This article describes the various BigQuery tables Mozilla uses to store Activity Stream data, along with some examples of how to access them.
- What is Activity Stream?
- Activity Stream Pings
- Accessing Activity Stream Data
- Gotchas and Caveats
Activity Stream is the Firefox module which manages the in product content pages for Firefox:
What's new panel
The Activity Stream team has implemented data collection in and around these pages. This data has some overlap with the standard Firefox Telemetry system, however it is a custom system, designed and maintained by that team.
For specific questions about this data, reach out to the
#fx-messaging-system Slack channel directly.
Activity Stream pings are stored in BigQuery (like other Firefox Telemetry). There are two datasets:
activity_stream dataset contains the following tables:
eventsstores user interactions with the
sessionsstores sessions of
impression_statsstores impression/click/block events for the Pocket recommendations on the
spoc_fillsstores "Pocket Sponsored" recommendation related pings
messaging_system dataset contains the following tables:
cfrstores metrics on user interactions with the CFR (Contextual Feature Recommendation) system
momentsstores "Moments Pages" related pings
onboardingstores metrics on user interactions with onboarding features
snippetsstores impression/click/dismissal metrics for Firefox Snippets
whats_new_panelstores "What's New Panel" related pings
undesired_eventsstores system health related events
Since this data collection isn't collected or maintained through our standard Telemetry API, there are a number of "gotchas" to keep in mind when working on this data:
Ping send conditions: Activity Stream pings have different send conditions, both from Telemetry pings as well as from each other. For example, AS Session Pings get sent by profiles that entered an Activity Stream session, at the end of that session, regardless of how long that session is. Compare this to
mainpings, which get sent by all Telemetry enabled profiles upon subsession end (browser shutdown, environment change, or local midnight cutoff).
Due to these inconsistencies, using data from different sources can be tricky. For example, if we wanted to know how much of DAU (from
mainpings) had a custom
about:homepage (available in AS Health Pings), joining on
client_idand a date field would only provide information on profiles that started the session on that same day (active profiles on multi-day sessions would be excluded).
Population covered: In addition to the usual considerations when looking at a measurement (in what version of Firefox did this measurement start getting collected? In what channels is it enabled in? etc.), when working with this data, there are additional Activity Stream specific conditions to consider when deciding "who is eligible to send this ping?"
For example, Pocket recommendations are only enabled in the US, CA, UK, and DE countries, for profiles that are on en-US, en-CA, en-GB, and de locales. Furthermore, users can set their
about:newtabpage to non-Activity Stream pages. This information can be important when deciding denominators for certain metrics.
Different ping types in the same table: The tables in the
activity_streamnamespace can contain multiple types of pings. For example, the
eventstable contains both AS Page Takeover pings as well as AS User Event pings.
Null handling: Some fields in the Activity Stream data encode nulls with a
'N/A'string or a
Changes in ping behaviors: These pings continue to undergo development and the behavior as well as possible values for a given ping seem to change over time. For example, older versions of the event pings for clicking on a Topsite do not seem to report
icon_types, while newer versions do. Caution is advised.
Pocket data: Data related to Pocket interaction and usage in the
about:newtabpages get sent to Pocket via this data collection and pipeline. However, due to privacy reasons, the
client_idis omitted in the ping whenever the Pocket recommendation identifiers are included, instead it reports with another user unique identifier
impression_id. Though all the Pocket user interactions, such as clicks, dismisses, and save to pocket are still reported as the regular events with the
client_idas long as they don't contain the Pocket recommendation identifiers.
Note: only includes
client_ids that completed an Activity Stream session that day.
SELECT client_id, DATE(submission_timestamp) AS date, count(DISTINCT session_id) as num_sessions FROM `moz-fx-data-shared-prod.activity_stream.sessions` WHERE DATE(submission_timestamp) = '20200601' GROUP BY 1
SELECT client_id, DATE(submission_timestamp) AS date, session_id, page, source, action_position, experiments FROM `moz-fx-data-shared-prod.activity_stream.events` WHERE source in ('TOP_SITES', 'HIGHLIGHTS') AND event = 'CLICK' DATE(submission_timestamp) = '20200601'
Note: Which snippet message a record corresponds to can be identified by the
message_id (check with Marketing for snippet recipes published).
SELECT client_id, DATE(submission_timestamp) AS date, event, message_id, event_context, experiments FROM `moz-fx-data-shared-prod.messaging_system.snippets` WHERE DATE(submission_timestamp) = '20200601'