Class v1.FeaturestoreServiceClient (3.13.0)

Package

Constructors

(constructor)(opts, gaxInstance)

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

Properties

apiEndpoint

get apiEndpoint(): string;

apiEndpoint

static get apiEndpoint(): string;

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;

scopes

static get scopes(): string[];

servicePath

static get servicePath(): string;

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;

annotationSpecPath(project, location, dataset, annotationSpec)

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

artifactPath(project, location, metadataStore, artifact)

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

batchCreateFeatures(request, options)

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

  /**
   * 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').v1;

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

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

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

  callBatchCreateFeatures();

batchCreateFeatures(request, options, callback)

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

batchCreateFeatures(request, callback)

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

batchPredictionJobPath(project, location, batchPredictionJob)

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

batchReadFeatureValues(request, options)

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

  /**
   * 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').v1;

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

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

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

  callBatchReadFeatureValues();

batchReadFeatureValues(request, options, callback)

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

batchReadFeatureValues(request, callback)

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

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>;

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

checkBatchCreateFeaturesProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callBatchCreateFeatures();

checkBatchReadFeatureValuesProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callBatchReadFeatureValues();

checkCreateEntityTypeProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callCreateEntityType();

checkCreateFeatureProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callCreateFeature();

checkCreateFeaturestoreProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callCreateFeaturestore();

checkDeleteEntityTypeProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callDeleteEntityType();

checkDeleteFeatureProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callDeleteFeature();

checkDeleteFeaturestoreProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callDeleteFeaturestore();

checkDeleteFeatureValuesProgress(name)

checkDeleteFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.DeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1.DeleteFeatureValuesOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata>>;

  /**
   * 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').v1;

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

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

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

  callExportFeatureValues();

checkImportFeatureValuesProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callImportFeatureValues();

checkUpdateFeaturestoreProgress(name)

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

  /**
   * 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').v1;

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

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

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

  callUpdateFeaturestore();

close()

close(): Promise<void>;

contextPath(project, location, metadataStore, context)

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

createEntityType(request, options)

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

  /**
   * 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').v1;

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

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

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

  callCreateEntityType();

createEntityType(request, options, callback)

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

createEntityType(request, callback)

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

createFeature(request, options)

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

  /**
   * 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').v1;

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

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

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

  callCreateFeature();

createFeature(request, options, callback)

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

createFeature(request, callback)

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

createFeaturestore(request, options)

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

  /**
   * 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').v1;

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

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

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

  callCreateFeaturestore();

createFeaturestore(request, options, callback)

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

createFeaturestore(request, callback)

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

customJobPath(project, location, customJob)

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

dataItemPath(project, location, dataset, dataItem)

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

dataLabelingJobPath(project, location, dataLabelingJob)

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

datasetPath(project, location, dataset)

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

datasetVersionPath(project, location, dataset, datasetVersion)

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

deleteEntityType(request, options)

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

  /**
   * 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').v1;

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

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

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

  callDeleteEntityType();

deleteEntityType(request, options, callback)

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

deleteEntityType(request, callback)

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

deleteFeature(request, options)

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

  /**
   * 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').v1;

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

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

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

  callDeleteFeature();

deleteFeature(request, options, callback)

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

deleteFeature(request, callback)

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

deleteFeaturestore(request, options)

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

  /**
   * 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').v1;

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

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

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

  callDeleteFeaturestore();

deleteFeaturestore(request, options, callback)

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

deleteFeaturestore(request, callback)

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

deleteFeatureValues(request, options)

deleteFeatureValues(request?: protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IDeleteFeatureValuesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteFeatureValues(request, callback)

deleteFeatureValues(request: protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IDeleteFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): 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>;

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

deploymentResourcePoolPath(project, location, deploymentResourcePool)

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

entityTypePath(project, location, featurestore, entityType)

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

executionPath(project, location, metadataStore, execution)

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

exportFeatureValues(request, options)

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

  /**
   * 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').v1;

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

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

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

  callExportFeatureValues();

exportFeatureValues(request, options, callback)

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

exportFeatureValues(request, callback)

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

featureGroupPath(project, location, featureGroup)

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

featureOnlineStorePath(project, location, featureOnlineStore)

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

featurestorePath(project, location, featurestore)

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

featureViewPath(project, location, featureOnlineStore, featureView)

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

featureViewSyncPath(project, location, featureOnlineStore, featureView)

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

getEntityType(request, options)

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

  /**
   * 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').v1;

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

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

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

  callGetEntityType();

getEntityType(request, options, callback)

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

getEntityType(request, callback)

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

getFeature(request, options)

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

  /**
   * 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').v1;

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

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

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

  callGetFeature();

getFeature(request, options, callback)

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

getFeature(request, callback)

