The service that handles CRUD and List for resources for Featurestore. v1
Package
@google-cloud/aiplatformConstructors
(constructor)(opts, gaxInstance)
constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);
Construct an instance of FeaturestoreServiceClient.
Name | Description |
opts |
ClientOptions
|
gaxInstance |
typeof gax | typeof gax.fallback
: loaded instance of |
Properties
apiEndpoint
static get apiEndpoint(): string;
The DNS address for this API service - same as servicePath(), exists for compatibility reasons.
auth
auth: gax.GoogleAuth;
descriptors
descriptors: Descriptors;
featurestoreServiceStub
featurestoreServiceStub?: Promise<{
[name: string]: Function;
}>;
iamClient
iamClient: IamClient;
innerApiCalls
innerApiCalls: {
[name: string]: Function;
};
locationsClient
locationsClient: LocationsClient;
operationsClient
operationsClient: gax.OperationsClient;
pathTemplates
pathTemplates: {
[name: string]: gax.PathTemplate;
};
port
static get port(): number;
The port for this API service.
scopes
static get scopes(): string[];
The scopes needed to make gRPC calls for every method defined in this service.
servicePath
static get servicePath(): string;
The DNS address for this API service.
warn
warn: (code: string, message: string, warnType?: string) => void;
Methods
annotationPath(project, location, dataset, dataItem, annotation)
annotationPath(project: string, location: string, dataset: string, dataItem: string, annotation: string): string;
Return a fully-qualified annotation resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
dataItem |
string
|
annotation |
string
|
Type | Description |
string | {string} Resource name string. |
annotationSpecPath(project, location, dataset, annotationSpec)
annotationSpecPath(project: string, location: string, dataset: string, annotationSpec: string): string;
Return a fully-qualified annotationSpec resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
annotationSpec |
string
|
Type | Description |
string | {string} Resource name string. |
artifactPath(project, location, metadataStore, artifact)
artifactPath(project: string, location: string, metadataStore: string, artifact: string): string;
Return a fully-qualified artifact resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
artifact |
string
|
Type | Description |
string | {string} Resource name string. |
batchCreateFeatures(request, options)
batchCreateFeatures(request?: protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Creates a batch of Features in a given EntityType.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the EntityType to create the batch of
* Features under. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const parent = 'abc123'
/**
* Required. The request message specifying the Features to create. All
* Features must be created under the same parent EntityType. The `parent`
* field in each child request message can be omitted. If `parent` is set in a
* child request, then the value must match the `parent` value in this request
* message.
*/
// const requests = 1234
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
batchCreateFeatures(request, callback)
batchCreateFeatures(request: protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateFeaturesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
batchPredictionJobPath(project, location, batchPredictionJob)
batchPredictionJobPath(project: string, location: string, batchPredictionJob: string): string;
Return a fully-qualified batchPredictionJob resource name string.
Name | Description |
project |
string
|
location |
string
|
batchPredictionJob |
string
|
Type | Description |
string | {string} Resource name string. |
batchReadFeatureValues(request, options)
batchReadFeatureValues(request?: protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Batch reads Feature values from a Featurestore.
This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Each read instance consists of exactly one read timestamp and one or more
* entity IDs identifying entities of the corresponding EntityTypes whose
* Features are requested.
* Each output instance contains Feature values of requested entities
* concatenated together as of the read time.
* An example read instance may be `foo_entity_id, bar_entity_id,
* 2020-01-01T10:00:00.123Z`.
* An example output instance may be `foo_entity_id, bar_entity_id,
* 2020-01-01T10:00:00.123Z, foo_entity_feature1_value,
* bar_entity_feature2_value`.
* Timestamp in each read instance must be millisecond-aligned.
* `csv_read_instances` are read instances stored in a plain-text CSV file.
* The header should be:
* ENTITY_TYPE_ID1, ENTITY_TYPE_ID2, ..., timestamp
* The columns can be in any order.
* Values in the timestamp column must use the RFC 3339 format, e.g.
* `2012-07-30T10:43:17.123Z`.
*/
// const csvReadInstances = {}
/**
* Similar to csv_read_instances, but from BigQuery source.
*/
// const bigqueryReadInstances = {}
/**
* Required. The resource name of the Featurestore from which to query Feature
* values. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}`
*/
// const featurestore = 'abc123'
/**
* Required. Specifies output location and format.
*/
// const destination = {}
/**
* When not empty, the specified fields in the *_read_instances source will be
* joined as-is in the output, in addition to those fields from the
* Featurestore Entity.
* For BigQuery source, the type of the pass-through values will be
* automatically inferred. For CSV source, the pass-through values will be
* passed as opaque bytes.
*/
// const passThroughFields = 1234
/**
* Required. Specifies EntityType grouping Features to read values of and
* settings. Each EntityType referenced in
* BatchReadFeatureValuesRequest.entity_type_specs must have a column
* specifying entity IDs in the EntityType in
* BatchReadFeatureValuesRequest.request .
