Source code for airflow.providers.google.cloud.transfers.bigquery_to_sql

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"""Base operator for BigQuery to SQL operators."""
from __future__ import annotations

import abc
from typing import TYPE_CHECKING, Sequence

from airflow.models import BaseOperator
from airflow.providers.common.sql.hooks.sql import DbApiHook
from airflow.providers.google.cloud.hooks.bigquery import BigQueryHook
from airflow.providers.google.cloud.utils.bigquery_get_data import bigquery_get_data

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class BigQueryToSqlBaseOperator(BaseOperator): """ Fetch data from a BigQuery table (alternatively fetch selected columns) and insert it into an SQL table. This is a BaseOperator; an abstract class. Refer to children classes which are related to specific SQL databases (MySQL, MsSQL, Postgres...). .. note:: If you pass fields to ``selected_fields`` which are in different order than the order of columns already in BQ table, the data will still be in the order of BQ table. For example if the BQ table has 3 columns as ``[A,B,C]`` and you pass 'B,A' in the ``selected_fields`` the data would still be of the form ``'A,B'`` and passed through this form to the SQL database. :param dataset_table: A dotted ``<dataset>.<table>``: the big query table of origin :param target_table_name: target SQL table :param selected_fields: List of fields to return (comma-separated). If unspecified, all fields are returned. :param gcp_conn_id: reference to a specific Google Cloud hook. :param database: name of database which overwrite defined one in connection :param replace: Whether to replace instead of insert :param batch_size: The number of rows to take in each batch :param location: The location used for the operation. :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: Sequence[str] = ( "target_table_name", "impersonation_chain", )
def __init__( self, *, dataset_table: str, target_table_name: str | None, selected_fields: list[str] | str | None = None, gcp_conn_id: str = "google_cloud_default", database: str | None = None, replace: bool = False, batch_size: int = 1000, location: str | None = None, impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.selected_fields = selected_fields self.gcp_conn_id = gcp_conn_id self.database = database self.target_table_name = target_table_name self.replace = replace self.batch_size = batch_size self.location = location self.impersonation_chain = impersonation_chain try: self.dataset_id, self.table_id = dataset_table.split(".") except ValueError: raise ValueError(f"Could not parse {dataset_table} as <dataset>.<table>") from None @abc.abstractmethod
[docs] def get_sql_hook(self) -> DbApiHook: """Return a concrete SQL Hook (a PostgresHook for instance)."""
[docs] def execute(self, context: Context) -> None: big_query_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, location=self.location, impersonation_chain=self.impersonation_chain, ) self.persist_links(context) sql_hook = self.get_sql_hook() for rows in bigquery_get_data( self.log, self.dataset_id, self.table_id, big_query_hook, self.batch_size, self.selected_fields, ): sql_hook.insert_rows( table=self.target_table_name, rows=rows, target_fields=self.selected_fields, replace=self.replace, )

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