activity_occurrence is leaving out activity in partition, why?

[jbergenblom]

Just started diving in to the Activity Schema pattern and am simultaneously using this dbt-activity-schema and the ActivitySchema repo as reference.

But when trying out the dbt macros I couldn't get anything useful out using the window aggregates (activity_occurrence and activity_repeated_at). Or at least not assuming that they should reflect the ordinal ordering of events for a specific customer AND activity.

Just take the pseudo-code for these metrics from the ActivitySchema implementation specification: occurrence-columns calculation. Here the field activity is used in the partitioning.

row_number() over (partition by coalesce (activity, customer, anonymous_customer_id) order by ts asc) as activity_occurrence,
lead(ts) over (partition by coalesce (activity, customer, anonymous_customer_id) order by ts asc) as activity_repeated_at

But in this repo's implementation there is only partitioning done using customer:

# macros/activity_occurrence.sql
...
partition by coalesce (
    {{ safe_cast("customer", type_string()) }},
    {{ safe_cast("anonymous_customer_id", type_string()) }}
) order by ts asc ) as activity_occurrence,
...

So they contradict, and in my head I can't see the value in just having an ordinal numbering of all events for a customer. Is this diff something you did intentionally?