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For more information about the Scuba query language, see:
BQL syntax and usage for a description of BQL building blocks and examples of common Scuba queries in BQL.
BQL vs. SQL comparison for similarities and differences between BQL and SQL concepts.
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select count(*) from my_table between 2019-01-01 and 2019-01-15
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Note that data outside of the time span can be used in a query when a query or properties used in the query have an offset or trailing window that go beyond the time span.
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with last_24hr_activity as Actor<user>(
count(*) over 24 hours
),
num_flow_events as Flow<user_session>(
count(*)
)
select avg(price), avg(last_24hr_activity), avg(num_flow_events) from my_table
|
In this query, scopes of the aggregations are event, actor and flow, respectively, assuming that price is an event property.
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with user_play_time as Actor<user>(
sum(play_time)
)
select avg(user_play_time) group by music_service
|
If a user used two different music services, A and B, for 10 hours and 50 hours, respectively, the user’s total play time (sum(play_time)) is divided into two (10 and 50) and accounts for the averages of respective groups.
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