*/
// const entityTypeSpecs = 1234
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
batchReadFeatureValues(request, callback)
batchReadFeatureValues(request: protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IBatchReadFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
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
.
Name | Description |
request |
protos.google.longrunning.CancelOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>
The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
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>>;
Check the status of the long running operation returned by batchCreateFeatures()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchCreateFeaturesResponse, protos.google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the EntityType to create the batch of
* Features under. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const parent = 'abc123'
/**
* Required. The request message specifying the Features to create. All
* Features must be created under the same parent EntityType. The `parent`
* field in each child request message can be omitted. If `parent` is set in a
* child request, then the value must match the `parent` value in this request
* message.
*/
// const requests = 1234
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callBatchCreateFeatures() {
// Construct request
const request = {
parent,
requests,
};
// Run request
const [operation] = await aiplatformClient.batchCreateFeatures(request);
const [response] = await operation.promise();
console.log(response);
}
callBatchCreateFeatures();
checkBatchReadFeatureValuesProgress(name)
checkBatchReadFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata>>;
Check the status of the long running operation returned by batchReadFeatureValues()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse, protos.google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Each read instance consists of exactly one read timestamp and one or more
* entity IDs identifying entities of the corresponding EntityTypes whose
* Features are requested.
* Each output instance contains Feature values of requested entities
* concatenated together as of the read time.
* An example read instance may be `foo_entity_id, bar_entity_id,
* 2020-01-01T10:00:00.123Z`.
* An example output instance may be `foo_entity_id, bar_entity_id,
* 2020-01-01T10:00:00.123Z, foo_entity_feature1_value,
* bar_entity_feature2_value`.
* Timestamp in each read instance must be millisecond-aligned.
* `csv_read_instances` are read instances stored in a plain-text CSV file.
* The header should be:
* ENTITY_TYPE_ID1, ENTITY_TYPE_ID2, ..., timestamp
* The columns can be in any order.
* Values in the timestamp column must use the RFC 3339 format, e.g.
* `2012-07-30T10:43:17.123Z`.
*/
// const csvReadInstances = {}
/**
* Similar to csv_read_instances, but from BigQuery source.
*/
// const bigqueryReadInstances = {}
/**
* Required. The resource name of the Featurestore from which to query Feature
* values. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}`
*/
// const featurestore = 'abc123'
/**
* Required. Specifies output location and format.
*/
// const destination = {}
/**
* When not empty, the specified fields in the *_read_instances source will be
* joined as-is in the output, in addition to those fields from the
* Featurestore Entity.
* For BigQuery source, the type of the pass-through values will be
* automatically inferred. For CSV source, the pass-through values will be
* passed as opaque bytes.
*/
// const passThroughFields = 1234
/**
* Required. Specifies EntityType grouping Features to read values of and
* settings. Each EntityType referenced in
* BatchReadFeatureValuesRequest.entity_type_specs must have a column
* specifying entity IDs in the EntityType in
* BatchReadFeatureValuesRequest.request .
*/
// const entityTypeSpecs = 1234
/**
* 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>>;
Check the status of the long running operation returned by createEntityType()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.EntityType, protos.google.cloud.aiplatform.v1.CreateEntityTypeOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* 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>>;
Check the status of the long running operation returned by createFeature()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.Feature, protos.google.cloud.aiplatform.v1.CreateFeatureOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the EntityType to create a Feature.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const parent = 'abc123'
/**
* Required. The Feature to create.
*/
// const feature = {}
/**
* Required. The ID to use for the Feature, which will become the final
* component of the Feature's resource name.
* This value may be up to 128 characters, and valid characters are
* `[a-z0-9_]`. The first character cannot be a number.
* The value must be unique within an EntityType.
*/
// const featureId = 'abc123'
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callCreateFeature() {
// Construct request
const request = {
parent,
feature,
featureId,
};
// Run request
const [operation] = await aiplatformClient.createFeature(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateFeature();
checkCreateFeaturestoreProgress(name)
checkCreateFeaturestoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata>>;
Check the status of the long running operation returned by createFeaturestore()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* 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>>;
Check the status of the long running operation returned by deleteEntityType()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* 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>>;
Check the status of the long running operation returned by deleteFeature()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Features to be deleted.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callDeleteFeature() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteFeature(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteFeature();
checkDeleteFeaturestoreProgress(name)
checkDeleteFeaturestoreProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteFeaturestore()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* 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();
checkExportFeatureValuesProgress(name)
checkExportFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata>>;
Check the status of the long running operation returned by exportFeatureValues()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Exports the latest Feature values of all entities of the EntityType
* within a time range.
*/
// const snapshotExport = {}
/**
* Exports all historical values of all entities of the EntityType within a
* time range
*/
// const fullExport = {}
/**
* Required. The resource name of the EntityType from which to export Feature
* values. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const entityType = 'abc123'
/**
* Required. Specifies destination location and format.
*/
// const destination = {}
/**
* Required. Selects Features to export values of.
