generation timestamp before
   *  this timestamp. If not set, retrieve oldest values kept in Feature Store.
   *  Timestamp, if present, must not have higher than millisecond precision.
   */
  // const startTime = {}

  // 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 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 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 or FeatureGroup to create a
   *  Feature. Format for entity_type as parent:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   *  Format for feature_group as parent:
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}`
   */
  // 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 128 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within an EntityType/FeatureGroup.
   */
  // 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 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 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 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}`
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}/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 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 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 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 = [1,2,3,4]

  // 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 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 = [1,2,3,4]
  /**
   *  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 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`
   *    * `online_storage_ttl_days`
   */
  // 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 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 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 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 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 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 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 or FeatureGroup to create a
   *  Feature. Format for entity_type as parent:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   *  Format for feature_group as parent:
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}`
   */
  // 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 128 characters, and valid characters are
   *  `[a-z0-9_]`. The first character cannot be a number.
   *  The value must be unique within an EntityType/FeatureGroup.
   */
  // 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 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 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 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 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 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 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.

datasetVersionPath(project, location, dataset, datasetVersion)

datasetVersionPath(project: string, location: string, dataset: string, datasetVersion: string): string;

Return a fully-qualified datasetVersion resource name string.

Parameters
NameDescription
project string
location string
dataset string
datasetVersion 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 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 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 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 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 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 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}`
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}/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 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 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 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 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 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 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 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 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 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 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 DeleteOperationRequest

The request object that will be sent.

options 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 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.

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 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 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 = [1,2,3,4]

  // 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 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 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

featureGroupPath(project, location, featureGroup)

featureGroupPath(project: string, location: string, featureGroup: string): string;

Return a fully-qualified featureGroup resource name string.

Parameters
NameDescription
project string
location string
featureGroup string
Returns
TypeDescription
string

{string} Resource name string.

featureOnlineStorePath(project, location, featureOnlineStore)

featureOnlineStorePath(project: string, location: string, featureOnlineStore: string): string;

Return a fully-qualified featureOnlineStore resource name string.

Parameters
NameDescription
project string
location string
featureOnlineStore 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.

featureViewPath(project, location, featureOnlineStore, featureView)

featureViewPath(project: string, location: string, featureOnlineStore: string, featureView: string): string;

Return a fully-qualified featureView resource name string.

Parameters
NameDescription
project string
location string
featureOnlineStore string
featureView string
Returns
TypeDescription
string

{string} Resource name string.

featureViewSyncPath(project, location, featureOnlineStore, featureView)

featureViewSyncPath(project: string, location: string, featureOnlineStore: string, featureView: string): string;

Return a fully-qualified featureViewSync resource name string.

Parameters
NameDescription
project string
location string
featureOnlineStore string
featureView 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 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 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 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 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 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 . Please see the documentation 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 for entity_type as parent:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   *  Format for feature_group as parent:
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}`
   */
  // 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 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 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 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 . Please see the documentation 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 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 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 CallOptions | Callback<google.iam.v1.Policy, 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 for the details.

callback Callback<google.iam.v1.Policy, 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 .

Returns
TypeDescription
Promise<[google.iam.v1.Policy]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 CallOptions | Callback<google.cloud.location.ILocation, google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>

Call options. See CallOptions for more details.

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

{Promise} - The promise which resolves to an array. The first element of the array is an object representing . Please see the documentation 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 GetOperationRequest

The request object that will be sent.

options 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 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 . {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 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 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 = [1,2,3,4]
  /**
   *  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 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 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 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 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 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 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 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. 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 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 = 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 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 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 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 . 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 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 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 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 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. When you iterate the returned iterable, each element will be an object representing . 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 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 for entity_type as parent:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   *  Format for feature_group as parent:
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}`
   */
  // 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 or
   *  FeatureRegistryService.ListFeatures google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatures 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeatures google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures 
   *  or
   *  FeatureRegistryService.ListFeatures google.cloud.aiplatform.v1beta1.FeatureRegistryService.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` (Not supported for FeatureRegistry Feature)
   *    * `create_time`
   *    * `update_time`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  Only applicable for Vertex AI Feature Store (Legacy).
   *  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="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 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 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 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 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 . 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 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 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 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 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. When you iterate the returned iterable, each element will be an object representing . 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 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 = 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 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 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 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<google.cloud.location.ILocation>

{Object} An iterable Object that allows async iteration. When you iterate the returned iterable, each element will be an object representing . 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 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 ListOperationsRequest

The request object that will be sent.

options CallOptions

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

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

{Object} An iterable Object that conforms to 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.

matchDatasetFromDatasetVersionName(datasetVersionName)

matchDatasetFromDatasetVersionName(datasetVersionName: string): string | number;

Parse the dataset from DatasetVersion resource.

