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The Average Daily Load

hardSQLSubqueriesArithmetic

Kindled is sizing the infrastructure for next season and needs a baseline: on a day when the site is actually in use, how many tracked actions does it handle? Days on which nothing was recorded must not be part of the average — they would drag the figure toward zero and make the capacity plan too small. The denominator is therefore how many separate days appear in the table at all, not how many days the month has.

events — one row per tracked action. user_id points at a row in users. event_type is one of signup, view_product, add_to_cart and purchase. event_date is the day the action happened. Nothing guarantees a person produces all four kinds, or any particular number of rows.

id user_id event_type event_date
1 1 signup 2023-05-01
2 1 view_product 2023-05-01
3 1 add_to_cart 2023-05-02
4 1 purchase 2023-05-03
5 2 signup 2023-05-02
6 2 view_product 2023-05-02
7 3 signup 2023-05-03
8 3 view_product 2023-05-03
9 3 add_to_cart 2023-05-04
10 4 signup 2023-05-04
11 4 view_product 2023-05-05
12 4 add_to_cart 2023-05-05
13 4 purchase 2023-05-06
14 5 signup 2023-05-05
15 6 signup 2023-05-06
16 6 view_product 2023-05-06
17 7 signup 2023-05-07
18 7 view_product 2023-05-07
19 7 add_to_cart 2023-05-08
20 7 purchase 2023-05-09
21 8 signup 2023-05-08

The table already exists in the database — there is nothing to create or load.

Task: Write a query that returns one row and one column, avg_daily_events, holding the total number of tracked actions divided by the number of separate days on which anything was recorded, rounded to 2 decimal places.

Example output — the shape, on an invented figure. A tracker running at five and three quarter actions a day reads:

avg_daily_events
5.75

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