I’m working on a tricky SQL problem involving two tables with a one-to-many relationship. Here’s what I’m dealing with:
Table A has rows with a unique identifier, start date, and end date. Table B contains multiple entries per identifier, each having its own start and end dates along with an associated value.
I need to write a query that merges these tables and splits the date ranges to correctly display the value during each period. The final output should resemble:
id start_date end_date value
001 2023-01-01 2023-01-15 Alpha
001 2023-01-16 2023-01-31 Beta
001 2023-02-01 2023-02-28 Beta
Any suggestions on how to tackle this? I’m considering joins or subqueries and would appreciate any guidance.
This problem can be effectively tackled using a combination of Common Table Expressions (CTEs) and window functions.
Start by creating a CTE that combines all distinct dates from both tables. Then, use LAG and LEAD functions to identify the start and end of each period.
Finally, join this result with your original tables to assign the correct values. This approach handles overlapping ranges efficiently and scales well with large datasets. It’s particularly effective in PostgreSQL or SQL Server, but can be adapted for other DBMS. I’ve implemented similar solutions in production environments, and they’ve proven robust and performant.
hey, have u tried a recursive cte, possibly with a cross apply? did u consider adjusting the ranges dynamically?
what db system r u on? some systems have unique funcs. curious if others had similar success.