Parameter
NameDescription
datasetVersionName string

A fully-qualified path representing DatasetVersion 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.

matchDatasetVersionFromDatasetVersionName(datasetVersionName)

matchDatasetVersionFromDatasetVersionName(datasetVersionName: string): string | number;

Parse the dataset_version from DatasetVersion resource.

Parameter
NameDescription
datasetVersionName string

A fully-qualified path representing DatasetVersion resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset_version.

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.

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName)

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName: string): string | number;

Parse the endpoint from ProjectLocationEndpoint resource.

Parameter
NameDescription
projectLocationEndpointName string

A fully-qualified path representing project_location_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.

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

Parse the entity_type from ProjectLocationFeaturestoreEntityTypeFeature resource.

Parameter
NameDescription
projectLocationFeaturestoreEntityTypeFeatureName string

A fully-qualified path representing project_location_featurestore_entity_type_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.

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

Parse the feature from ProjectLocationFeatureGroupFeature resource.

Parameter
NameDescription
projectLocationFeatureGroupFeatureName string

A fully-qualified path representing project_location_feature_group_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature.

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

Parse the feature from ProjectLocationFeaturestoreEntityTypeFeature resource.

Parameter
NameDescription
projectLocationFeaturestoreEntityTypeFeatureName string

A fully-qualified path representing project_location_featurestore_entity_type_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature.

matchFeatureGroupFromFeatureGroupName(featureGroupName)

matchFeatureGroupFromFeatureGroupName(featureGroupName: string): string | number;

Parse the feature_group from FeatureGroup resource.

Parameter
NameDescription
featureGroupName string

A fully-qualified path representing FeatureGroup resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_group.

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

Parse the feature_group from ProjectLocationFeatureGroupFeature resource.

Parameter
NameDescription
projectLocationFeatureGroupFeatureName string

A fully-qualified path representing project_location_feature_group_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_group.

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName)

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

Parse the feature_online_store from FeatureOnlineStore resource.

Parameter
NameDescription
featureOnlineStoreName string

A fully-qualified path representing FeatureOnlineStore resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_online_store.

matchFeatureOnlineStoreFromFeatureViewName(featureViewName)

matchFeatureOnlineStoreFromFeatureViewName(featureViewName: string): string | number;

Parse the feature_online_store from FeatureView resource.

Parameter
NameDescription
featureViewName string

A fully-qualified path representing FeatureView resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_online_store.

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName)

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName: string): string | number;

Parse the feature_online_store from FeatureViewSync resource.

Parameter
NameDescription
featureViewSyncName string

A fully-qualified path representing FeatureViewSync resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_online_store.

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.

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.

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

Parse the featurestore from ProjectLocationFeaturestoreEntityTypeFeature resource.

Parameter
NameDescription
projectLocationFeaturestoreEntityTypeFeatureName string

A fully-qualified path representing project_location_featurestore_entity_type_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeatureViewFromFeatureViewName(featureViewName)

matchFeatureViewFromFeatureViewName(featureViewName: string): string | number;

Parse the feature_view from FeatureView resource.

Parameter
NameDescription
featureViewName string

A fully-qualified path representing FeatureView resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_view.

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName)

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName: string): string | number;

Parse the feature_view from FeatureViewSync resource.

Parameter
NameDescription
featureViewSyncName string

A fully-qualified path representing FeatureViewSync resource.

Returns
TypeDescription
string | number

{string} A string representing the feature_view.

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.

matchLocationFromDatasetVersionName(datasetVersionName)

matchLocationFromDatasetVersionName(datasetVersionName: string): string | number;

Parse the location from DatasetVersion resource.

Parameter
NameDescription
datasetVersionName string

A fully-qualified path representing DatasetVersion 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.