*/
// const featureSelector = {}
/**
* Per-Feature export settings.
*/
// const settings = 1234
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callExportFeatureValues() {
// Construct request
const request = {
entityType,
destination,
featureSelector,
};
// Run request
const [operation] = await aiplatformClient.exportFeatureValues(request);
const [response] = await operation.promise();
console.log(response);
}
callExportFeatureValues();
checkImportFeatureValuesProgress(name)
checkImportFeatureValuesProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata>>;
Check the status of the long running operation returned by importFeatureValues()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
*/
// const avroSource = {}
/**
*/
// const bigquerySource = {}
/**
*/
// const csvSource = {}
/**
* Source column that holds the Feature timestamp for all Feature
* values in each entity.
*/
// const featureTimeField = 'abc123'
/**
* Single Feature timestamp for all entities being imported. The
* timestamp must not have higher than millisecond precision.
*/
// const featureTime = {}
/**
* Required. The resource name of the EntityType grouping the Features for
* which values are being imported. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
*/
// const entityType = 'abc123'
/**
* Source column that holds entity IDs. If not provided, entity IDs are
* extracted from the column named `entity_id`.
*/
// const entityIdField = 'abc123'
/**
* Required. Specifications defining which Feature values to import from the
* entity. The request fails if no feature_specs are provided, and having
* multiple feature_specs for one Feature is not allowed.
*/
// const featureSpecs = 1234
/**
* If set, data will not be imported for online serving. This
* is typically used for backfilling, where Feature generation timestamps are
* not in the timestamp range needed for online serving.
*/
// const disableOnlineServing = true
/**
* Specifies the number of workers that are used to write data to the
* Featurestore. Consider the online serving capacity that you require to
* achieve the desired import throughput without interfering with online
* serving. The value must be positive, and less than or equal to 100.
* If not set, defaults to using 1 worker. The low count ensures minimal
* impact on online serving performance.
*/
// const workerCount = 1234
/**
* If true, API doesn't start ingestion analysis pipeline.
*/
// const disableIngestionAnalysis = true
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callImportFeatureValues() {
// Construct request
const request = {
entityType,
featureSpecs,
};
// Run request
const [operation] = await aiplatformClient.importFeatureValues(request);
const [response] = await operation.promise();
console.log(response);
}
callImportFeatureValues();
checkUpdateFeaturestoreProgress(name)
checkUpdateFeaturestoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.UpdateFeaturestoreOperationMetadata>>;
Check the status of the long running operation returned by updateFeaturestore()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.Featurestore, protos.google.cloud.aiplatform.v1.UpdateFeaturestoreOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* 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` (available in Preview)
*/
// const updateMask = {}
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callUpdateFeaturestore() {
// Construct request
const request = {
featurestore,
};
// Run request
const [operation] = await aiplatformClient.updateFeaturestore(request);
const [response] = await operation.promise();
console.log(response);
}
callUpdateFeaturestore();
close()
close(): Promise<void>;
Terminate the gRPC channel and close the client.
The client will no longer be usable and all future behavior is undefined.
Type | Description |
Promise<void> | {Promise} A promise that resolves when the client is closed. |
contextPath(project, location, metadataStore, context)
contextPath(project: string, location: string, metadataStore: string, context: string): string;
Return a fully-qualified context resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
context |
string
|
Type | Description |
string | {string} Resource name string. |
createEntityType(request, options)
createEntityType(request?: protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Creates a new EntityType in a given Featurestore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createEntityType(request, callback)
createEntityType(request: protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateEntityTypeRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.ICreateEntityTypeOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createFeature(request, options)
createFeature(request?: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Creates a new Feature in a given EntityType.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeatureRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the EntityType to create a Feature.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const parent = 'abc123'
/**
* Required. The Feature to create.
*/
// const feature = {}
/**
* Required. The ID to use for the Feature, which will become the final
* component of the Feature's resource name.
* This value may be up to 128 characters, and valid characters are
* `[a-z0-9_]`. The first character cannot be a number.
* The value must be unique within an EntityType.
*/
// const featureId = 'abc123'
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new FeaturestoreServiceClient();
async function callCreateFeature() {
// Construct request
const request = {
parent,
feature,
featureId,
};
// Run request
const [operation] = await aiplatformClient.createFeature(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateFeature();
createFeature(request, options, callback)
createFeature(request: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeatureRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createFeature(request, callback)
createFeature(request: protos.google.cloud.aiplatform.v1.ICreateFeatureRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeatureRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.ICreateFeatureOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createFeaturestore(request, options)
createFeaturestore(request?: protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Creates a new Featurestore in a given project and location.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createFeaturestore(request, callback)
createFeaturestore(request: protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateFeaturestoreRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.ICreateFeaturestoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
customJobPath(project, location, customJob)
customJobPath(project: string, location: string, customJob: string): string;
Return a fully-qualified customJob resource name string.
