Database Reference
In-Depth Information
things like financial information and GitHub commit history. Researchers
can mine these sources or combine the data with their own for new insight.
Any dataset can be shared with any user just by making an API call or using
the UI to edit the access control settings. If you want someone in a different
continent to run queries against your data, you don't have to ship it to them
or let them log into your servers. You just share the dataset with them,
and they can run queries against the data directly. You have the option of
requiring them to pay the BigQuery bill for any queries they run (just add
them to the Access Control List) or allowing them to run queries that are
billed to you (add them to your project). These concepts will be clearer in
later chapters, but we bring them up now to whet your appetite.
Web UI
BigQuery provides a web UI at
https://bigquery.cloud.google.com
.
This interface allows you to
perform most of the operations in the API: Browse available tables, read
their schema and data, share datasets with other users, load data, and export
it to Google Cloud Storage. It also allows you to create and edit queries.
Although it may seem like an afterthought to have a web UI for a database,
it means that anyone can use it from any web browser—there is no need
to download any client side software or install anything. Many users will
perform all the tasks they need directly from the web interface.
Figure 2.2
shows the BigQuery web UI.