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.

matchLocationFromFeatureGroupName(featureGroupName)

matchLocationFromFeatureGroupName(featureGroupName: string): string | number;

Parse the location from FeatureGroup resource.

Parameter
NameDescription
featureGroupName string

A fully-qualified path representing FeatureGroup resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName)

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

Parse the location from FeatureOnlineStore resource.

Parameter
NameDescription
featureOnlineStoreName string

A fully-qualified path representing FeatureOnlineStore 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.

matchLocationFromFeatureViewName(featureViewName)

matchLocationFromFeatureViewName(featureViewName: string): string | number;

Parse the location from FeatureView resource.

Parameter
NameDescription
featureViewName string

A fully-qualified path representing FeatureView resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeatureViewSyncName(featureViewSyncName)

matchLocationFromFeatureViewSyncName(featureViewSyncName: string): string | number;

Parse the location from FeatureViewSync resource.

Parameter
NameDescription
featureViewSyncName string

A fully-qualified path representing FeatureViewSync 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.

matchLocationFromNasJobName(nasJobName)

matchLocationFromNasJobName(nasJobName: string): string | number;

Parse the location from NasJob resource.

Parameter
NameDescription
nasJobName string

A fully-qualified path representing NasJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromNasTrialDetailName(nasTrialDetailName)

matchLocationFromNasTrialDetailName(nasTrialDetailName: string): string | number;

Parse the location from NasTrialDetail resource.

Parameter
NameDescription
nasTrialDetailName string

A fully-qualified path representing NasTrialDetail resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromPersistentResourceName(persistentResourceName)

matchLocationFromPersistentResourceName(persistentResourceName: string): string | number;

Parse the location from PersistentResource resource.

Parameter
NameDescription
persistentResourceName string

A fully-qualified path representing PersistentResource 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.

matchLocationFromProjectLocationEndpointName(projectLocationEndpointName)

matchLocationFromProjectLocationEndpointName(projectLocationEndpointName: string): string | number;

Parse the location from ProjectLocationEndpoint resource.

Parameter
NameDescription
projectLocationEndpointName string

A fully-qualified path representing project_location_endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchLocationFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

Parse the location from ProjectLocationFeatureGroupFeature resource.

Parameter
NameDescription
projectLocationFeatureGroupFeatureName string

A fully-qualified path representing project_location_feature_group_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchLocationFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

Parse the location from ProjectLocationFeaturestoreEntityTypeFeature resource.

Parameter
NameDescription
projectLocationFeaturestoreEntityTypeFeatureName string

A fully-qualified path representing project_location_featurestore_entity_type_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromProjectLocationPublisherModelName(projectLocationPublisherModelName)

matchLocationFromProjectLocationPublisherModelName(projectLocationPublisherModelName: string): string | number;

Parse the location from ProjectLocationPublisherModel resource.

Parameter
NameDescription
projectLocationPublisherModelName string

A fully-qualified path representing project_location_publisher_model 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.

matchLocationFromScheduleName(scheduleName)

matchLocationFromScheduleName(scheduleName: string): string | number;

Parse the location from Schedule resource.

Parameter
NameDescription
scheduleName string

A fully-qualified path representing Schedule 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.

matchModelFromProjectLocationPublisherModelName(projectLocationPublisherModelName)

matchModelFromProjectLocationPublisherModelName(projectLocationPublisherModelName: string): string | number;

Parse the model from ProjectLocationPublisherModel resource.

Parameter
NameDescription
projectLocationPublisherModelName string

A fully-qualified path representing project_location_publisher_model resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromPublisherModelName(publisherModelName)

matchModelFromPublisherModelName(publisherModelName: string): string | number;

Parse the model from PublisherModel resource.

Parameter
NameDescription
publisherModelName string

A fully-qualified path representing PublisherModel resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchNasJobFromNasJobName(nasJobName)

matchNasJobFromNasJobName(nasJobName: string): string | number;

Parse the nas_job from NasJob resource.

Parameter
NameDescription
nasJobName string

A fully-qualified path representing NasJob resource.

Returns
TypeDescription
string | number

{string} A string representing the nas_job.

matchNasJobFromNasTrialDetailName(nasTrialDetailName)

matchNasJobFromNasTrialDetailName(nasTrialDetailName: string): string | number;

Parse the nas_job from NasTrialDetail resource.

