Source code for airflow.providers.amazon.aws.transfers.s3_to_sql
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from __future__ import annotations
from tempfile import NamedTemporaryFile
from typing import TYPE_CHECKING, Callable, Iterable, Sequence
from airflow.compat.functools import cached_property
from airflow.exceptions import AirflowException
from airflow.hooks.base import BaseHook
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.s3 import S3Hook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class S3ToSqlOperator(BaseOperator):
"""
Loads Data from S3 into a SQL Database.
You need to provide a parser function that takes a filename as an input
and returns an iterable of rows
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:S3ToSqlOperator`
:param schema: reference to a specific schema in SQL database
:param table: reference to a specific table in SQL database
:param s3_bucket: reference to a specific S3 bucket
:param s3_key: reference to a specific S3 key
:param sql_conn_id: reference to a specific SQL database. Must be of type DBApiHook
:param aws_conn_id: reference to a specific S3 / AWS connection
:param column_list: list of column names to use in the insert SQL.
:param commit_every: The maximum number of rows to insert in one
transaction. Set to `0` to insert all rows in one transaction.
:param parser: parser function that takes a filepath as input and returns an iterable.
e.g. to use a CSV parser that yields rows line-by-line, pass the following
function:
def parse_csv(filepath):
import csv
with open(filepath, newline="") as file:
yield from csv.reader(file)
"""
[docs] template_fields: Sequence[str] = (
"s3_bucket",
"s3_key",
"schema",
"table",
"column_list",
"sql_conn_id",
)
[docs] template_ext: Sequence[str] = ()
def __init__(
self,
*,
s3_key: str,
s3_bucket: str,
table: str,
parser: Callable[[str], Iterable[Iterable]],
column_list: list[str] | None = None,
commit_every: int = 1000,
schema: str | None = None,
sql_conn_id: str = "sql_default",
aws_conn_id: str = "aws_default",
**kwargs,
) -> None:
super().__init__(**kwargs)
self.s3_bucket = s3_bucket
self.s3_key = s3_key
self.table = table
self.schema = schema
self.aws_conn_id = aws_conn_id
self.sql_conn_id = sql_conn_id
self.column_list = column_list
self.commit_every = commit_every
self.parser = parser
[docs] def execute(self, context: Context) -> None:
self.log.info("Loading %s to SQL table %s...", self.s3_key, self.table)
s3_hook = S3Hook(aws_conn_id=self.aws_conn_id)
s3_obj = s3_hook.get_key(key=self.s3_key, bucket_name=self.s3_bucket)
with NamedTemporaryFile() as local_tempfile:
s3_obj.download_fileobj(local_tempfile)
local_tempfile.flush()
local_tempfile.seek(0)
self.db_hook.insert_rows(
table=self.table,
schema=self.schema,
target_fields=self.column_list,
rows=self.parser(local_tempfile.name),
commit_every=self.commit_every,
)
@cached_property
[docs] def db_hook(self):
self.log.debug("Get connection for %s", self.sql_conn_id)
hook = BaseHook.get_hook(self.sql_conn_id)
if not callable(getattr(hook, "insert_rows", None)):
raise AirflowException(
"This hook is not supported. The hook class must have an `insert_rows` method."
)
return hook
