Google BigQuery: Schedule, Trigger, Monitor, and Orchestrate Operations
Google BigQuery is a serverless, highly scalable data warehouse designed to make SQL-based queries on large datasets fast and easy. It is part of the Google Cloud Platform and enables users to perform real-time data analysis with its powerful processing capabilities and simple SQL interface..
This Universal Task allows Stonebranch users to schedule, trigger, monitor, and orchestrate the Google BigQuery process directly from the Universal Controller.
-
This task uses Python modules google-cloud-big query and google-auth to make REST-API calls to Google BigQuery
-
This task will use the GCP Project ID, BigQuery SQL or Schema, Dataset ID, Job ID, Location, Table ID, Cloud Storage URI, and Source File Format as parameters of BigQuery function, and GCP KeyFile (API KEY) of Service account for authenticating the REST-API calls to Google BigQuery.
Key Features
This Universal task provides the following main features:
-
BigQuery SQL
-
List dataset
-
List tables in the dataset
-
View job information
-
Create a dataset
-
Load local file to a table
-
Load cloud storage data to a table
-
Export table data
What's New (v1.1.4)
This new release involves a Bug Fix
-
Fix: Usage for the Double quotes for the _scriptPath
| Product Component: | Universal Agent, Universal Controller |
|---|---|
| Version: | 1.1.4 |
| Vendor: | |
| Type: | Free |
| Compatibility : | UC/UA 7.0 |