Struct FeaturestoreService 

pub struct FeaturestoreService { /* private fields */ }

Available on crate feature featurestore-service only.

Implements a client for the Vertex AI API.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
    let client = FeaturestoreService::builder().build().await?;
    let parent = "parent_value";
    let mut list = client.list_featurestores()
        .set_parent(parent)
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }

Service Description

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

Configuration

To configure FeaturestoreService use the with_* methods in the type returned by builder(). The default configuration should work for most applications. Common configuration changes include

• with_endpoint(): by default this client uses the global default endpoint (https://aiplatform.googleapis.com). Applications using regional endpoints or running in restricted networks (e.g. a network configured override this default.
• with_credentials(): by default this client uses Application Default Credentials. Applications using custom authentication may need to override this default.

Pooling and Cloning

FeaturestoreService holds a connection pool internally, it is advised to create one and reuse it. You do not need to wrap FeaturestoreService in an Rc or Arc to reuse it, because it already uses an Arc internally.

Implementations

impl FeaturestoreService

pub fn builder() -> ClientBuilder

Returns a builder for FeaturestoreService.

let client = FeaturestoreService::builder().build().await?;

pub fn from_stub<T>(stub: T) -> Self

where T: FeaturestoreService + 'static,

Creates a new client from the provided stub.

The most common case for calling this function is in tests mocking the client’s behavior.

pub fn create_featurestore(&self) -> CreateFeaturestore

Creates a new Featurestore in a given project and location.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::model::Featurestore;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let response = client.create_featurestore()
        .set_parent(parent)
        .set_featurestore_id("featurestore_id_value")
        .set_featurestore(
            Featurestore::new()/* set fields */
        )
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn get_featurestore(&self) -> GetFeaturestore

Gets details of a single Featurestore.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.get_featurestore()
        .set_name(name)
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn list_featurestores(&self) -> ListFeaturestores

Lists Featurestores in a given project and location.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let mut list = client.list_featurestores()
        .set_parent(parent)
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn update_featurestore(&self) -> UpdateFeaturestore

Updates the parameters of a single Featurestore.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_wkt::FieldMask;
use google_cloud_aiplatform_v1::model::Featurestore;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.update_featurestore()
        .set_featurestore(
            Featurestore::new().set_name(name)/* set fields */
        )
        .set_update_mask(FieldMask::default().set_paths(["updated.field.path1", "updated.field.path2"]))
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn delete_featurestore(&self) -> DeleteFeaturestore

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

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    client.delete_featurestore()
        .set_name(name)
        .poller().until_done().await?;
    Ok(())
}

pub fn create_entity_type(&self) -> CreateEntityType

Creates a new EntityType in a given Featurestore.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::model::EntityType;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let response = client.create_entity_type()
        .set_parent(parent)
        .set_entity_type(
            EntityType::new()/* set fields */
        )
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn get_entity_type(&self) -> GetEntityType

Gets details of a single EntityType.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.get_entity_type()
        .set_name(name)
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn list_entity_types(&self) -> ListEntityTypes

Lists EntityTypes in a given Featurestore.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let mut list = client.list_entity_types()
        .set_parent(parent)
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn update_entity_type(&self) -> UpdateEntityType

Updates the parameters of a single EntityType.

Example

use google_cloud_wkt::FieldMask;
use google_cloud_aiplatform_v1::model::EntityType;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.update_entity_type()
        .set_entity_type(
            EntityType::new().set_name(name)/* set fields */
        )
        .set_update_mask(FieldMask::default().set_paths(["updated.field.path1", "updated.field.path2"]))
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn delete_entity_type(&self) -> DeleteEntityType

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

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    client.delete_entity_type()
        .set_name(name)
        .poller().until_done().await?;
    Ok(())
}

pub fn create_feature(&self) -> CreateFeature

Creates a new Feature in a given EntityType.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::model::Feature;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let response = client.create_feature()
        .set_parent(parent)
        .set_feature_id("feature_id_value")
        .set_feature(
            Feature::new()/* set fields */
        )
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn batch_create_features(&self) -> BatchCreateFeatures

Creates a batch of Features in a given EntityType.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.batch_create_features()
        /* set fields */
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn get_feature(&self) -> GetFeature

Gets details of a single Feature.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.get_feature()
        .set_name(name)
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn list_features(&self) -> ListFeatures

Lists Features in a given EntityType.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, parent: &str
) -> Result<()> {
    let mut list = client.list_features()
        .set_parent(parent)
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn update_feature(&self) -> UpdateFeature

Updates the parameters of a single Feature.

Example

use google_cloud_wkt::FieldMask;
use google_cloud_aiplatform_v1::model::Feature;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    let response = client.update_feature()
        .set_feature(
            Feature::new().set_name(name)/* set fields */
        )
        .set_update_mask(FieldMask::default().set_paths(["updated.field.path1", "updated.field.path2"]))
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn delete_feature(&self) -> DeleteFeature

Deletes a single Feature.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService, name: &str
) -> Result<()> {
    client.delete_feature()
        .set_name(name)
        .poller().until_done().await?;
    Ok(())
}

pub fn import_feature_values(&self) -> ImportFeatureValues

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.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.import_feature_values()
        /* set fields */
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn batch_read_feature_values(&self) -> BatchReadFeatureValues

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.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.batch_read_feature_values()
        /* set fields */
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn export_feature_values(&self) -> ExportFeatureValues

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

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.export_feature_values()
        /* set fields */
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn delete_feature_values(&self) -> DeleteFeatureValues

Delete Feature values from Featurestore.

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

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

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

Example

use google_cloud_lro::Poller;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.delete_feature_values()
        /* set fields */
        .poller().until_done().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn search_features(&self) -> SearchFeatures

Searches Features matching a query in a given project.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let mut list = client.search_features()
        /* set fields */
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn list_locations(&self) -> ListLocations

Lists information about the supported locations for this service.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let mut list = client.list_locations()
        /* set fields */
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn get_location(&self) -> GetLocation

Gets information about a location.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.get_location()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn set_iam_policy(&self) -> SetIamPolicy

Sets the access control policy on the specified resource. Replaces any existing policy.

Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.set_iam_policy()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn get_iam_policy(&self) -> GetIamPolicy

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

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.get_iam_policy()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn test_iam_permissions(&self) -> TestIamPermissions

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

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

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.test_iam_permissions()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn list_operations(&self) -> ListOperations

Provides the Operations service functionality in this service.

Example

use google_cloud_gax::paginator::ItemPaginator as _;
use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let mut list = client.list_operations()
        /* set fields */
        .by_item();
    while let Some(item) = list.next().await.transpose()? {
        println!("{:?}", item);
    }
    Ok(())
}

pub fn get_operation(&self) -> GetOperation

Provides the Operations service functionality in this service.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.get_operation()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

pub fn delete_operation(&self) -> DeleteOperation

Provides the Operations service functionality in this service.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    client.delete_operation()
        /* set fields */
        .send().await?;
    Ok(())
}

pub fn cancel_operation(&self) -> CancelOperation

Provides the Operations service functionality in this service.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    client.cancel_operation()
        /* set fields */
        .send().await?;
    Ok(())
}

pub fn wait_operation(&self) -> WaitOperation

Provides the Operations service functionality in this service.

Example

use google_cloud_aiplatform_v1::Result;
async fn sample(
   client: &FeaturestoreService
) -> Result<()> {
    let response = client.wait_operation()
        /* set fields */
        .send().await?;
    println!("response {:?}", response);
    Ok(())
}

Trait Implementations

impl Clone for FeaturestoreService

fn clone(&self) -> FeaturestoreService

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FeaturestoreService

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.