Google BigQuery: Rolling Count Distinct - sql

Question

I have a table with is simply a list of dates and user IDs (not aggregated).
We define a metric called active users for a given date by counting the distinct number of IDs that appear in the previous 45 days.
I am trying to run a query in BigQuery that, for each day, returns the day plus the number of active users for that day (count distinct user from 45 days ago until today).
I have experimented with window functions, but can't figure out how to define a range based on the date values in a column. Instead, I believe the following query would work in a database like MySQL, but does not in BigQuery.
SELECT
day,
(SELECT
COUNT(DISTINCT visid)
FROM daily_users
WHERE day BETWEEN DATE_ADD(t.day, -45, "DAY") AND t.day
) AS active_users
FROM daily_users AS t
GROUP BY 1
This doesn't work in BigQuery: "Subselect not allowed in SELECT clause."
How to do this in BigQuery?

Answer 1

BigQuery documentation claims that count(distinct) works as a window function. However, that doesn't help you, because you are not looking for a traditional window frame.
One method would adds a record for each date after a visit:
select theday, count(distinct visid)
from (select date_add(u.day, n.n, "day") as theday, u.visid
from daily_users u cross join
(select 1 as n union all select 2 union all . . .
select 45
) n
) u
group by theday;
Note: there may be simpler ways to generate a series of 45 integers in BigQuery.

Answer 2

Below should work with BigQuery
#legacySQL
SELECT day, active_users FROM (
SELECT
day,
COUNT(DISTINCT id)
OVER (ORDER BY ts RANGE BETWEEN 45*24*3600 PRECEDING AND CURRENT ROW) AS active_users
FROM (
SELECT day, id, TIMESTAMP_TO_SEC(TIMESTAMP(day)) AS ts
FROM daily_users
)
) GROUP BY 1, 2 ORDER BY 1
Above assumes that day field is represented as '2016-01-10' format.
If it is not a case , you should adjust TIMESTAMP_TO_SEC(TIMESTAMP(day)) in most inner select
Also please take a look at COUNT(DISTINC) specifics in BigQuery
Update for BigQuery Standard SQL
#standardSQL
SELECT
day,
(SELECT COUNT(DISTINCT id) FROM UNNEST(active_users) id) AS active_users
FROM (
SELECT
day,
ARRAY_AGG(id)
OVER (ORDER BY ts RANGE BETWEEN 3888000 PRECEDING AND CURRENT ROW) AS active_users
FROM (
SELECT day, id, UNIX_DATE(PARSE_DATE('%Y-%m-%d', day)) * 24 * 3600 AS ts
FROM daily_users
)
)
GROUP BY 1, 2
ORDER BY 1
You can test / play with it using below dummy sample
#standardSQL
WITH daily_users AS (
SELECT 1 AS id, '2016-01-10' AS day UNION ALL
SELECT 2 AS id, '2016-01-10' AS day UNION ALL
SELECT 1 AS id, '2016-01-11' AS day UNION ALL
SELECT 3 AS id, '2016-01-11' AS day UNION ALL
SELECT 1 AS id, '2016-01-12' AS day UNION ALL
SELECT 1 AS id, '2016-01-12' AS day UNION ALL
SELECT 1 AS id, '2016-01-12' AS day UNION ALL
SELECT 1 AS id, '2016-01-13' AS day
)
SELECT
day,
(SELECT COUNT(DISTINCT id) FROM UNNEST(active_users) id) AS active_users
FROM (
SELECT
day,
ARRAY_AGG(id)
OVER (ORDER BY ts RANGE BETWEEN 86400 PRECEDING AND CURRENT ROW) AS active_users
FROM (
SELECT day, id, UNIX_DATE(PARSE_DATE('%Y-%m-%d', day)) * 24 * 3600 AS ts
FROM daily_users
)
)
GROUP BY 1, 2
ORDER BY 1