entity_types

Creates, updates, deletes, gets or lists an entity_types resource.

Overview

Name	entity_types
Type	Resource
Id	google.aiplatform.entity_types

Fields

The following fields are returned by SELECT queries:

get

Successful response

Name	Datatype	Description
name	string	Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
createTime	string (google-datetime)	Output only. Timestamp when this EntityType was created.
description	string	Optional. Description of the EntityType.
etag	string	Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels	object	Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
monitoringConfig	object	Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled. (id: GoogleCloudAiplatformV1FeaturestoreMonitoringConfig)
offlineStorageTtlDays	integer (int32)	Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
satisfiesPzi	boolean	Output only. Reserved for future use.
satisfiesPzs	boolean	Output only. Reserved for future use.
updateTime	string (google-datetime)	Output only. Timestamp when this EntityType was most recently updated.

list

Successful response

Name	Datatype	Description
name	string	Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
createTime	string (google-datetime)	Output only. Timestamp when this EntityType was created.
description	string	Optional. Description of the EntityType.
etag	string	Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels	object	Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
monitoringConfig	object	Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled. (id: GoogleCloudAiplatformV1FeaturestoreMonitoringConfig)
offlineStorageTtlDays	integer (int32)	Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
satisfiesPzi	boolean	Output only. Reserved for future use.
satisfiesPzs	boolean	Output only. Reserved for future use.
updateTime	string (google-datetime)	Output only. Timestamp when this EntityType was most recently updated.

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
get	select	projectsId, locationsId, featurestoresId, entityTypesId		Gets details of a single EntityType.
list	select	projectsId, locationsId, featurestoresId	filter, pageSize, pageToken, orderBy, readMask	Lists EntityTypes in a given Featurestore.
create	insert	projectsId, locationsId, featurestoresId	entityTypeId	Creates a new EntityType in a given Featurestore.
patch	update	projectsId, locationsId, featurestoresId, entityTypesId	updateMask	Updates the parameters of a single EntityType.
delete	delete	projectsId, locationsId, featurestoresId, entityTypesId	force	Deletes a single EntityType. The EntityType must not have any Features or force must be set to true for the request to succeed.
read_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.
streaming_read_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.
write_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.
import_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		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.
export_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		Exports Feature values from all the entities of a target EntityType.
delete_feature_values	exec	projectsId, locationsId, featurestoresId, entityTypesId		Delete Feature values from Featurestore. The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done. If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
entityTypesId	string
featurestoresId	string
locationsId	string
projectsId	string
entityTypeId	string
filter	string
force	boolean
orderBy	string
pageSize	integer (int32)
pageToken	string
readMask	string (google-fieldmask)
updateMask	string (google-fieldmask)

SELECT examples

get

Gets details of a single EntityType.

SELECT
name,
createTime,
description,
etag,
labels,
monitoringConfig,
offlineStorageTtlDays,
satisfiesPzi,
satisfiesPzs,
updateTime
FROM google.aiplatform.entity_types
WHERE projectsId = '{{ projectsId }}' -- required
AND locationsId = '{{ locationsId }}' -- required
AND featurestoresId = '{{ featurestoresId }}' -- required
AND entityTypesId = '{{ entityTypesId }}' -- required;

list

Lists EntityTypes in a given Featurestore.

SELECT
name,
createTime,
description,
etag,
labels,
monitoringConfig,
offlineStorageTtlDays,
satisfiesPzi,
satisfiesPzs,
updateTime
FROM google.aiplatform.entity_types
WHERE projectsId = '{{ projectsId }}' -- required
AND locationsId = '{{ locationsId }}' -- required
AND featurestoresId = '{{ featurestoresId }}' -- required
AND filter = '{{ filter }}'
AND pageSize = '{{ pageSize }}'
AND pageToken = '{{ pageToken }}'
AND orderBy = '{{ orderBy }}'
AND readMask = '{{ readMask }}';

INSERT examples

create

Creates a new EntityType in a given Featurestore.