Name | Description |
project |
string
|
location |
string
|
customJob |
string
|
Type | Description |
string | {string} Resource name string. |
dataItemPath(project, location, dataset, dataItem)
dataItemPath(project: string, location: string, dataset: string, dataItem: string): string;
Return a fully-qualified dataItem resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
dataItem |
string
|
Type | Description |
string | {string} Resource name string. |
dataLabelingJobPath(project, location, dataLabelingJob)
dataLabelingJobPath(project: string, location: string, dataLabelingJob: string): string;
Return a fully-qualified dataLabelingJob resource name string.
Name | Description |
project |
string
|
location |
string
|
dataLabelingJob |
string
|
Type | Description |
string | {string} Resource name string. |
datasetPath(project, location, dataset)
datasetPath(project: string, location: string, dataset: string): string;
Return a fully-qualified dataset resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
Type | Description |
string | {string} Resource name string. |
deleteEntityType(request, options)
deleteEntityType(request?: protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a single EntityType. The EntityType must not have any Features or force
must be set to true for the request to succeed.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteEntityType(request, callback)
deleteEntityType(request: protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteEntityTypeRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteFeature(request, options)
deleteFeature(request?: protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a single Feature.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Features to be deleted.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteFeature(request, callback)
deleteFeature(request: protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeatureRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteFeaturestore(request, options)
deleteFeaturestore(request?: protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or force
must be set to true for the request to succeed.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteFeaturestore(request, callback)
deleteFeaturestore(request: protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteFeaturestoreRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
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
.
Name | Description |
request |
protos.google.longrunning.DeleteOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>
The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
Promise<protos.google.protobuf.Empty> |
const client = longrunning.operationsClient();
await client.deleteOperation({name: ''});
endpointPath(project, location, endpoint)
endpointPath(project: string, location: string, endpoint: string): string;
Return a fully-qualified endpoint resource name string.
Name | Description |
project |
string
|
location |
string
|
endpoint |
string
|
Type | Description |
string | {string} Resource name string. |
entityTypePath(project, location, featurestore, entityType)
entityTypePath(project: string, location: string, featurestore: string, entityType: string): string;
Return a fully-qualified entityType resource name string.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
entityType |
string
|
Type | Description |
string | {string} Resource name string. |
executionPath(project, location, metadataStore, execution)
executionPath(project: string, location: string, metadataStore: string, execution: string): string;
Return a fully-qualified execution resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
execution |
string
|
Type | Description |
string | {string} Resource name string. |
exportFeatureValues(request, options)
exportFeatureValues(request?: protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Exports Feature values from all the entities of a target EntityType.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Exports the latest Feature values of all entities of the EntityType
* within a time range.
*/
// const snapshotExport = {}
/**
* Exports all historical values of all entities of the EntityType within a
* time range
*/
// const fullExport = {}
/**
* Required. The resource name of the EntityType from which to export Feature
* values. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const entityType = 'abc123'
/**
* Required. Specifies destination location and format.
*/
// const destination = {}
/**
* Required. Selects Features to export values of.
*/
// const featureSelector = {}
/**
* Per-Feature export settings.
*/
// const settings = 1234
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
exportFeatureValues(request, callback)
exportFeatureValues(request: protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportFeatureValuesRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IExportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
featurePath(project, location, featurestore, entityType, feature)
featurePath(project: string, location: string, featurestore: string, entityType: string, feature: string): string;
Return a fully-qualified feature resource name string.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
entityType |
string
|
feature |
string
|
Type | Description |
string | {string} Resource name string. |
featurestorePath(project, location, featurestore)
featurestorePath(project: string, location: string, featurestore: string): string;
Return a fully-qualified featurestore resource name string.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
Type | Description |
string | {string} Resource name string. |
getEntityType(request, options)
getEntityType(request?: protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IEntityType,
protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | undefined,
{} | undefined
]>;
Gets details of a single EntityType.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IEntityType,
protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [EntityType]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getEntityType(request, callback)
getEntityType(request: protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IEntityType, protos.google.cloud.aiplatform.v1.IGetEntityTypeRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getFeature(request, options)
getFeature(request?: protos.google.cloud.aiplatform.v1.IGetFeatureRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IFeature,
protos.google.cloud.aiplatform.v1.IGetFeatureRequest | undefined,
{} | undefined
]>;
Gets details of a single Feature.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeatureRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IFeature,
protos.google.cloud.aiplatform.v1.IGetFeatureRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Feature]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Feature resource.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeatureRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getFeature(request, callback)
getFeature(request: protos.google.cloud.aiplatform.v1.IGetFeatureRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeatureRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IFeature, protos.google.cloud.aiplatform.v1.IGetFeatureRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getFeaturestore(request, options)
getFeaturestore(request?: protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IFeaturestore,
protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | undefined,
{} | undefined
]>;
Gets details of a single Featurestore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IFeaturestore,
protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Featurestore]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* 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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getFeaturestore(request, callback)
getFeaturestore(request: protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IFeaturestore, protos.google.cloud.aiplatform.v1.IGetFeaturestoreRequest | null | undefined, {} | null | undefined>
|
Type | Description |
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.
