Postgres create view with column values based on another table?-CodePudding

I'm implementing a view to store leaderboard data of the top 10 users that is computed using an expensive COUNT(*). I'm planning on the view to look something like this:

id SERIAL PRIMARY KEY
user_id TEXT
type TEXT
rank INTEGER
count INTEGER

-- adding an index to user_id
-- adding a two-column unique index to user_id and type

I'm having trouble with seeing how this view should be created to properly account for the rank and type. Essentially, I have a big table (~30 million rows) like this:

 ---- --------- --------- ---------------------------- 
| id | user_id |  type   |         created_at         |
 ---- --------- --------- ---------------------------- 
|  1 |       1 | Diamond | 2021-05-11 17:35:18.399517 |
|  2 |       1 | Diamond | 2021-05-12 17:35:17.399517 |
|  3 |       1 | Diamond | 2021-05-12 17:35:18.399517 |
|  4 |       2 | Diamond | 2021-05-13 17:35:18.399517 |
|  5 |       1 | Clay    | 2021-05-14 17:35:18.399517 |
|  6 |       1 | Clay    | 2021-05-15 17:35:18.399517 |
 ---- --------- --------- ----------------------------

With the table above, I'm trying to achieve something like this:

 ---- --------- --------- ------ ------- 
| id | user_id |  type   | rank | count |
 ---- --------- --------- ------ ------- 
|  1 |       1 | Diamond |    1 |     3 |
|  2 |       2 | Diamond |    2 |     1 |
|  3 |       1 | Clay    |    1 |     2 |
|  4 |       1 | Weekly  |    1 |     5 | -- 3 diamonds   2 clay obtained between Mon-Sun
|  5 |       2 | Weekly  |    2 |     1 |
 ---- --------- --------- ------ -------

By Weekly I am counting the time from the last Sunday to the upcoming Sunday.

Is this doable using only SQL, or is some kind of script needed? If doable, how would this be done? It's worth mentioning that there are thousands of different types, so not having to manually specify type would be preferred.

If there's anything unclear, please let me know and I'll do my best to clarify. Thanks!

CodePudding user response：

I think this is what you were talking about, right?

WITH scores_plus_weekly AS ((
        SELECT id, user_id, 'Weekly' AS type, created_at
        FROM scores
        WHERE created_at BETWEEN '2021-05-10' AND '2021-05-17'
    )
    UNION (
        SELECT * FROM scores
    ))
SELECT
    row_number() OVER (ORDER BY CASE "type" WHEN 'Diamond' THEN 0 WHEN 'Clay' THEN 1 ELSE 2 END, count(*) DESC) as "id",
    user_id,
    "type",
    row_number() OVER (PARTITION BY count(*) DESC) as "rank",
    count(*)
FROM scores_plus_weekly
GROUP BY user_id, "type"
ORDER BY "id";

I'm sure this is not the only way, but I thought the result wasn't too complex. This query first combines the original database with all scores from this week. For the sake of consistency I picked a date range that matches your entire example set. It then groups by user_id and type to get the counts for each combination. The row_numbers will give you the overall rank and the rank per type. A big part of this query consists of sorting by type, so if you're joining another table that contains the order or priority of the types, the CASE can probably be simplified.

Then, lastly, this entire query can be caught in a view using the CREATE VIEW score_ranks AS , followed by your query.

CodePudding user response：

The "weekly" rows are produced in a different way compared to the "user" rows (I called them two different "categories"). To get the result you want you can combine two queries using UNION ALL.

For example:

select 'u' as category, user_id, type,
  rank() over(partition by type order by count(*) desc) as rk,
  count(*) as cnt
from scores
group by user_id, type
union all
select 'w', user_id, 'Weekly',
  rank() over(order by count(*) desc),
  count(*) as cnt
from scores
group by user_id
order by category, type desc, rk

Result:

 category  user_id  type     rk  cnt 
 --------- -------- -------- --- --- 
 u         1        Diamond  1   3   
 u         2        Diamond  2   1   
 u         1        Clay     1   2   
 w         1        Weekly   1   5   
 w         2        Weekly   2   1

See running example at DB Fiddle.

Note: For the sake of simplicity I left the filtering by timestamp out of the query. If you really needed to include only the rows of the last 7 days (or other period of time), it would be a matter of adding a WHERE clause in both subqueries.