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Load data with Storage to Tables
Learn how to transfer data from files to database tables using the Storage to Tables operation.
A Storage to Tables (STT) data pipeline operation allows you to load data files from a Google Cloud Storage (GCS) bucket into one or several BigQuery databases.
Note that the uniqueness of the configuration is checked against the GCS bucket name AND directory combination. This means that you can have only one configuration per bucket/directory combination, as any new configuration will overwrite the previous one.
- CSV and any delimited flat files
- New line delimited JSON files
- These two file types can be compressed using gzip
- Google BigQuery
Every time a new file matching the specified rule appears in a given directory of a Google Cloud Storage bucket:
- it will be removed from the source directory,
- if options have been set accordingly, the file will be copied to an archive directory located in the same storage, inside a folder named with the date contained in the filename,
- the file data will be loaded into a BigQuery table matching its filename template for each database specified.
Automatic metadata feature will add specific columns during the ingestion process related to the inpput source.
The added columns are:
tlr_ingestion_timestamp_utc (TIMESTAMP)
tlr_input_file_source_type (STRING)
tlr_input_file_name (STRING)
tlr_input_file_full_resource_name (STRING)
- 1.
- 2.Create a working folder as you want, and create a JSON file for your data operation inside.
- 3.
- 4.
- 5.Access your working folder by running the following command:cd "[path to your working folder]"
- 6.To deploy the data operation, run the following command:tailer deploy your-file.json
- 7.
- 8.Access your output table(s), and archive folder, if any, to check the result of the data operation.