Name | Description |
request |
IamProtos.google.iam.v1.GetIamPolicyRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details. |
callback |
Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [Policy]. |
Type | Description |
Promise<IamProtos.google.iam.v1.Policy> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Policy]. The promise has a method named "cancel" which cancels the ongoing API call. |
getLocation(request, options, callback)
getLocation(request: LocationProtos.google.cloud.location.IGetLocationRequest, options?: gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>, callback?: Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>): Promise<LocationProtos.google.cloud.location.ILocation>;
Gets information about a location.
Name | Description |
request |
LocationProtos.google.cloud.location.IGetLocationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>
Call options. See CallOptions for more details. |
callback |
Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>
|
Type | Description |
Promise<LocationProtos.google.cloud.location.ILocation> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Location]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
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.
Name | Description |
request |
protos.google.longrunning.GetOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [google.longrunning.Operation]. {Promise} - The promise which resolves to an array. The first element of the array is an object representing [google.longrunning.Operation]. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
Promise<[protos.google.longrunning.Operation]> |
const client = longrunning.operationsClient();
const name = '';
const [response] = await client.getOperation({name});
// doThingsWith(response)
getProjectId()
getProjectId(): Promise<string>;
Type | Description |
Promise<string> |
getProjectId(callback)
getProjectId(callback: Callback<string, undefined, undefined>): void;
Name | Description |
callback |
Callback<string, undefined, undefined>
|
Type | Description |
void |
hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)
hyperparameterTuningJobPath(project: string, location: string, hyperparameterTuningJob: string): string;
Return a fully-qualified hyperparameterTuningJob resource name string.
Name | Description |
project |
string
|
location |
string
|
hyperparameterTuningJob |
string
|
Type | Description |
string | {string} Resource name string. |
importFeatureValues(request, options)
importFeatureValues(request?: protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Imports Feature values into the Featurestore from a source storage.
The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done.
If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done.
There are also scenarios where the caller can cause inconsistency.
- Source data for import contains multiple distinct Feature values for the same entity ID and timestamp. - Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy. - Online serving cluster is under-provisioned.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
*/
// const avroSource = {}
/**
*/
// const bigquerySource = {}
/**
*/
// const csvSource = {}
/**
* Source column that holds the Feature timestamp for all Feature
* values in each entity.
*/
// const featureTimeField = 'abc123'
/**
* Single Feature timestamp for all entities being imported. The
* timestamp must not have higher than millisecond precision.
*/
// const featureTime = {}
/**
* Required. The resource name of the EntityType grouping the Features for
* which values are being imported. Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`
*/
// const entityType = 'abc123'
/**
* Source column that holds entity IDs. If not provided, entity IDs are
* extracted from the column named `entity_id`.
*/
// const entityIdField = 'abc123'
/**
* Required. Specifications defining which Feature values to import from the
* entity. The request fails if no feature_specs are provided, and having
* multiple feature_specs for one Feature is not allowed.
*/
// const featureSpecs = 1234
/**
* If set, data will not be imported for online serving. This
* is typically used for backfilling, where Feature generation timestamps are
* not in the timestamp range needed for online serving.
*/
// const disableOnlineServing = true
/**
* Specifies the number of workers that are used to write data to the
* Featurestore. Consider the online serving capacity that you require to
* achieve the desired import throughput without interfering with online
* serving. The value must be positive, and less than or equal to 100.
* If not set, defaults to using 1 worker. The low count ensures minimal
* impact on online serving performance.
*/
// const workerCount = 1234
/**
* If true, API doesn't start ingestion analysis pipeline.
*/
// const disableIngestionAnalysis = true
// Imports the Aiplatform library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
importFeatureValues(request, callback)
importFeatureValues(request: protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportFeatureValuesRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportFeatureValuesResponse, protos.google.cloud.aiplatform.v1.IImportFeatureValuesOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
indexEndpointPath(project, location, indexEndpoint)
indexEndpointPath(project: string, location: string, indexEndpoint: string): string;
Return a fully-qualified indexEndpoint resource name string.
Name | Description |
project |
string
|
location |
string
|
indexEndpoint |
string
|
Type | Description |
string | {string} Resource name string. |
indexPath(project, location, index)
indexPath(project: string, location: string, index: string): string;
Return a fully-qualified index resource name string.
Name | Description |
project |
string
|
location |
string
|
index |
string
|
Type | Description |
string | {string} Resource name string. |
initialize()
initialize(): Promise<{
[name: string]: Function;
}>;
Initialize the client. Performs asynchronous operations (such as authentication) and prepares the client. This function will be called automatically when any class method is called for the first time, but if you need to initialize it before calling an actual method, feel free to call initialize() directly.
You can await on this method if you want to make sure the client is initialized.
