BigQuery : is it possible to execute another query inside an UDF?

I have a table that records a row for each unique user per day with some aggregated stats for that user on that day, and I need to produce a report that tells me for each day, the no. of unique users in the last 30 days including that day.


    <li>for Aug 31st, it'll count the unique users from Aug 2nd to Aug 31st</li> <li>for Aug 30th, it'll count the unique users from Aug 1st to Aug 30th</li> <li>and so on...</li> </ul>

    I've looked at some related questions but they aren't quite what I need - if a user logs in on multiple days in the last 30 days he should be counted only once, so I can't just sum the DAU count for the last 30 days.

    Bigquery SQL for sliding window aggregate

    BigQuery SQL for 28-day sliding window aggregate (without writing 28 lines of SQL)

    So far, my ideas are to either:

      <li>write a simple script that'll execute a separate BigQuery for each of the relevant days</li> <li>write a BigQuery UDF that'll execute basically the same query for each day selected from another query</li> </ul>

      but I've not found any examples on how to execute another BigQuery query inside an UDF, or if it's possible at all.


      I need to produce a report that tells me for each day, the no. of unique users in the last 30 days including that day.

      Below should do this

      SELECT calendar_day, EXACT_COUNT_DISTINCT(userID) AS unique_users FROM ( SELECT calendar_day, userID FROM YourTable CROSS JOIN ( SELECT DATE(DATE_ADD('2016-08-08', pos - 1, "DAY")) AS calendar_day FROM ( SELECT ROW_NUMBER() OVER() AS pos, * FROM (FLATTEN(( SELECT SPLIT(RPAD('', 1 + DATEDIFF('2016-09-08', '2016-08-08'), '.'),'') AS h FROM (SELECT NULL)),h ))) ) AS calendar WHERE DATEDIFF(calendar_day, dt) BETWEEN 0 AND 29 ) GROUP BY calendar_day ORDER BY calendar_day DESC

      It assumes YourTable has userID and dt fields (like below for example)

      dt userID 2016-09-08 1 2016-09-08 2 ...

      And you can control: - reporting dates range by changing respectively 2016-08-08 and 2016-09-08 - aggregation size by changing 29 in BETWEEN 0 AND 29


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