How to write SQL query to calculate instances where a row containing a distinct id occurs 7 days after the fist occurrence if the unique id? - sql

Question

I am looking to return a date, the count of unique_ids first occurrences on that date, the number unique_ids that occurred 7 days after their first occurrence and the percentage of occurrences after 7 days / number of first occurrences.
example data_import table
+---------------------+------------------+
| time | distinct_id |
+---------------------+------------------+
| 2018/10/01 | 1 | first instance of `1`
+---------------------+------------------+
| 2018/10/01 | 2 | also first instance, but does not occur 7 days later
+---------------------+------------------+
| 2018/10/02 | 1 | should be disregarded (not first instance of 1)
+---------------------+------------------+
| 2018/10/02 | 3 | first instance of `3`
+---------------------+------------------+
| 2018/10/08 | 1 | First instance 7 days after first instance of `1`
+---------------------+------------------+
| 2018/10/08 | 1 | Don't count as this is the 2nd instance of `1` on this day
+---------------------+------------------+
| 2018/10/09 | 3 | 7 days after first instance of `3`
+---------------------+------------------+
| 2018/10/09 | 1 | 7 days after non-first instance of `1`
+---------------------+------------------+
And the expected return.
+---------------------+----------------------+------------------------+---------------------------+
| time | num_of_1st_instance | num_occur_7_days_after | percent_used_7_days_after |
+---------------------+----------------------+------------------------+---------------------------+
| 2018/10/01 | 2 | 1 | .50 |
+---------------------+----------------------+------------------------+---------------------------+
| 2018/10/02 | 1 | 1 | 1.0 |
+---------------------+----------------------+------------------------+---------------------------+
| 2018/10/03 | 0 | 0 | 0 |
+---------------------+----------------------+------------------------+---------------------------+
The query I have written is close, but counts occurrences other that the first for a distinct_id.
In my example, this query would include the occurrence of distinct_id 1 on 2018/10/02 and it's occurrence seven days after 2018/10/02 on 2018/10/09. Not wanted as the 2018/10/02 occurrence of distinct_id 1 is not it's first.
SELECT
data_import.time AS date,
count(distinct data_import.distinct_id) AS num_installs_on_install_date,
count(distinct future_activity.distinct_id) AS num_occur_7_days_after,
count(distinct future_activity.distinct_id) / count(distinct data_import.distinct_id)::float AS percent_used_7_days_after
FROM data_import
LEFT JOIN data_import AS future_activity ON
data_import.distinct_id = future_activity.distinct_id
AND
DATE(data_import.time) = DATE(future_activity.time) - INTERVAL '7 days'
AND
data_import.time = ( SELECT
time
FROM
data_import
WHERE
distinct_id = future_activity.distinct_id
ORDER BY
time
limit
1 )
GROUP BY DATE(data_import.time)
I hope that I explained this clearly. Please let me know how I can change my current query or a different approach to the solution.

Answer 1

Hmmm. Does this do what you want?
select di.time, sum( (seqnum = 1)::int) as first_instance,
sum( flag_7day ) as num_after_7_day,
sum( (seqnum = 1)::int) * 1.0 / sum( flag_7day ) as ratio
from (select di.*,
row_number() over (partition by distinct_id order by time) as seqnum,
(case when exists (select 1 from data_import di2 where di2.distinct_id = di.distinct_id and di2.time > di.time + interval '7 day')
then 1 else 0
end) as flag_7day
from data_import di
) di
group by di.time;
This doesn't return days with no first instances. Those days seem a bit awkward with respect to the ratio, so I'm not 100% sure that you really need them. If you do, it is easy enough to include a generate_series() to generate all dates in the range that you want.