INSERT INTO two columns from a SELECT query - sql

Question

I have a table called VIEWS with Id, Day, Month, name of video, name of browser... but I'm interested only in Id, Day and Month.
The ID can be duplicate because the user (ID) can watch a video multiple days in multiple months.
This is the query for the minimum date and the maximum date.
SELECT ID, CONCAT(MIN(DAY), '/', MIN(MONTH)) AS MIN_DATE,
CONCAT(MAX(DAY), '/', MAX(MONTH)) AS MAX_DATE,
FROM Views
GROUP BY ID
I want to insert this select with two columns(MIN_DATE and MAX_DATE) to two new columns with insert into.
How can be the insert into query?

Answer 1

To do what you are trying to do (there are some issues with your solution, please read my comments below), first you need to add the new columns to the table.
ALTER TABLE Views ADD MIN_DATE VARCHAR(10)
ALTER TABLE Views ADD MAX_DATE VARCHAR(10)
Then you need to UPDATE your new columns (not INSERT, because you don't want new rows). Determine the min/max for each ID, then join the result back to the table to be able to update each row. You can't update directly from a GROUP BY as rows are grouped and lose their original row.
;WITH MinMax
(
SELECT
ID,
CONCAT(MIN(V.DAY), '/', MIN(V.MONTH)) AS MIN_DATE,
CONCAT(MAX(V.DAY), '/', MAX(V.MONTH)) AS MAX_DATE
FROM
Views AS V
GROUP BY
ID
)
UPDATE V SET
MIN_DATE = M.MIN_DATE,
MAX_DATE = M.MAX_DATE
FROM
MinMax AS M
INNER JOIN Views AS V ON M.ID = V.ID
The problems that I see with this design are:
Storing aggregated columns: you usually want to do this only for performance issues (which I believe is not the case here), as querying the aggregated (grouped) rows is faster due to being less rows to read. The problem is that you will have to update the grouped values each time one of the original rows is updated, which as extra processing time. Another option would be periodically updating the aggregated values, but you will have to accept that for a period of time the grouped values are not really representing the tracking table.
Keeping aggregated columns on the same table as the data they are aggregating: this is normalization problem. Updating or inserting a row will trigger updating all rows with the same ID as the min/max values might have changed. Also the min/max values will always be repeated on all rows that belong to the same ID, which is extra space that you are wasting. If you had to save aggregated data, you need to save it on a different table, which causes the problems I listed on the previous point.
Using text data type to store dates: you always want to work dates with a proper DATETIME data type. This will not only enable to use date functions like DATEADD or DATEDIFF, but also save space (varchars that store dates need more bytes that DATETIME). I don't see the year part on your query, it should be considered to compute a min/max (this might depend what you are storing on this table).
Computing the min/max incorrectly: If you have the following rows:
ID DAY MONTH
1 5 1
1 3 2
The current result of your query would be 3/1 as MIN_DATE and 5/2 as MAX_DATE, which I believe is not what you are trying to find. The lowest here should be the 5th of January and the highest the 3rd of February. This is a consequence of storing date parts as independent values and not the whole date as a DATETIME.
What you usually want to do for this scenario is to group directly on the query that needs the data grouped, so you will do the GROUP BY on the SELECT that needs the min/max. Having an index by ID would make the grouping very fast. Thus, you save the storage space you would use to keep the aggregated values and also the result is always the real grouped result at the time that you are querying.
Would be something like the following:
;WITH MinMax
(
SELECT
ID,
CONCAT(MIN(V.DAY), '/', MIN(V.MONTH)) AS MIN_DATE, -- Date problem (varchar + min/max computed seperately)
CONCAT(MAX(V.DAY), '/', MAX(V.MONTH)) AS MAX_DATE -- Date problem (varchar + min/max computed seperately)
FROM
Views AS V
GROUP BY
ID
)
SELECT
V.*,
M.MIN_DATE,
M.MAX_DATE
FROM
MinMax AS M
INNER JOIN Views AS V ON M.ID = V.ID