marcosmarxm commented on a change in pull request #15367:
URL: https://github.com/apache/airflow/pull/15367#discussion_r614317645
##########
File path: airflow/providers/google/cloud/operators/bigquery.py
##########
@@ -2039,6 +2039,149 @@ def execute(self, context) -> None:
)
+class BigQueryPatchTableSchemaOperator(BaseOperator):
+ """
+ Patch BigQuery Table Schema
+ Updates fields on a table schema based on contents of the supplied schema
+ parameter. The supplied schema does not need to be complete, if the field
+ already exists in the schema you only need to supply a schema with the
+ fields you want to patch and the "name" key set on the schema resource.
+
+ .. seealso::
+ For more information on how to use this operator, take a look at the
guide:
+ :ref:`howto/operator:BigQueryPatchTableSchemaOperator`
+
+ :param dataset_id: A dotted
+ ``(<project>.|<project>:)<dataset>`` that indicates which dataset
+ will be updated. (templated)
+ :type dataset_id: str
+ :param schema_fields: a partial schema resource. see
+
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#TableSchema
+
+ **Example**: ::
+
+ schema_fields=[
+ {"name": "emp_name", "description": "Some New Description"},
+ {"name": "salary", "description": "Some New Description"},
+ {"name": "departments", "fields": [
+ {"name": "name", "description": "Some New Description"},
+ {"name": "type", "description": "Some New Description"}
+ ]},
+ ]
+
+ :type schema_fields: dict
+ :param project_id: The name of the project where we want to update the
dataset.
+ Don't need to provide, if projectId in dataset_reference.
+ :type project_id: str
+ :param gcp_conn_id: (Optional) The connection ID used to connect to Google
Cloud.
+ :type gcp_conn_id: str
+ :param bigquery_conn_id: (Deprecated) The connection ID used to connect to
Google Cloud.
+ This parameter has been deprecated. You should pass the gcp_conn_id
parameter instead.
+ :type bigquery_conn_id: str
+ :param delegate_to: The account to impersonate, if any.
+ For this to work, the service account making the request must have
domain-wide
+ delegation enabled.
+ :type delegate_to: str
+ :param location: The location used for the operation.
+ :type location: str
+ :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).
+ :type impersonation_chain: Union[str, Sequence[str]]
+ """
+
+ template_fields = (
+ 'schema_fields',
+ 'dataset_id',
+ 'table_id',
+ 'project_id',
+ 'impersonation_chain',
+ )
+ template_fields_renderers = {"schema_fields": "json"}
+ ui_color = BigQueryUIColors.TABLE.value
+
+ @classmethod
+ def _patch_schema(cls, old_schema, new_schema):
+ # Updates the content of "old_schema" with
Review comment:
```suggestion
def _patch_schema(cls, old_schema: Dict, new_schema: Dict) -> None:
"""
Updates the content of "old_schema" with
the fields from new_schema. Makes changes
in place and hence has no return value.
Works recursively for sub-records.
Start by turning the schema list of fields into
a dict keyed on the field name for both the old
and the new schema.
:param old_schema: Old schema...
:type old_schema: dict
"""
```
This way information about the function itself will be render in Airflow
website and users have more information about it, take a look [in a example
here](
https://airflow.apache.org/docs/apache-airflow-providers-google/stable/_api/airflow/providers/google/cloud/hooks/bigquery/index.html#airflow.providers.google.cloud.hooks.bigquery.BigQueryHook.get_schema)
##########
File path: airflow/providers/google/cloud/operators/bigquery.py
##########
@@ -2039,6 +2039,149 @@ def execute(self, context) -> None:
)
+class BigQueryPatchTableSchemaOperator(BaseOperator):
+ """
+ Patch BigQuery Table Schema
+ Updates fields on a table schema based on contents of the supplied schema
+ parameter. The supplied schema does not need to be complete, if the field
+ already exists in the schema you only need to supply a schema with the
+ fields you want to patch and the "name" key set on the schema resource.
