Base operator for SQL to GCS operators.

Module Contents



Copy data from SQL to Google Cloud Storage in JSON or CSV format.

class*, sql: str, bucket: str, filename: str, schema_filename: Optional[str] = None, approx_max_file_size_bytes: int = 1900000000, export_format: str = 'json', field_delimiter: str = ',', null_marker: Optional[str] = None, gzip: bool = False, schema: Optional[Union[str, list]] = None, parameters: Optional[dict] = None, gcp_conn_id: str = 'google_cloud_default', google_cloud_storage_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs)[source]

Bases: airflow.models.BaseOperator

Copy data from SQL to Google Cloud Storage in JSON or CSV format.

  • sql (str) -- The SQL to execute.

  • bucket (str) -- The bucket to upload to.

  • filename (str) -- The filename to use as the object name when uploading to Google Cloud Storage. A {} should be specified in the filename to allow the operator to inject file numbers in cases where the file is split due to size.

  • schema_filename (str) -- If set, the filename to use as the object name when uploading a .json file containing the BigQuery schema fields for the table that was dumped from the database.

  • approx_max_file_size_bytes (long) -- This operator supports the ability to split large table dumps into multiple files (see notes in the filename param docs above). This param allows developers to specify the file size of the splits. Check to see the maximum allowed file size for a single object.

  • export_format (str) -- Desired format of files to be exported.

  • field_delimiter (str) -- The delimiter to be used for CSV files.

  • null_marker (str) -- The null marker to be used for CSV files.

  • gzip (bool) -- Option to compress file for upload (does not apply to schemas).

  • schema (str or list) -- The schema to use, if any. Should be a list of dict or a str. Pass a string if using Jinja template, otherwise, pass a list of dict. Examples could be seen: /schemas#specifying_a_json_schema_file

  • gcp_conn_id (str) -- (Optional) The connection ID used to connect to Google Cloud.

  • google_cloud_storage_conn_id (str) -- (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead.

  • delegate_to (str) -- 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.

  • parameters (dict) -- a parameters dict that is substituted at query runtime.

  • impersonation_chain (Union[str, Sequence[str]]) -- 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).

template_fields :Sequence[str] = ['sql', 'bucket', 'filename', 'schema_filename', 'schema', 'parameters', 'impersonation_chain'][source]
template_ext :Sequence[str] = ['.sql'][source]
ui_color = #a0e08c[source]
execute(self, context: airflow.utils.context.Context)[source]

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

convert_types(self, schema, col_type_dict, row) list[source]

Convert values from DBAPI to output-friendly formats.

abstract query(self)[source]

Execute DBAPI query.

abstract field_to_bigquery(self, field) Dict[str, str][source]

Convert a DBAPI field to BigQuery schema format.

abstract convert_type(self, value, schema_type)[source]

Convert a value from DBAPI to output-friendly formats.

Was this entry helpful?