Type | Description |
Promise<{
[name: string]: Function;
}> | {Promise} A promise that resolves to an authenticated service stub. |
listEntityTypes(request, options)
listEntityTypes(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IEntityType[],
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest | null,
protos.google.cloud.aiplatform.v1.IListEntityTypesResponse
]>;
Lists EntityTypes in a given Featurestore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IEntityType[],
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest | null,
protos.google.cloud.aiplatform.v1.IListEntityTypesResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [EntityType]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>
|
Type | Description |
void |
listEntityTypes(request, callback)
listEntityTypes(request: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, protos.google.cloud.aiplatform.v1.IListEntityTypesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IEntityType>
|
Type | Description |
void |
listEntityTypesAsync(request, options)
listEntityTypesAsync(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IEntityType>;
Equivalent to listEntityTypes
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IEntityType> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [EntityType]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* 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 = await aiplatformClient.listEntityTypesAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListEntityTypes();
listEntityTypesStream(request, options)
listEntityTypesStream(request?: protos.google.cloud.aiplatform.v1.IListEntityTypesRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListEntityTypesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [EntityType] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listFeatures(request, options)
listFeatures(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IFeature[],
protos.google.cloud.aiplatform.v1.IListFeaturesRequest | null,
protos.google.cloud.aiplatform.v1.IListFeaturesResponse
]>;
Lists Features in a given EntityType.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IFeature[],
protos.google.cloud.aiplatform.v1.IListFeaturesRequest | null,
protos.google.cloud.aiplatform.v1.IListFeaturesResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Feature]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturesRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>
|
Type | Description |
void |
listFeatures(request, callback)
listFeatures(request: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturesRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturesRequest, protos.google.cloud.aiplatform.v1.IListFeaturesResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeature>
|
Type | Description |
void |
listFeaturesAsync(request, options)
listFeaturesAsync(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature>;
Equivalent to listFeatures
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IFeature> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Feature]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Location to list Features.
* Format:
* `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`
*/
// const parent = 'abc123'
/**
* Lists the Features that match the filter expression. The following
* filters are supported:
* * `value_type`: Supports = and != comparisons.
* * `create_time`: Supports =, !=, <,>, >=, and <= comparisons.="" values="" must="" *="" be="" in="" rfc="" 3339="" format.="" *="" *="" `update_time`:="" supports="," !=","><,>, >=, and <= comparisons.="" values="" must="" *="" be="" in="" rfc="" 3339="" format.="" *="" *="" `labels`:="" supports="" key-value="" equality="" as="" well="" as="" key="" presence.="" *="" examples:="" *="" *="" `value_type="DOUBLE`" --=""> Features whose type is DOUBLE.
* * `create_time > \"2020-01-31T15:30:00.000000Z\" OR
* update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created
* or updated after 2020-01-31T15:30:00.000000Z.
* * `labels.active = yes AND labels.env = prod` --> Features having both
* (active: yes) and (env: prod) labels.
* * `labels.env: *` --> Any Feature which has a label with 'env' as the
* key.
*/
// const filter = 'abc123'
/**
* The maximum number of Features to return. The service may return fewer
* than this value. If unspecified, at most 1000 Features will be returned.
* The maximum value is 1000; any value greater than 1000 will be coerced to
* 1000.
*/
// const pageSize = 1234
/**
* A page token, received from a previous
* FeaturestoreService.ListFeatures google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures
* call. Provide this to retrieve the subsequent page.
* When paginating, all other parameters provided to
* FeaturestoreService.ListFeatures google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures
* must match the call that provided the page token.
*/
// const pageToken = 'abc123'
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
* Supported fields:
* * `feature_id`
* * `value_type`
* * `create_time`
* * `update_time`
*/
// const orderBy = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
/**
* If set, return the most recent
* ListFeaturesRequest.latest_stats_count google.cloud.aiplatform.v1.ListFeaturesRequest.latest_stats_count
* of stats for each Feature in response. Valid value is 0, 10. If number of
* stats exists < *="" listfeaturesrequest.latest_stats_count="" google.cloud.aiplatform.v1.listfeaturesrequest.latest_stats_count,="" *="" return="" all="" existing="" stats.="" */="" const="" lateststatscount="1234" imports="" the="" aiplatform="" library="" const="" {featurestoreserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" featurestoreserviceclient();="" async="" function="" calllistfeatures()="" {="" construct="" request="" const="" request="{" parent,="" };="" run="" request="" const="" iterable="await" aiplatformclient.listfeaturesasync(request);="" for="" await="" (const="" response="" of="" iterable)="" {="" console.log(response);="" }="" }="" calllistfeatures();="">
listFeaturesStream(request, options)
listFeaturesStream(request?: protos.google.cloud.aiplatform.v1.IListFeaturesRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [Feature] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listFeaturestores(request, options)
listFeaturestores(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IFeaturestore[],
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest | null,
protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse
]>;
Lists Featurestores in a given project and location.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IFeaturestore[],
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest | null,
protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Featurestore]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
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;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>
|
Type | Description |
void |
listFeaturestores(request, callback)
listFeaturestores(request: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, protos.google.cloud.aiplatform.v1.IListFeaturestoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IFeaturestore>
|
Type | Description |
void |
listFeaturestoresAsync(request, options)
listFeaturestoresAsync(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IFeaturestore>;
Equivalent to listFeaturestores
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IFeaturestore> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Featurestore]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* 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 = await aiplatformClient.listFeaturestoresAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListFeaturestores();
listFeaturestoresStream(request, options)
listFeaturestoresStream(request?: protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListFeaturestoresRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [Featurestore] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
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.