Parameter
NameDescription
nasTrialDetailName string

A fully-qualified path representing NasTrialDetail resource.

Returns
TypeDescription
string | number

{string} A string representing the nas_job.

matchNasTrialDetailFromNasTrialDetailName(nasTrialDetailName)

matchNasTrialDetailFromNasTrialDetailName(nasTrialDetailName: string): string | number;

Parse the nas_trial_detail from NasTrialDetail resource.

Parameter
NameDescription
nasTrialDetailName string

A fully-qualified path representing NasTrialDetail resource.

Returns
TypeDescription
string | number

{string} A string representing the nas_trial_detail.

matchPersistentResourceFromPersistentResourceName(persistentResourceName)

matchPersistentResourceFromPersistentResourceName(persistentResourceName: string): string | number;

Parse the persistent_resource from PersistentResource resource.

Parameter
NameDescription
persistentResourceName string

A fully-qualified path representing PersistentResource resource.

Returns
TypeDescription
string | number

{string} A string representing the persistent_resource.

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 | number

{string} A string representing the project.

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

Parse the project from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

Parse the project from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

Parse the project from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the project from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDatasetVersionName(datasetVersionName)

matchProjectFromDatasetVersionName(datasetVersionName: string): string | number;

Parse the project from DatasetVersion resource.

Parameter
NameDescription
datasetVersionName string

A fully-qualified path representing DatasetVersion resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the project from DeploymentResourcePool resource.

Parameter
NameDescription
deploymentResourcePoolName string

A fully-qualified path representing DeploymentResourcePool resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

Parse the project from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

Parse the project from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureGroupName(featureGroupName)

matchProjectFromFeatureGroupName(featureGroupName: string): string | number;

Parse the project from FeatureGroup resource.

Parameter
NameDescription
featureGroupName string

A fully-qualified path representing FeatureGroup resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureOnlineStoreName(featureOnlineStoreName)

matchProjectFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

Parse the project from FeatureOnlineStore resource.

Parameter
NameDescription
featureOnlineStoreName string

A fully-qualified path representing FeatureOnlineStore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

Parse the project from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureViewName(featureViewName)

matchProjectFromFeatureViewName(featureViewName: string): string | number;

Parse the project from FeatureView resource.

Parameter
NameDescription
featureViewName string

A fully-qualified path representing FeatureView resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureViewSyncName(featureViewSyncName)

matchProjectFromFeatureViewSyncName(featureViewSyncName: string): string | number;

Parse the project from FeatureViewSync resource.

Parameter
NameDescription
featureViewSyncName string

A fully-qualified path representing FeatureViewSync resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the project from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the project from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

Parse the project from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the project from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the project from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the project from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the project from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromNasJobName(nasJobName)

matchProjectFromNasJobName(nasJobName: string): string | number;

Parse the project from NasJob resource.

Parameter
NameDescription
nasJobName string

A fully-qualified path representing NasJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromNasTrialDetailName(nasTrialDetailName)

matchProjectFromNasTrialDetailName(nasTrialDetailName: string): string | number;

Parse the project from NasTrialDetail resource.

Parameter
NameDescription
nasTrialDetailName string

A fully-qualified path representing NasTrialDetail resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromPersistentResourceName(persistentResourceName)

matchProjectFromPersistentResourceName(persistentResourceName: string): string | number;

Parse the project from PersistentResource resource.

Parameter
NameDescription
persistentResourceName string

A fully-qualified path representing PersistentResource resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

Parse the project from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectLocationEndpointName(projectLocationEndpointName)

matchProjectFromProjectLocationEndpointName(projectLocationEndpointName: string): string | number;

Parse the project from ProjectLocationEndpoint resource.

Parameter
NameDescription
projectLocationEndpointName string

A fully-qualified path representing project_location_endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchProjectFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

Parse the project from ProjectLocationFeatureGroupFeature resource.

Parameter
NameDescription
projectLocationFeatureGroupFeatureName string

A fully-qualified path representing project_location_feature_group_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchProjectFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

Parse the project from ProjectLocationFeaturestoreEntityTypeFeature resource.

