# Glean Data

The following describes in detail how we structure Glean data in BigQuery. For information on the actual software which does this, see the Generated Schemas reference. This document intended as a reference, if you want a tutorial on how best to access Glean Data in BigQuery, see Accessing Glean Data.

## Tables

Each ping type is recorded in its own table, and these tables are named using {application_id}.{ping_type}. For example, for Fenix, the application id is org.mozilla.fenix, so its metrics pings are available in the table org_mozilla_fenix.metrics.

## Columns

Fields are nested inside BigQuery STRUCTs to organize them into groups, and we can use dot notation to specify individual subfields in a query. For example, columns containing Glean's built-in client information are in the client_info struct, so accessing its columns involves using a client_info. prefix.

The top-level groups are:

### Ping and Client Info sections

Core attributes sent with every ping are mapped to the client_info and ping_info sections. For example, the client id is mapped to a column called client_info.client_id.

### The metrics group

Custom metrics in the metrics section have two additional levels of indirection in their column name: they are organized by the metric type, and then by their category: metrics.{metric_type}.{category}_{name}.

For example, suppose you had the following boolean metric defined in a metrics.yaml file (abridged for clarity):

browser:
is_default:
type: boolean
description: >
Is this application the default browser?
send_in_pings:
- metrics


It would be available in the column metrics.boolean.browser_is_default.

### The events group

Events are stored as a set of records in a single column called "events": there might be many events sent as part of a single ping. Each record has the following fields which allow you to filter for the specific metrics of interest:

• category (maps to the metric category)
• name (maps to the metric name)

For example, suppose you had the following event metric defined in a metrics.yaml file (again, abridged for clarity):

engine_tab:
foreground_metrics:
type: event
description: |
Event collecting data about the state of tabs when the app comes back to
the foreground.
extra_keys:
extra_keys:
background_active_tabs:
description: |
Number of active tabs (with an engine session assigned) when the app
went to the background.
...


In this case the event's category would be engine_tab and its name would be foreground_metrics.

You can use the record's timestamp and extra fields to get the event's timestamp and specifics related to the event. For a complete example, see "event metrics" under Accessing Glean Data.