calculate column names automatically sql - sql

Question

Is there a way to calculate column names automatically in SQL like below. I need top calculate the Calendar weeks based on from and to date and distribute evenly
Material
From
To
Sales
M01
03.10.2022
31.10.2022
1000
M02
14.11.2022
28.11.2022
1000
Expected output
CW =calendar week
Material
Cw40
CW41
Cw42
CW43
CW44
CW45
CW46
CW47
M01
250
250
250
250
M02
500
500

Answer 1

Is there a way to calculate column names automatically in SQL like below.
No, in SQL (not just Oracle SQL) you needs a fixed, known number of column names so it is impossible to dynamically generate columns with a static SQL query.
If you want to generate the data then either:
Generate the data as rows (rather than columns) and pivot the result in whatever third-party application you are using to access the database. You can generate the output using a correlated row-generator:
SELECT t.material,
w.iso_year,
w.iso_week,
w.weekly_sales
FROM table_name t
CROSS APPLY (
SELECT TO_NUMBER(
TO_CHAR(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
'IYYY'
)
) AS iso_year,
TO_NUMBER(
TO_CHAR(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
'IW'
)
) AS iso_week,
( LEAST(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * LEVEL,
to_dt
)
- GREATEST(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
from_dt
)
) / (to_dt - from_dt) * sales AS weekly_sales
FROM DUAL
CONNECT BY TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL-1) < to_dt
) w
or:
WITH data (from_dt, dt, to_dt, material, sales) AS (
SELECT from_dt, from_dt, to_dt, material, sales
FROM table_name
UNION ALL
SELECT from_dt,
TRUNC(dt + INTERVAL '7' DAY, 'IW'),
to_dt,
material,
sales
FROM data
WHERE TRUNC(dt + INTERVAL '7' DAY, 'IW') < to_dt
)
SELECT material,
TO_NUMBER(TO_CHAR(dt, 'IYYY')) AS iso_year,
TO_NUMBER(TO_CHAR(dt, 'IW')) AS iso_week,
( LEAST(dt + INTERVAL '7' DAY, to_dt) - dt)
/ (to_dt - from_dt) * sales AS weekly_sales
FROM data
Which, for the sample data:
CREATE TABLE table_name (Material, From_dt, To_dt, Sales) AS
SELECT 'M01', DATE '2022-10-03', DATE '2022-10-31', 1000 FROM DUAL UNION ALL
SELECT 'M02', DATE '2022-11-14', DATE '2022-11-28', 1000 FROM DUAL;
Both output:
MATERIAL
ISO_YEAR
ISO_WEEK
WEEKLY_SALES
M01
2022
40
250
M01
2022
41
250
M01
2022
42
250
M01
2022
43
250
M02
2022
46
500
M02
2022
47
500
Or, if you did want to output the values as columns then you need to specify the columns (which would be 53 columns for all 53 potential ISO weeks) and can do that using:
SELECT *
FROM (
SELECT t.material,
w.iso_year,
w.iso_week,
w.weekly_sales
FROM table_name t
CROSS APPLY (
SELECT TO_NUMBER(
TO_CHAR(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
'IYYY'
)
) AS iso_year,
TO_NUMBER(
TO_CHAR(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
'IW'
)
) AS iso_week,
( LEAST(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * LEVEL,
to_dt
)
- GREATEST(
TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL - 1),
from_dt
)
) / (to_dt - from_dt) * sales AS weekly_sales
FROM DUAL
CONNECT BY TRUNC(from_dt, 'IW') + INTERVAL '7' DAY * (LEVEL-1) < to_dt
) w
)
PIVOT (
SUM(weekly_sales)
FOR iso_week IN (
1 AS cw01,
2 AS cw02,
3 AS cw03,
-- ...
40 AS cw40,
41 AS cw41,
42 AS cw42,
43 AS cw43,
44 AS cw44,
45 AS cw45,
46 AS cw46,
47 AS cw47,
48 AS cw48,
49 AS cw49,
50 AS cw50,
51 AS cw51,
52 AS cw52,
53 AS cw53
)
)
or:
WITH data (from_dt, dt, to_dt, material, sales) AS (
SELECT from_dt, from_dt, to_dt, material, sales
FROM table_name
UNION ALL
SELECT from_dt,
TRUNC(dt + INTERVAL '7' DAY, 'IW'),
to_dt,
material,
sales
FROM data
WHERE TRUNC(dt + INTERVAL '7' DAY, 'IW') < to_dt
)
SELECT *
FROM (
SELECT material,
TO_NUMBER(TO_CHAR(dt, 'IYYY')) AS iso_year,
TO_NUMBER(TO_CHAR(dt, 'IW')) AS iso_week,
( LEAST(dt + INTERVAL '7' DAY, to_dt) - dt)
/ (to_dt - from_dt) * sales AS weekly_sales
FROM data
)
PIVOT (
SUM(weekly_sales)
FOR iso_week IN (
1 AS cw01,
2 AS cw02,
3 AS cw03,
-- ...
40 AS cw40,
41 AS cw41,
42 AS cw42,
43 AS cw43,
44 AS cw44,
45 AS cw45,
46 AS cw46,
47 AS cw47,
48 AS cw48,
49 AS cw49,
50 AS cw50,
51 AS cw51,
52 AS cw52,
53 AS cw53
)
)
Which both output:
MATERIAL
ISO_YEAR
CW01
CW02
CW03
CW40
CW41
CW42
CW43
CW44
CW45
CW46
CW47
CW48
CW49
CW50
CW51
CW52
CW53
M01
2022
null
null
null
250
250
250
250
null
null
null
null
null
null
null
null
null
null
M02
2022
null
null
null
null
null
null
null
null
null
500
500
null
null
null
null
null
null
fiddle