+
+ .. seealso::
+ For more information on how to use this operator, take a look at the
guide:
+ :ref:`howto/operator:BigQueryPatchTableSchemaOperator`
+
+ :param dataset_id: A dotted
+ ``(<project>.|<project>:)<dataset>`` that indicates which dataset
+ will be updated. (templated)
+ :type dataset_id: str
+ :param schema_fields: a partial schema resource. see
+
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#TableSchema
+
+ **Example**: ::
+
+ schema_fields=[
+ {"name": "emp_name", "description": "Some New Description"},
+ {"name": "salary", "description": "Some New Description"},
+ {"name": "departments", "fields": [
+ {"name": "name", "description": "Some New Description"},
+ {"name": "type", "description": "Some New Description"}
+ ]},
+ ]
+
+ :type schema_fields: dict
+ :param project_id: The name of the project where we want to update the
dataset.
+ Don't need to provide, if projectId in dataset_reference.
+ :type project_id: str
+ :param gcp_conn_id: (Optional) The connection ID used to connect to Google
Cloud.
+ :type gcp_conn_id: str
+ :param bigquery_conn_id: (Deprecated) The connection ID used to connect to
Google Cloud.
+ This parameter has been deprecated. You should pass the gcp_conn_id
parameter instead.
+ :type bigquery_conn_id: str
+ :param delegate_to: The account to impersonate, if any.
+ For this to work, the service account making the request must have
domain-wide
+ delegation enabled.
+ :type delegate_to: str
+ :param location: The location used for the operation.
+ :type location: str
+ :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).
+ :type impersonation_chain: Union[str, Sequence[str]]
+ """
+
+ template_fields = (
+ 'schema_fields',
+ 'dataset_id',
+ 'table_id',
+ 'project_id',
+ 'impersonation_chain',
+ )
+ template_fields_renderers = {"schema_fields": "json"}
+ ui_color = BigQueryUIColors.TABLE.value
+
+ @classmethod
+ def _patch_schema(cls, old_schema, new_schema):
+ # Updates the content of "old_schema" with
+ # the fields from new_schema. Makes changes
+ # in place and hence has no return value.
+ # Works recursively for sub-records
+
+ # Start by turning the schema list of fields into
+ # a dict keyed on the field name for both the old
+ # and the new schema
+ new_fields = {field["name"]: field for field in new_schema["fields"]
if "name" in field}
+ old_fields = {field["name"]: field for field in old_schema["fields"]}
+
+ # Iterate over all new fields and update the
+ # old_schema dict
+ for field_key in new_fields.keys():
+ # Check if the field exists in the old_schema, if
+ # so change it
+ if field_key in old_fields:
+ old_field = old_fields[field_key]
+ new_field = new_fields[field_key]
+ # Check if recursion is needed
+ if "fields" in new_field:
+ cls._patch_schema(old_field, new_field)
+ del new_field["fields"]
+
+ # Do the update
+ old_field.update(new_field)
+
+ # Field didn't exist, add it as a new field
+ else:
+ old_schema["fields"].append(new_fields[field_key])
+
+ @apply_defaults
+ def __init__(
+ self,
+ *,
+ dataset_id: Optional[str] = None,
+ schema_fields: List[Dict[str, Any]],
+ table_id: Optional[str] = None,
+ project_id: Optional[str] = None,
+ gcp_conn_id: str = 'google_cloud_default',
+ delegate_to: Optional[str] = None,
+ impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
+ **kwargs,
+ ) -> None:
+ self.schema_fields = schema_fields
+ self.table_id = table_id
+ self.dataset_id = dataset_id
+ self.project_id = project_id
+ self.gcp_conn_id = gcp_conn_id
+ self.delegate_to = delegate_to
+ self.impersonation_chain = impersonation_chain
+ super().__init__(**kwargs)
+
+ def execute(self, context):
+ bq_hook = BigQueryHook(
+ gcp_conn_id=self.gcp_conn_id,
+ delegate_to=self.delegate_to,
+ impersonation_chain=self.impersonation_chain,
+ )
+
+ table_schema = bq_hook.get_schema(
+ dataset_id=self.dataset_id, table_id=self.table_id,
project_id=self.project_id
+ )
+
+ self._patch_schema(old_schema=table_schema, new_schema={"fields":
self.schema_fields})
+
+ return bq_hook.update_table(
+ table_resource={"schema": table_schema},
+ fields=["schema"],
+ dataset_id=self.dataset_id,
+ table_id=self.table_id,
+ project_id=self.project_id,
+ )
Review comment:
BigQueryHook has `patch_table`, `patch_dataset`, `get_schema` methods...
maybe the function `_patch_schema` should belong to the BigqueryHook class.
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