Source code for airflow.providers.amazon.aws.transfers.glacier_to_gcs
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from __future__ import annotations
import tempfile
from typing import TYPE_CHECKING, Sequence
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.glacier import GlacierHook
from airflow.providers.google.cloud.hooks.gcs import GCSHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class GlacierToGCSOperator(BaseOperator):
"""
Transfers data from Amazon Glacier to Google Cloud Storage
.. note::
Please be warn that GlacierToGCSOperator may depends on memory usage.
Transferring big files may not working well.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:GlacierToGCSOperator`
:param aws_conn_id: The reference to the AWS connection details
:param gcp_conn_id: The reference to the GCP connection details
:param vault_name: the Glacier vault on which job is executed
:param bucket_name: the Google Cloud Storage bucket where the data will be transferred
:param object_name: the name of the object to check in the Google cloud
storage bucket.
:param gzip: option to compress local file or file data for upload
:param chunk_size: size of chunk in bytes the that will downloaded from Glacier vault
:param delegate_to: The 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).
"""
[docs] template_fields: Sequence[str] = ("vault_name", "bucket_name", "object_name")
def __init__(
self,
*,
aws_conn_id: str = "aws_default",
gcp_conn_id: str = "google_cloud_default",
vault_name: str,
bucket_name: str,
object_name: str,
gzip: bool,
chunk_size: int = 1024,
delegate_to: str | None = None,
google_impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.aws_conn_id = aws_conn_id
self.gcp_conn_id = gcp_conn_id
self.vault_name = vault_name
self.bucket_name = bucket_name
self.object_name = object_name
self.gzip = gzip
self.chunk_size = chunk_size
self.delegate_to = delegate_to
self.impersonation_chain = google_impersonation_chain
[docs] def execute(self, context: Context) -> str:
glacier_hook = GlacierHook(aws_conn_id=self.aws_conn_id)
gcs_hook = GCSHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
impersonation_chain=self.impersonation_chain,
)
job_id = glacier_hook.retrieve_inventory(vault_name=self.vault_name)
with tempfile.NamedTemporaryFile() as temp_file:
glacier_data = glacier_hook.retrieve_inventory_results(
vault_name=self.vault_name, job_id=job_id["jobId"]
)
# Read the file content in chunks using StreamingBody
# https://botocore.amazonaws.com/v1/documentation/api/latest/reference/response.html
stream = glacier_data["body"]
for chunk in stream.iter_chunk(chunk_size=self.chunk_size):
temp_file.write(chunk)
temp_file.flush()
gcs_hook.upload(
bucket_name=self.bucket_name,
object_name=self.object_name,
filename=temp_file.name,
gzip=self.gzip,
)
return f"gs://{self.bucket_name}/{self.object_name}"