Parameter
NameDescription
projectLocationFeaturestoreEntityTypeFeatureName string

A fully-qualified path representing project_location_featurestore_entity_type_feature resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectLocationPublisherModelName(projectLocationPublisherModelName)

matchProjectFromProjectLocationPublisherModelName(projectLocationPublisherModelName: string): string | number;

Parse the project from ProjectLocationPublisherModel resource.

Parameter
NameDescription
projectLocationPublisherModelName string

A fully-qualified path representing project_location_publisher_model resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

Parse the project from Project resource.

Parameter
NameDescription
projectName string

A fully-qualified path representing Project resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromSavedQueryName(savedQueryName)

matchProjectFromSavedQueryName(savedQueryName: string): string | number;

Parse the project from SavedQuery resource.

Parameter
NameDescription
savedQueryName string

A fully-qualified path representing SavedQuery resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromScheduleName(scheduleName)

matchProjectFromScheduleName(scheduleName: string): string | number;

Parse the project from Schedule resource.

Parameter
NameDescription
scheduleName string

A fully-qualified path representing Schedule resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the project from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

Parse the project from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the project from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

Parse the project from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the project from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the project from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrainingPipelineName(trainingPipelineName)

matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the project from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrialName(trialName)

matchProjectFromTrialName(trialName: string): string | number;

Parse the project from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchPublisherFromProjectLocationPublisherModelName(projectLocationPublisherModelName)

matchPublisherFromProjectLocationPublisherModelName(projectLocationPublisherModelName: string): string | number;

Parse the publisher from ProjectLocationPublisherModel resource.

Parameter
NameDescription
projectLocationPublisherModelName string

A fully-qualified path representing project_location_publisher_model resource.

Returns
TypeDescription
string | number

{string} A string representing the publisher.

matchPublisherFromPublisherModelName(publisherModelName)

matchPublisherFromPublisherModelName(publisherModelName: string): string | number;

Parse the publisher from PublisherModel resource.

Parameter
NameDescription
publisherModelName string

A fully-qualified path representing PublisherModel resource.

Returns
TypeDescription
string | number

{string} A string representing the publisher.

matchRunFromTensorboardRunName(tensorboardRunName)

matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the run from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the run from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchSavedQueryFromSavedQueryName(savedQueryName)

matchSavedQueryFromSavedQueryName(savedQueryName: string): string | number;

Parse the saved_query from SavedQuery resource.

Parameter
NameDescription
savedQueryName string

A fully-qualified path representing SavedQuery resource.

Returns
TypeDescription
string | number

{string} A string representing the saved_query.

matchScheduleFromScheduleName(scheduleName)

matchScheduleFromScheduleName(scheduleName: string): string | number;

Parse the schedule from Schedule resource.

Parameter
NameDescription
scheduleName string

A fully-qualified path representing Schedule resource.

Returns
TypeDescription
string | number

{string} A string representing the schedule.

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the slice from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the slice.

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the specialist_pool from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the specialist_pool.

matchStudyFromStudyName(studyName)

matchStudyFromStudyName(studyName: string): string | number;

Parse the study from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the study.

matchStudyFromTrialName(trialName)

matchStudyFromTrialName(trialName: string): string | number;

Parse the study from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the study.

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the tensorboard from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardName(tensorboardName)

matchTensorboardFromTensorboardName(tensorboardName: string): string | number;

Parse the tensorboard from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardRunName(tensorboardRunName)

matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the tensorboard from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the tensorboard from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the time_series from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the time_series.

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the training_pipeline from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the training_pipeline.

matchTrialFromTrialName(trialName)

matchTrialFromTrialName(trialName: string): string | number;

Parse the trial from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the trial.

metadataSchemaPath(project, location, metadataStore, metadataSchema)

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

Return a fully-qualified metadataSchema resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
metadataSchema string
Returns
TypeDescription
string

{string} Resource name string.

metadataStorePath(project, location, metadataStore)

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

Return a fully-qualified metadataStore resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
Returns
TypeDescription
string

{string} Resource name string.

modelDeploymentMonitoringJobPath(project, location, modelDeploymentMonitoringJob)

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

Return a fully-qualified modelDeploymentMonitoringJob resource name string.

Parameters
NameDescription
project string
location string
modelDeploymentMonitoringJob string
Returns
TypeDescription
string

{string} Resource name string.

modelEvaluationPath(project, location, model, evaluation)

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

Return a fully-qualified modelEvaluation resource name string.

