Step 1: Understanding the Problem

The problem involves joining multiple tables with overlapping time periods using SQL. The goal is to find a solution that allows for efficient handling of additional temporal tables.

Step 2: Analyzing the Current Query

The current query uses a CASE statement to determine the start and end dates of the intervals, but it only considers two tables. This approach may not be scalable if more tables are added.

Step 3: Considering Alternative Approaches

One alternative approach is to use the geometry data type in SQL Server, which allows for representing time periods as spatial objects. This can simplify the process of finding overlapping intervals and make it easier to nest subqueries.

Step 4: Applying the Geometry Data Type

By applying the geometry data type, we can create a spatial object that represents the time period of each table. This allows us to use geometric functions to find the intersection and length of the intervals, making it easier to determine the start and end dates.

Step 5: Modifying the Query

The modified query uses the geometry data type to represent the time periods of each table. It then finds the intersection and length of the intervals using geometric functions and determines the start and end dates based on these values.

Step 6: Evaluating Performance

While the geometry data type approach may not be the fastest for very large datasets, it provides a more scalable solution than the original query.

The final answer is: $\boxed{1}$

Last modified on 2024-03-16