Name | Description |
request |
LocationProtos.google.cloud.location.IListLocationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<LocationProtos.google.cloud.location.ILocation> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Location]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
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.
Name | Description |
request |
protos.google.longrunning.ListOperationsRequest
The request object that will be sent. |
options |
gax.CallOptions
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
Type | Description |
AsyncIterable<protos.google.longrunning.ListOperationsResponse> | {Object} An iterable Object that conforms to https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols. |
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.
Name | Description |
project |
string
|
location |
string
|
Type | Description |
string | {string} Resource name string. |
matchAnnotationFromAnnotationName(annotationName)
matchAnnotationFromAnnotationName(annotationName: string): string | number;
Parse the annotation from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the annotation. |
matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)
matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the annotation_spec from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the annotation_spec. |
matchArtifactFromArtifactName(artifactName)
matchArtifactFromArtifactName(artifactName: string): string | number;
Parse the artifact from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the artifact. |
matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)
matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the batch_prediction_job from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the batch_prediction_job. |
matchContextFromContextName(contextName)
matchContextFromContextName(contextName: string): string | number;
Parse the context from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the context. |
matchCustomJobFromCustomJobName(customJobName)
matchCustomJobFromCustomJobName(customJobName: string): string | number;
Parse the custom_job from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the custom_job. |
matchDataItemFromAnnotationName(annotationName)
matchDataItemFromAnnotationName(annotationName: string): string | number;
Parse the data_item from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the data_item. |
matchDataItemFromDataItemName(dataItemName)
matchDataItemFromDataItemName(dataItemName: string): string | number;
Parse the data_item from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the data_item. |
matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)
matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the data_labeling_job from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the data_labeling_job. |
matchDatasetFromAnnotationName(annotationName)
matchDatasetFromAnnotationName(annotationName: string): string | number;
Parse the dataset from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromAnnotationSpecName(annotationSpecName)
matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the dataset from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromDataItemName(dataItemName)
matchDatasetFromDataItemName(dataItemName: string): string | number;
Parse the dataset from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromDatasetName(datasetName)
matchDatasetFromDatasetName(datasetName: string): string | number;
Parse the dataset from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromSavedQueryName(savedQueryName)
matchDatasetFromSavedQueryName(savedQueryName: string): string | number;
Parse the dataset from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchEndpointFromEndpointName(endpointName)
matchEndpointFromEndpointName(endpointName: string): string | number;
Parse the endpoint from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the endpoint. |
matchEntityTypeFromEntityTypeName(entityTypeName)
matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;
Parse the entity_type from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEntityTypeFromFeatureName(featureName)
matchEntityTypeFromFeatureName(featureName: string): string | number;
Parse the entity_type from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEvaluationFromModelEvaluationName(modelEvaluationName)
matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the evaluation from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the evaluation from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchExecutionFromExecutionName(executionName)
matchExecutionFromExecutionName(executionName: string): string | number;
Parse the execution from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the execution. |
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the experiment from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardRunName(tensorboardRunName)
matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the experiment from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the experiment from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchFeatureFromFeatureName(featureName)
matchFeatureFromFeatureName(featureName: string): string | number;
Parse the feature from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the feature. |
matchFeaturestoreFromEntityTypeName(entityTypeName)
matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;
Parse the featurestore from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeatureName(featureName)
matchFeaturestoreFromFeatureName(featureName: string): string | number;
Parse the featurestore from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeaturestoreName(featurestoreName)
matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;
Parse the featurestore from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the hyperparameter_tuning_job. |
matchIndexEndpointFromIndexEndpointName(indexEndpointName)
matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the index_endpoint from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the index_endpoint. |
matchIndexFromIndexName(indexName)
matchIndexFromIndexName(indexName: string): string | number;
Parse the index from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the index. |
matchLocationFromAnnotationName(annotationName)
matchLocationFromAnnotationName(annotationName: string): string | number;
Parse the location from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromAnnotationSpecName(annotationSpecName)
matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the location from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromArtifactName(artifactName)
matchLocationFromArtifactName(artifactName: string): string | number;
Parse the location from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromBatchPredictionJobName(batchPredictionJobName)
matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the location from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromContextName(contextName)
matchLocationFromContextName(contextName: string): string | number;
Parse the location from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromCustomJobName(customJobName)
matchLocationFromCustomJobName(customJobName: string): string | number;
Parse the location from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataItemName(dataItemName)
matchLocationFromDataItemName(dataItemName: string): string | number;
Parse the location from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataLabelingJobName(dataLabelingJobName)
matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the location from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDatasetName(datasetName)
matchLocationFromDatasetName(datasetName: string): string | number;
Parse the location from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEndpointName(endpointName)
matchLocationFromEndpointName(endpointName: string): string | number;
Parse the location from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEntityTypeName(entityTypeName)
matchLocationFromEntityTypeName(entityTypeName: string): string | number;
Parse the location from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromExecutionName(executionName)
matchLocationFromExecutionName(executionName: string): string | number;
Parse the location from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeatureName(featureName)
matchLocationFromFeatureName(featureName: string): string | number;
Parse the location from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeaturestoreName(featurestoreName)
matchLocationFromFeaturestoreName(featurestoreName: string): string | number;
Parse the location from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the location from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexEndpointName(indexEndpointName)
matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the location from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexName(indexName)
matchLocationFromIndexName(indexName: string): string | number;
Parse the location from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromLocationName(locationName)
matchLocationFromLocationName(locationName: string): string | number;
Parse the location from Location resource.