Parameters
NameDescription
project string
location string
model string
evaluation string
Returns
TypeDescription
string

{string} Resource name string.

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

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

Return a fully-qualified modelEvaluationSlice resource name string.

Parameters
NameDescription
project string
location string
model string
evaluation string
slice string
Returns
TypeDescription
string

{string} Resource name string.

modelPath(project, location, model)

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

Return a fully-qualified model resource name string.

Parameters
NameDescription
project string
location string
model string
Returns
TypeDescription
string

{string} Resource name string.

nasJobPath(project, location, nasJob)

nasJobPath(project: string, location: string, nasJob: string): string;

Return a fully-qualified nasJob resource name string.

Parameters
NameDescription
project string
location string
nasJob string
Returns
TypeDescription
string

{string} Resource name string.

nasTrialDetailPath(project, location, nasJob, nasTrialDetail)

nasTrialDetailPath(project: string, location: string, nasJob: string, nasTrialDetail: string): string;

Return a fully-qualified nasTrialDetail resource name string.

Parameters
NameDescription
project string
location string
nasJob string
nasTrialDetail string
Returns
TypeDescription
string

{string} Resource name string.

persistentResourcePath(project, location, persistentResource)

persistentResourcePath(project: string, location: string, persistentResource: string): string;

Return a fully-qualified persistentResource resource name string.

Parameters
NameDescription
project string
location string
persistentResource string
Returns
TypeDescription
string

{string} Resource name string.

pipelineJobPath(project, location, pipelineJob)

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

Return a fully-qualified pipelineJob resource name string.

Parameters
NameDescription
project string
location string
pipelineJob string
Returns
TypeDescription
string

{string} Resource name string.

projectLocationEndpointPath(project, location, endpoint)

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

Return a fully-qualified projectLocationEndpoint resource name string.

Parameters
NameDescription
project string
location string
endpoint string
Returns
TypeDescription
string

{string} Resource name string.

projectLocationFeatureGroupFeaturePath(project, location, featureGroup, feature)

projectLocationFeatureGroupFeaturePath(project: string, location: string, featureGroup: string, feature: string): string;

Return a fully-qualified projectLocationFeatureGroupFeature resource name string.

Parameters
NameDescription
project string
location string
featureGroup string
feature string
Returns
TypeDescription
string

{string} Resource name string.

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

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

Return a fully-qualified projectLocationFeaturestoreEntityTypeFeature resource name string.

Parameters
NameDescription
project string
location string
featurestore string
entityType string
feature string
Returns
TypeDescription
string

{string} Resource name string.

projectLocationPublisherModelPath(project, location, publisher, model)

projectLocationPublisherModelPath(project: string, location: string, publisher: string, model: string): string;

Return a fully-qualified projectLocationPublisherModel resource name string.

Parameters
NameDescription
project string
location string
publisher string
model string
Returns
TypeDescription
string

{string} Resource name string.

projectPath(project)

projectPath(project: string): string;

Return a fully-qualified project resource name string.

Parameter
NameDescription
project string
Returns
TypeDescription
string

{string} Resource name string.

publisherModelPath(publisher, model)

publisherModelPath(publisher: string, model: string): string;

Return a fully-qualified publisherModel resource name string.

Parameters
NameDescription
publisher string
model string
Returns
TypeDescription
string

{string} Resource name string.

savedQueryPath(project, location, dataset, savedQuery)

savedQueryPath(project: string, location: string, dataset: string, savedQuery: string): string;

Return a fully-qualified savedQuery resource name string.

Parameters
NameDescription
project string
location string
dataset string
savedQuery string
Returns
TypeDescription
string

{string} Resource name string.

schedulePath(project, location, schedule)

schedulePath(project: string, location: string, schedule: string): string;

Return a fully-qualified schedule resource name string.

Parameters
NameDescription
project string
location string
schedule string
Returns
TypeDescription
string

{string} Resource name string.

searchFeatures(request, options)

searchFeatures(request?: protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IFeature[],
        protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest | null,
        protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesResponse
    ]>;

Searches Features matching a query in a given project.