INSERT INTO google.aiplatform.entity_types (
data__name,
data__description,
data__labels,
data__etag,
data__monitoringConfig,
data__offlineStorageTtlDays,
projectsId,
locationsId,
featurestoresId,
entityTypeId
)
SELECT 
'{{ name }}',
'{{ description }}',
'{{ labels }}',
'{{ etag }}',
'{{ monitoringConfig }}',
{{ offlineStorageTtlDays }},
'{{ projectsId }}',
'{{ locationsId }}',
'{{ featurestoresId }}',
'{{ entityTypeId }}'
RETURNING
name,
done,
error,
metadata,
response
;

Manifest

# Description fields are for documentation purposes
- name: entity_types
  props:
    - name: projectsId
      value: string
      description: Required parameter for the entity_types resource.
    - name: locationsId
      value: string
      description: Required parameter for the entity_types resource.
    - name: featurestoresId
      value: string
      description: Required parameter for the entity_types resource.
    - name: name
      value: string
      description: >
        Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
        
    - name: description
      value: string
      description: >
        Optional. Description of the EntityType.
        
    - name: labels
      value: object
      description: >
        Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
        
    - name: etag
      value: string
      description: >
        Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
        
    - name: monitoringConfig
      value: object
      description: >
        Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
        
    - name: offlineStorageTtlDays
      value: integer
      description: >
        Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
        
    - name: entityTypeId
      value: string

UPDATE examples

patch

Updates the parameters of a single EntityType.

UPDATE google.aiplatform.entity_types
SET 
data__name = '{{ name }}',
data__description = '{{ description }}',
data__labels = '{{ labels }}',
data__etag = '{{ etag }}',
data__monitoringConfig = '{{ monitoringConfig }}',
data__offlineStorageTtlDays = {{ offlineStorageTtlDays }}
WHERE 
projectsId = '{{ projectsId }}' --required
AND locationsId = '{{ locationsId }}' --required
AND featurestoresId = '{{ featurestoresId }}' --required
AND entityTypesId = '{{ entityTypesId }}' --required
AND updateMask = '{{ updateMask}}'
RETURNING
name,
createTime,
description,
etag,
labels,
monitoringConfig,
offlineStorageTtlDays,
satisfiesPzi,
satisfiesPzs,
updateTime;

DELETE examples

delete

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

DELETE FROM google.aiplatform.entity_types
WHERE projectsId = '{{ projectsId }}' --required
AND locationsId = '{{ locationsId }}' --required
AND featurestoresId = '{{ featurestoresId }}' --required
AND entityTypesId = '{{ entityTypesId }}' --required
AND force = '{{ force }}';

Lifecycle Methods

read_feature_values

Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.

EXEC google.aiplatform.entity_types.read_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"entityId": "{{ entityId }}", 
"featureSelector": "{{ featureSelector }}"
}';

streaming_read_feature_values

Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.

EXEC google.aiplatform.entity_types.streaming_read_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"entityIds": "{{ entityIds }}", 
"featureSelector": "{{ featureSelector }}"
}';

write_feature_values

Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.

EXEC google.aiplatform.entity_types.write_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"payloads": "{{ payloads }}"
}';

import_feature_values

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.

EXEC google.aiplatform.entity_types.import_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"avroSource": "{{ avroSource }}", 
"bigquerySource": "{{ bigquerySource }}", 
"csvSource": "{{ csvSource }}", 
"featureTimeField": "{{ featureTimeField }}", 
"featureTime": "{{ featureTime }}", 
"entityIdField": "{{ entityIdField }}", 
"featureSpecs": "{{ featureSpecs }}", 
"disableOnlineServing": {{ disableOnlineServing }}, 
"workerCount": {{ workerCount }}, 
"disableIngestionAnalysis": {{ disableIngestionAnalysis }}
}';

export_feature_values

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

EXEC google.aiplatform.entity_types.export_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"snapshotExport": "{{ snapshotExport }}", 
"fullExport": "{{ fullExport }}", 
"destination": "{{ destination }}", 
"featureSelector": "{{ featureSelector }}", 
"settings": "{{ settings }}"
}';

delete_feature_values

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.

EXEC google.aiplatform.entity_types.delete_feature_values 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@featurestoresId='{{ featurestoresId }}' --required, 
@entityTypesId='{{ entityTypesId }}' --required 
@@json=
'{
"selectEntity": "{{ selectEntity }}", 
"selectTimeRangeAndFeature": "{{ selectTimeRangeAndFeature }}"
}';