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"""
This module contains Azure Data Lake Storage to
Google Cloud Storage operator.
"""
import os
from tempfile import NamedTemporaryFile
from typing import TYPE_CHECKING, Optional, Sequence, Union
from airflow.providers.google.cloud.hooks.gcs import GCSHook, _parse_gcs_url
from airflow.providers.microsoft.azure.hooks.data_lake import AzureDataLakeHook
from airflow.providers.microsoft.azure.operators.adls import ADLSListOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class ADLSToGCSOperator(ADLSListOperator):
"""
Synchronizes an Azure Data Lake Storage path with a GCS bucket
:param src_adls: The Azure Data Lake path to find the objects (templated)
:param dest_gcs: The Google Cloud Storage bucket and prefix to
store the objects. (templated)
:param replace: If true, replaces same-named files in GCS
:param gzip: Option to compress file for upload
:param azure_data_lake_conn_id: The connection ID to use when
connecting to Azure Data Lake Storage.
:param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud.
:param delegate_to: Google account to impersonate using domain-wide delegation of authority,
if any. For this to work, the service account making the request must have
domain-wide delegation enabled.
:param google_impersonation_chain: Optional Google 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).
**Examples**:
The following Operator would copy a single file named
``hello/world.avro`` from ADLS to the GCS bucket ``mybucket``. Its full
resulting gcs path will be ``gs://mybucket/hello/world.avro`` ::
copy_single_file = AdlsToGoogleCloudStorageOperator(
task_id='copy_single_file',
src_adls='hello/world.avro',
dest_gcs='gs://mybucket',
replace=False,
azure_data_lake_conn_id='azure_data_lake_default',
gcp_conn_id='google_cloud_default'
)
The following Operator would copy all parquet files from ADLS
to the GCS bucket ``mybucket``. ::
copy_all_files = AdlsToGoogleCloudStorageOperator(
task_id='copy_all_files',
src_adls='*.parquet',
dest_gcs='gs://mybucket',
replace=False,
azure_data_lake_conn_id='azure_data_lake_default',
gcp_conn_id='google_cloud_default'
)
The following Operator would copy all parquet files from ADLS
path ``/hello/world``to the GCS bucket ``mybucket``. ::
copy_world_files = AdlsToGoogleCloudStorageOperator(
task_id='copy_world_files',
src_adls='hello/world/*.parquet',
dest_gcs='gs://mybucket',
replace=False,
azure_data_lake_conn_id='azure_data_lake_default',
gcp_conn_id='google_cloud_default'
)
"""
[docs] template_fields: Sequence[str] = (
'src_adls',
'dest_gcs',
'google_impersonation_chain',
)
def __init__(
self,
*,
src_adls: str,
dest_gcs: str,
azure_data_lake_conn_id: str,
gcp_conn_id: str = 'google_cloud_default',
delegate_to: Optional[str] = None,
replace: bool = False,
gzip: bool = False,
google_impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
**kwargs,
) -> None:
super().__init__(path=src_adls, azure_data_lake_conn_id=azure_data_lake_conn_id, **kwargs)
self.src_adls = src_adls
self.dest_gcs = dest_gcs
self.replace = replace
self.gcp_conn_id = gcp_conn_id
self.delegate_to = delegate_to
self.gzip = gzip
self.google_impersonation_chain = google_impersonation_chain
[docs] def execute(self, context: 'Context'):
# use the super to list all files in an Azure Data Lake path
files = super().execute(context)
g_hook = GCSHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
impersonation_chain=self.google_impersonation_chain,
)
if not self.replace:
# if we are not replacing -> list all files in the ADLS path
# and only keep those files which are present in
# ADLS and not in Google Cloud Storage
bucket_name, prefix = _parse_gcs_url(self.dest_gcs)
existing_files = g_hook.list(bucket_name=bucket_name, prefix=prefix)
files = list(set(files) - set(existing_files))
if files:
hook = AzureDataLakeHook(azure_data_lake_conn_id=self.azure_data_lake_conn_id)
for obj in files:
with NamedTemporaryFile(mode='wb', delete=True) as f:
hook.download_file(local_path=f.name, remote_path=obj)
f.flush()
dest_gcs_bucket, dest_gcs_prefix = _parse_gcs_url(self.dest_gcs)
dest_path = os.path.join(dest_gcs_prefix, obj)
self.log.info("Saving file to %s", dest_path)
g_hook.upload(
bucket_name=dest_gcs_bucket, object_name=dest_path, filename=f.name, gzip=self.gzip
)
self.log.info("All done, uploaded %d files to GCS", len(files))
else:
self.log.info("In sync, no files needed to be uploaded to GCS")
return files
