GoogleAnalyticsModifyFileHeadersDataImportOperator
GoogleGA has a very particular naming convention for Data Import. Ability to prefix “ga:” to all column headers and also a dict to rename columns to match the custom dimension ID in GA i.e clientId : dimensionX.
Access Instructions
Install the Google provider package into your Airflow environment.
Import the module into your DAG file and instantiate it with your desired params.
Parameters
storage_bucketThe Google cloud storage bucket where the file is stored.
storage_name_objectThe name of the object in the desired Google cloud storage bucket. (templated) If the destination points to an existing folder, the file will be taken from the specified folder.
gcp_conn_idThe connection ID to use when fetching connection info.
custom_dimension_header_mappingDictionary to handle when uploading custom dimensions which have generic IDs ie. ‘dimensionX’ which are set by GA. Dictionary maps the current CSV header to GA ID which will be the new header for the CSV to upload to GA eg clientId : dimension1.
delegate_toThe 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.
impersonation_chainOptional 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).
Documentation
GA has a very particular naming convention for Data Import. Ability to prefix “ga:” to all column headers and also a dict to rename columns to match the custom dimension ID in GA i.e clientId : dimensionX.