I have a table that contains employee bank data
Employee |Bank |Date |Delta
---------------------------------------------------
Smith |Vacation |2023-01-01 |15.0
Smith |Vacation |2023-01-02 |Null
Smith |Vacation |2023-01-03 |Null
Smith |Vacation |2023-01-04 |7.5
I would like to write a statement so that I can update 2023-01-02 and 2023-01-03 with the Delta value from January 1. Essentially, I want to use the value from the most recent row that isn't > than the date on the row.
Once complete, I want the table to look like this:
Employee |Bank |Date |Delta
---------------------------------------------------
Smith |Vacation |2023-01-01 |15.0
Smith |Vacation |2023-01-02 |15.0
Smith |Vacation |2023-01-03 |15.0
Smith |Vacation |2023-01-04 |7.5
The source table has a unique index consisting of Employee, Bank and Date descending. There could be up to 2 billion rows in the table.
I currently update the table with the following, but I am wondering if there is a more efficient way to do so?
WITH cte_date
AS (SELECT dd.date_key,
db.balance_key,
feb.employee_key
FROM shared.dim_date dd
CROSS JOIN
(
SELECT DISTINCT
employee_key
FROM wfms.fact_employee_balance
) feb
CROSS JOIN wfms.dim_balance db
WHERE dd.date BETWEEN DATEFROMPARTS(DATEPART(YY, GETDATE()) - 2, 12, 31) AND GETDATE())
SELECT dd.*,
t.delta
INTO wfms.test2
FROM cte_date dd
LEFT JOIN wfms.test1 t ON dd.balance_key = t.balance_key
AND dd.employee_key = t.employee_key
AND t.date_key = (SELECT TOP 1 tt1.date_key
FROM wfms.test1 tt1
WHERE tt1.balance_key = t.balance_key
AND tt1.employee_key = t.employee_key
AND tt1.date_key < dd.date_key);