Name | Description |
locationName |
string
A fully-qualified path representing Location resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataSchemaName(metadataSchemaName)
matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the location from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataStoreName(metadataStoreName)
matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the location from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the location from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationName(modelEvaluationName)
matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the location from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the location from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelName(modelName)
matchLocationFromModelName(modelName: string): string | number;
Parse the location from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromPipelineJobName(pipelineJobName)
matchLocationFromPipelineJobName(pipelineJobName: string): string | number;
Parse the location from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromSavedQueryName(savedQueryName)
matchLocationFromSavedQueryName(savedQueryName: string): string | number;
Parse the location from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromSpecialistPoolName(specialistPoolName)
matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the location from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromStudyName(studyName)
matchLocationFromStudyName(studyName: string): string | number;
Parse the location from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardExperimentName(tensorboardExperimentName)
matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the location from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardName(tensorboardName)
matchLocationFromTensorboardName(tensorboardName: string): string | number;
Parse the location from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardRunName(tensorboardRunName)
matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the location from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the location from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrainingPipelineName(trainingPipelineName)
matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the location from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrialName(trialName)
matchLocationFromTrialName(trialName: string): string | number;
Parse the location from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_schema from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_schema. |
matchMetadataStoreFromArtifactName(artifactName)
matchMetadataStoreFromArtifactName(artifactName: string): string | number;
Parse the metadata_store from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromContextName(contextName)
matchMetadataStoreFromContextName(contextName: string): string | number;
Parse the metadata_store from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromExecutionName(executionName)
matchMetadataStoreFromExecutionName(executionName: string): string | number;
Parse the metadata_store from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_store from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataStoreName(metadataStoreName)
matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the metadata_store from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the model_deployment_monitoring_job from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the model_deployment_monitoring_job. |
matchModelFromModelEvaluationName(modelEvaluationName)
matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the model from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the model from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelName(modelName)
matchModelFromModelName(modelName: string): string | number;
Parse the model from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchPipelineJobFromPipelineJobName(pipelineJobName)
matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;
Parse the pipeline_job from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the pipeline_job. |
matchProjectFromAnnotationName(annotationName)
matchProjectFromAnnotationName(annotationName: string): string | number;
Parse the project from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromAnnotationSpecName(annotationSpecName)
matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the project from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromArtifactName(artifactName)
matchProjectFromArtifactName(artifactName: string): string | number;
Parse the project from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromBatchPredictionJobName(batchPredictionJobName)
matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the project from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromContextName(contextName)
matchProjectFromContextName(contextName: string): string | number;
Parse the project from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromCustomJobName(customJobName)
matchProjectFromCustomJobName(customJobName: string): string | number;
Parse the project from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataItemName(dataItemName)
matchProjectFromDataItemName(dataItemName: string): string | number;
Parse the project from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataLabelingJobName(dataLabelingJobName)
matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the project from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDatasetName(datasetName)
matchProjectFromDatasetName(datasetName: string): string | number;
Parse the project from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEndpointName(endpointName)
matchProjectFromEndpointName(endpointName: string): string | number;
Parse the project from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEntityTypeName(entityTypeName)
matchProjectFromEntityTypeName(entityTypeName: string): string | number;
Parse the project from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromExecutionName(executionName)
matchProjectFromExecutionName(executionName: string): string | number;
Parse the project from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeatureName(featureName)
matchProjectFromFeatureName(featureName: string): string | number;
Parse the project from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeaturestoreName(featurestoreName)
matchProjectFromFeaturestoreName(featurestoreName: string): string | number;
Parse the project from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the project from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexEndpointName(indexEndpointName)
matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the project from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexName(indexName)
matchProjectFromIndexName(indexName: string): string | number;
Parse the project from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromLocationName(locationName)
matchProjectFromLocationName(locationName