Source code for airflow.providers.google.cloud.operators.vertex_ai.dataset

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"""This module contains Google Vertex AI operators."""

from __future__ import annotations

from typing import TYPE_CHECKING, Sequence

from google.api_core.exceptions import NotFound
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.cloud.aiplatform_v1.types import Dataset, ExportDataConfig, ImportDataConfig

from airflow.providers.google.cloud.hooks.vertex_ai.dataset import DatasetHook
from airflow.providers.google.cloud.links.vertex_ai import VertexAIDatasetLink, VertexAIDatasetListLink
from airflow.providers.google.cloud.operators.cloud_base import GoogleCloudBaseOperator

if TYPE_CHECKING:
    from google.api_core.retry import Retry
    from google.protobuf.field_mask_pb2 import FieldMask

    from airflow.utils.context import Context


[docs]class CreateDatasetOperator(GoogleCloudBaseOperator): """ Creates a Dataset. :param project_id: Required. The ID of the Google Cloud project the cluster belongs to. :param region: Required. The Cloud Dataproc region in which to handle the request. :param dataset: Required. The Dataset to create. This corresponds to the ``dataset`` field on the ``request`` instance; if ``request`` is provided, this should not be set. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, dataset: Dataset | dict, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.dataset = dataset self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) self.log.info("Creating dataset") operation = hook.create_dataset( project_id=self.project_id, region=self.region, dataset=self.dataset, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = hook.wait_for_operation(timeout=self.timeout, operation=operation) dataset = Dataset.to_dict(result) dataset_id = hook.extract_dataset_id(dataset) self.log.info("Dataset was created. Dataset id: %s", dataset_id) self.xcom_push(context, key="dataset_id", value=dataset_id) VertexAIDatasetLink.persist(context=context, task_instance=self, dataset_id=dataset_id) return dataset
[docs]class GetDatasetOperator(GoogleCloudBaseOperator): """ Get a Dataset. :param project_id: Required. The ID of the Google Cloud project the cluster belongs to. :param region: Required. The Cloud Dataproc region in which to handle the request. :param dataset_id: Required. The ID of the Dataset to get. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "dataset_id", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, dataset_id: str, read_mask: str | None = None, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.dataset_id = dataset_id self.read_mask = read_mask self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) try: self.log.info("Get dataset: %s", self.dataset_id) dataset_obj = hook.get_dataset( project_id=self.project_id, region=self.region, dataset=self.dataset_id, read_mask=self.read_mask, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) VertexAIDatasetLink.persist(context=context, task_instance=self, dataset_id=self.dataset_id) self.log.info("Dataset was gotten.") return Dataset.to_dict(dataset_obj) except NotFound: self.log.info("The Dataset ID %s does not exist.", self.dataset_id)
[docs]class DeleteDatasetOperator(GoogleCloudBaseOperator): """ Deletes a Dataset. :param project_id: Required. The ID of the Google Cloud project the cluster belongs to. :param region: Required. The Cloud Dataproc region in which to handle the request. :param dataset_id: Required. The ID of the Dataset to delete. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "dataset_id", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, dataset_id: str, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.dataset_id = dataset_id self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) try: self.log.info("Deleting dataset: %s", self.dataset_id) operation = hook.delete_dataset( project_id=self.project_id, region=self.region, dataset=self.dataset_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) hook.wait_for_operation(timeout=self.timeout, operation=operation) self.log.info("Dataset was deleted.") except NotFound: self.log.info("The Dataset ID %s does not exist.", self.dataset_id)
[docs]class ExportDataOperator(GoogleCloudBaseOperator): """ Exports data from a Dataset. :param project_id: Required. The ID of the Google Cloud project the cluster belongs to. :param region: Required. The Cloud Dataproc region in which to handle the request. :param dataset_id: Required. The ID of the Dataset to delete. :param export_config: Required. The desired output location. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "dataset_id", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, dataset_id: str, export_config: ExportDataConfig | dict, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.dataset_id = dataset_id self.export_config = export_config self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) self.log.info("Exporting data: %s", self.dataset_id) operation = hook.export_data( project_id=self.project_id, region=self.region, dataset=self.dataset_id, export_config=self.export_config, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) hook.wait_for_operation(timeout=self.timeout, operation=operation) self.log.info("Export was done successfully")
[docs]class ImportDataOperator(GoogleCloudBaseOperator): """ Imports data into a Dataset. :param project_id: Required. The ID of the Google Cloud project the cluster belongs to. :param region: Required. The Cloud Dataproc region in which to handle the request. :param dataset_id: Required. The ID of the Dataset to delete. :param import_configs: Required. The desired input locations. The contents of all input locations will be imported in one batch. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "dataset_id", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, dataset_id: str, import_configs: Sequence[ImportDataConfig] | list, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.dataset_id = dataset_id self.import_configs = import_configs self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) self.log.info("Importing data: %s", self.dataset_id) operation = hook.import_data( project_id=self.project_id, region=self.region, dataset=self.dataset_id, import_configs=self.import_configs, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) hook.wait_for_operation(timeout=self.timeout, operation=operation) self.log.info("Import was done successfully")
[docs]class ListDatasetsOperator(GoogleCloudBaseOperator): """ Lists Datasets in a Location. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param filter: The standard list filter. :param page_size: The standard list page size. :param page_token: The standard list page token. :param read_mask: Mask specifying which fields to read. :param order_by: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "project_id", "impersonation_chain")
def __init__( self, *, region: str, project_id: str, filter: str | None = None, page_size: int | None = None, page_token: str | None = None, read_mask: str | None = None, order_by: str | None = None, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.filter = filter self.page_size = page_size self.page_token = page_token self.read_mask = read_mask self.order_by = order_by self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) results = hook.list_datasets( project_id=self.project_id, region=self.region, filter=self.filter, page_size=self.page_size, page_token=self.page_token, read_mask=self.read_mask, order_by=self.order_by, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) VertexAIDatasetListLink.persist(context=context, task_instance=self) return [Dataset.to_dict(result) for result in results]
[docs]class UpdateDatasetOperator(GoogleCloudBaseOperator): """ Updates a Dataset. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param dataset_id: Required. The ID of the Dataset to update. :param dataset: Required. The Dataset which replaces the resource on the server. :param update_mask: Required. The update mask applies to the resource. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields = ("region", "dataset_id", "project_id", "impersonation_chain")
def __init__( self, *, project_id: str, region: str, dataset_id: str, dataset: Dataset | dict, update_mask: FieldMask | dict, retry: Retry | _MethodDefault = DEFAULT, timeout: float | None = None, metadata: Sequence[tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.project_id = project_id self.region = region self.dataset_id = dataset_id self.dataset = dataset self.update_mask = update_mask self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context): hook = DatasetHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) self.log.info("Updating dataset: %s", self.dataset_id) result = hook.update_dataset( project_id=self.project_id, region=self.region, dataset_id=self.dataset_id, dataset=self.dataset, update_mask=self.update_mask, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) self.log.info("Dataset was updated") return Dataset.to_dict(result)

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