Parameters
NameDescription
request ISearchFeaturesRequest

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.ISearchFeaturesRequest | null, protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesResponse ]>

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

searchFeatures(request, options, callback)

searchFeatures(request: protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>): void;
Parameters
NameDescription
request ISearchFeaturesRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IFeature>
Returns
TypeDescription
void

searchFeatures(request, callback)

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

searchFeaturesAsync(request, options)

searchFeaturesAsync(request?: protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IFeature>;

Equivalent to searchFeatures, but returns an iterable object.

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

Parameters
NameDescription
request ISearchFeaturesRequest

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. When you iterate the returned iterable, each element will be an object representing . 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 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 search Features.
   *  Format:
   *  `projects/{project}/locations/{location}`
   */
  // const location = 'abc123'
  /**
   *  Query string that is a conjunction of field-restricted queries and/or
   *  field-restricted filters.  Field-restricted queries and filters can be
   *  combined using `AND` to form a conjunction.
   *  A field query is in the form FIELD:QUERY. This implicitly checks if QUERY
   *  exists as a substring within Feature's FIELD. The QUERY
   *  and the FIELD are converted to a sequence of words (i.e. tokens) for
   *  comparison. This is done by:
   *    * Removing leading/trailing whitespace and tokenizing the search value.
   *    Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore
   *    `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated
   *    as a wildcard that matches characters within a token.
   *    * Ignoring case.
   *    * Prepending an asterisk to the first and appending an asterisk to the
   *    last token in QUERY.
   *  A QUERY must be either a singular token or a phrase. A phrase is one or
   *  multiple words enclosed in double quotation marks ("). With phrases, the
   *  order of the words is important. Words in the phrase must be matching in
   *  order and consecutively.
   *  Supported FIELDs for field-restricted queries:
   *  * `feature_id`
   *  * `description`
   *  * `entity_type_id`
   *  Examples:
   *  * `feature_id: foo` --> Matches a Feature with ID containing the substring
   *  `foo` (eg. `foo`, `foofeature`, `barfoo`).
   *  * `feature_id: foo*feature` --> Matches a Feature with ID containing the
   *  substring `foo*feature` (eg. `foobarfeature`).
   *  * `feature_id: foo AND description: bar` --> Matches a Feature with ID
   *  containing the substring `foo` and description containing the substring
   *  `bar`.
   *  Besides field queries, the following exact-match filters are
   *  supported. The exact-match filters do not support wildcards. Unlike
   *  field-restricted queries, exact-match filters are case-sensitive.
   *  * `feature_id`: Supports = comparisons.
   *  * `description`: Supports = comparisons. Multi-token filters should be
   *  enclosed in quotes.
   *  * `entity_type_id`: Supports = comparisons.
   *  * `value_type`: Supports = and != comparisons.
   *  * `labels`: Supports key-value equality as well as key presence.
   *  * `featurestore_id`: Supports = comparisons.
   *  Examples:
   *  * `description = "foo bar"` --> Any Feature with description exactly equal
   *  to `foo bar`
   *  * `value_type = DOUBLE` --> Features whose type is DOUBLE.
   *  * `labels.active = yes AND labels.env = prod` --> Features having both
   *      (active: yes) and (env: prod) labels.
   *  * `labels.env: *` --> Any Feature which has a label with `env` as the
   *    key.
   */
  // const query = 'abc123'
  /**
   *  The maximum number of Features to return. The service may return fewer
   *  than this value. If unspecified, at most 100 Features will be returned.
   *  The maximum value is 100; any value greater than 100 will be coerced to
   *  100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  FeaturestoreService.SearchFeatures google.cloud.aiplatform.v1beta1.FeaturestoreService.SearchFeatures 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.SearchFeatures google.cloud.aiplatform.v1beta1.FeaturestoreService.SearchFeatures,
   *  except `page_size`, must match the call that provided the page token.
   */
  // const pageToken = 'abc123'

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

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

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

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

  callSearchFeatures();

searchFeaturesStream(request, options)

searchFeaturesStream(request?: protos.google.cloud.aiplatform.v1beta1.ISearchFeaturesRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request ISearchFeaturesRequest

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 on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using searchFeaturesAsync() method described below for async iteration which you can stop as needed. Please see the documentation for more details and examples.

setIamPolicy(request, options, callback)

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

Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

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

The request object that will be sent.

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

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback Callback<google.iam.v1.Policy, google.iam.v1.SetIamPolicyRequest | 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 .