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

getFeaturestore(request, options)

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

  /**
   * 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').v1;

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

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

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

  callGetFeaturestore();

getFeaturestore(request, options, callback)

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

getFeaturestore(request, callback)

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

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]>;

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>;

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]>;

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

getProjectId()

getProjectId(): Promise<string>;

getProjectId(callback)

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

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

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

importFeatureValues(request, options)

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

  /**
   * 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').v1;

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

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

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

  callImportFeatureValues();

importFeatureValues(request, options, callback)

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

importFeatureValues(request, callback)

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

indexEndpointPath(project, location, indexEndpoint)

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

indexPath(project, location, index)

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

initialize()

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

listEntityTypes(request, options)

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

listEntityTypes(request, options, callback)

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

listEntityTypes(request, callback)

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

listEntityTypesAsync(request, options)

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

  /**
   * 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.v1.FeaturestoreService.ListEntityTypes 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListEntityTypes google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes 
   *  must match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported fields:
   *    * `entity_type_id`
   *    * `create_time`
   *    * `update_time`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

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

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

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

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

  callListEntityTypes();

listEntityTypesStream(request, options)

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

listFeatures(request, options)

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

listFeatures(request, options, callback)

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

listFeatures(request, callback)

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

listFeaturesAsync(request, options)

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

  /**
   * 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.v1.FeaturestoreService.ListFeatures 
   *  call or
   *  FeatureRegistryService.ListFeatures google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatures 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeatures google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures 
   *  or
   *  FeatureRegistryService.ListFeatures google.cloud.aiplatform.v1.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.v1.ListFeaturesRequest.latest_stats_count 
   *  of stats for each Feature in response. Valid value is 0, 10. If number of
   *  stats exists < *="" listfeaturesrequest.latest_stats_count="" google.cloud.aiplatform.v1.listfeaturesrequest.latest_stats_count,="" *="" return="" all="" existing="" stats.="" */="" const="" lateststatscount="1234" imports="" the="" aiplatform="" library="" const="" {featurestoreserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" featurestoreserviceclient();="" async="" function="" calllistfeatures()="" {="" construct="" request="" const="" request="{" parent,="" };="" run="" request="" const="" iterable="aiplatformClient.listFeaturesAsync(request);" for="" await="" (const="" response="" of="" iterable)="" {="" console.log(response);="" }="" }="" calllistfeatures();="">

listFeaturesStream(request, options)

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

listFeaturestores(request, options)

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

listFeaturestores(request, options, callback)

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

listFeaturestores(request, callback)

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

listFeaturestoresAsync(request, options)

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

  /**
   * 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.v1.FeaturestoreService.ListFeaturestores 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  FeaturestoreService.ListFeaturestores google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores 
   *  must match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported Fields:
   *    * `create_time`
   *    * `update_time`
   *    * `online_serving_config.fixed_node_count`
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

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

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

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

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

  callListFeaturestores();

listFeaturestoresStream(request, options)

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

listLocationsAsync(request, options)

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

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>;

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

locationPath(project, location)

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

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

matchDatasetFromDatasetVersionName(datasetVersionName)

matchDatasetFromDatasetVersionName(datasetVersionName: string): string | number;

matchDatasetFromSavedQueryName(savedQueryName)

matchDatasetFromSavedQueryName(savedQueryName: string): string | number;

matchDatasetVersionFromDatasetVersionName(datasetVersionName)

matchDatasetVersionFromDatasetVersionName(datasetVersionName: string): string | number;

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName)

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName: string): string | number;

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchFeatureGroupFromFeatureGroupName(featureGroupName)

matchFeatureGroupFromFeatureGroupName(featureGroupName: string): string | number;

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName)

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

matchFeatureOnlineStoreFromFeatureViewName(featureViewName)

matchFeatureOnlineStoreFromFeatureViewName(featureViewName: string): string | number;

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName)

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName: string): string | number;

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchFeatureViewFromFeatureViewName(featureViewName)

matchFeatureViewFromFeatureViewName(featureViewName: string): string | number;

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName)

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName: string): string | number;

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

matchIndexEndpointFromIndexEndpointName(indexEndpointName)

matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

matchLocationFromDatasetVersionName(datasetVersionName)

matchLocationFromDatasetVersionName(datasetVersionName: string): string | number;

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

matchLocationFromFeatureGroupName(featureGroupName)

matchLocationFromFeatureGroupName(featureGroupName: string): string | number;

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName)

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

matchLocationFromFeatureViewName(featureViewName)

matchLocationFromFeatureViewName(featureViewName: string): string | number;

matchLocationFromFeatureViewSyncName(featureViewSyncName)

matchLocationFromFeatureViewSyncName(featureViewSyncName: string): string | number;

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;