Using another table as value type - sql

Question

I have been searching this and can not find the proper answer if I need an JOIN or SUBQUERY, I have tried multiple ways if doing this and honestly I am hitting a major wall. I am trying to do something simple and I don't know how to progress
I have two tables I am trying to use: table 1) data 2) mapping
table 1 is like this the headers are :
Date
Value1
Value2
Value3
Value4
Etc.
Value in CSV style for example would be:
1/1/10,1,2,3,4
1/2/10,5,6,7,8
1/3/10,9,10,11,12
table 2 has only one row though, here are the headers and one row
Value1
Value2
Value3
Value4
The one row would be like:
Description1, Description2, Description3, Description4
So, I want to be able to, for example do a SELECT FROM table 1 and join in the Description for each matching row where the Column names are the same, so sample output based on the above would be to be like this:
1/1/10,1,Description1,2,Description2,3,Description3,4,Description4
1/2/10,5,Description1,6,Description2,7,Description3,8,Description4
Etc

Answer 1

Since there's just one row in table2 and no key, you can simply join it.
select *
from table1
join table2
Since there's just one row in table2 it's questionable why it exists at all. This could be done without a join at all.
select date, value1, 'Description1', value2, 'Description2', value3, 'Description3', value4, 'Description4'
from table1;
There's likely a better way to do this. Having columns like value1, value2, and value3 usually indicates poor table design. Instead of having four value columns, you should have four value rows. And instead of having a table with four columns of descriptions, it should be four rows of descriptions.
For example, let's say you're storing items in an order. An order can have many items. Rather than having a column for each item in an order like item1, item2, item3, you'd have a row for each item in a join table. Below that's order_items. Descriptions of the items is stored separately in its own table, one row per item.
user
----
id bigint primary key
name text not null
items
-----
id bigint primary key
name text not null
orders
------
id bigint primary key
user_id bigint references users(id)
created_at datetime
order_items
-----------
order_id bigint references orders(id)
item_id bigint references items(id)
If you want to look up all the items in an order, with their names, you'd use the order_items table to get all the items in an order, and join with the items table to get each item's name.
select i.name
from order_items oi
join items i on i.id = oi.item_id
where oi.order_id = ?

Answer 2

Comma separated lists of values are awkward to handle.
Rather than a CSV, storing the values in a mapping table is typically used.
If I understand correctly then I believe that the following may demonstrate along the lines of what you want:-
DROP TABLE IF EXISTS table1 /* Assigned Values per date (the mapping table)*/;
DROP TABLE If EXISTS table2 /* Values */;
CREATE TABLE IF NOT EXISTS table2 (valueid INTEGER PRIMARY KEY,value_description TEXT);
CREATE TABLE IF NOT EXISTS table1 (date TEXT, valueid_reference INTEGER REFERENCES table2(valueid),value INTEGER, UNIQUE(date, valueid_reference));
INSERT INTO table2 VALUES (1,'Value1 Description'),(2,'Value2 Description'),(3,'Value3 Description'),(4,'Value4 Description');
INSERT INTO table1 VALUES
('1/1/10',1,1),('1/1/10',2,2),('1/1/10',3,3),('1/1/10',4,4),
('1/2/10',1,5),('1/2/10',2,6),('1/2/10',3,7),('1/2/10',4,8)
;
SELECT date||','||group_concat(value||','||value_description) AS all_values_and_descriptions FROM table1 JOIN table2 ON valueid_reference = valueid GROUP BY date;
SELECT * FROM table1;
This results in :-
Noting that the REFRENCES (Foreign Key) will be a noop unless Foreign Key support is enabled. However, without it will still work.
As can be seen each value per date is an individual row in table 1 (so 4 rows per date). It is the group_concat function that is used to get all the values per date in conjunction with the GROUP BY clause which creates a set of rows (a Group) for each date.
The 2nd SELECT shows the rows in table1 :-