Returns
TypeDescription
Promise<[google.iam.v1.Policy]>

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

specialistPoolPath(project, location, specialistPool)

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

Return a fully-qualified specialistPool resource name string.

Parameters
NameDescription
project string
location string
specialistPool string
Returns
TypeDescription
string

{string} Resource name string.

studyPath(project, location, study)

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

Return a fully-qualified study resource name string.

Parameters
NameDescription
project string
location string
study string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardExperimentPath(project, location, tensorboard, experiment)

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

Return a fully-qualified tensorboardExperiment resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardPath(project, location, tensorboard)

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

Return a fully-qualified tensorboard resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
Returns
TypeDescription
string

{string} Resource name string.

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

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

Return a fully-qualified tensorboardRun resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
run string
Returns
TypeDescription
string

{string} Resource name string.

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

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

Return a fully-qualified tensorboardTimeSeries resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
run string
timeSeries string
Returns
TypeDescription
string

{string} Resource name string.

testIamPermissions(request, options, callback)

testIamPermissions(request: IamProtos.google.iam.v1.TestIamPermissionsRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>): Promise<[IamProtos.google.iam.v1.TestIamPermissionsResponse]>;

Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

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

The request object that will be sent.

options CallOptions | Callback<google.iam.v1.TestIamPermissionsResponse, google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback Callback<google.iam.v1.TestIamPermissionsResponse, google.iam.v1.TestIamPermissionsRequest | 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 .

Returns
TypeDescription
Promise<[google.iam.v1.TestIamPermissionsResponse]>

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

trainingPipelinePath(project, location, trainingPipeline)

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

Return a fully-qualified trainingPipeline resource name string.

Parameters
NameDescription
project string
location string
trainingPipeline string
Returns
TypeDescription
string

{string} Resource name string.

trialPath(project, location, study, trial)

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

Return a fully-qualified trial resource name string.

Parameters
NameDescription
project string
location string
study string
trial string
Returns
TypeDescription
string

{string} Resource name string.

updateEntityType(request, options)

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

Updates the parameters of a single EntityType.

Parameters
NameDescription
request IUpdateEntityTypeRequest

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.IUpdateEntityTypeRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing EntityType. Please see the documentation 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 EntityType's `name` field is used to identify the EntityType
   *  to be updated. Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
   */
  // const entityType = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  EntityType resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `description`
   *    * `labels`
   *    * `monitoring_config.snapshot_analysis.disabled`
   *    * `monitoring_config.snapshot_analysis.monitoring_interval_days`
   *    * `monitoring_config.snapshot_analysis.staleness_days`
   *    * `monitoring_config.import_features_analysis.state`
   *    * `monitoring_config.import_features_analysis.anomaly_detection_baseline`
   *    * `monitoring_config.numerical_threshold_config.value`
   *    * `monitoring_config.categorical_threshold_config.value`
   *    * `offline_storage_ttl_days`
   */
  // const updateMask = {}

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

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

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

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

  callUpdateEntityType();

updateEntityType(request, options, callback)

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

updateEntityType(request, callback)

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

updateFeature(request, options)

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

Updates the parameters of a single Feature.

Parameters
NameDescription
request IUpdateFeatureRequest

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.IUpdateFeatureRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing . Please see the documentation 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 Feature's `name` field is used to identify the Feature to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
   *  `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`
   */
  // const feature = {}
  /**
   *  Field mask is used to specify the fields to be overwritten in the
   *  Features resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then only the non-empty fields present in the
   *  request will be overwritten. Set the update_mask to `*` to override all
   *  fields.
   *  Updatable fields:
   *    * `description`
   *    * `labels`
   *    * `disable_monitoring` (Not supported for FeatureRegistry Feature)
   */
  // const updateMask = {}

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

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

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

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

  callUpdateFeature();

updateFeature(request, options, callback)

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

updateFeature(request, callback)

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

updateFeaturestore(request, options)

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

Updates the parameters of a single Featurestore.

Parameters
NameDescription
request IUpdateFeaturestoreRequest

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.IUpdateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the documentation 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`
   *    * `online_storage_ttl_days`
   */
  // 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();

updateFeaturestore(request, options, callback)

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

updateFeaturestore(request, callback)

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