How to Efficiently Merge Overlapping Date Intervals in SQL?

Merging Overlapping Date Intervals

In the realm of data analysis, it is common to encounter overlapping time ranges or date intervals. To effectively merge these overlapping intervals into distinct records, a robust and efficient solution is required.

One straightforward approach to merging overlapping date intervals is presented in the given question, utilizing a series of UPDATE statements within a loop. While this method achieves the desired result, it introduces the concern of whether there may be a more elegant or performant solution.

An Alternative Approach

An alternative approach, implemented in the provided answer, harnesses the power of correlated subqueries and NOT EXISTS conditions. This approach involves several SQL statements that operate in conjunction to identify and merge overlapping intervals:

SELECT 
       s1.StartDate,
       --t1.EndDate 
       MIN(t1.EndDate) AS EndDate
FROM @T s1 
INNER JOIN @T t1 ON s1.StartDate <= t1.EndDate
  AND NOT EXISTS(SELECT * FROM @T t2 
                 WHERE t1.EndDate >= t2.StartDate AND t1.EndDate < t2.EndDate) 
WHERE NOT EXISTS(SELECT * FROM @T s2 
                 WHERE s1.StartDate > s2.StartDate AND s1.StartDate <= s2.EndDate) 
GROUP BY s1.StartDate 
ORDER BY s1.StartDate 

Breaking down the steps:

1. Identifying Overlapping Intervals: The query pairs each interval (s1) with other intervals (t1) that overlap it. This is achieved through the INNER JOIN condition s1.StartDate <= t1.EndDate.
2. Excluding Indirect Overlaps: The subquery NOT EXISTS(SELECT * FROM @T t2 WHERE t1.EndDate >= t2.StartDate AND t1.EndDate < t2.EndDate) ensures that only direct overlaps are considered. This prevents the merging of intervals that are indirectly connected by a chain of overlapping intervals.
3. Eliminating Duplicate Intervals: The outer NOT EXISTS condition NOT EXISTS(SELECT * FROM @T s2 WHERE s1.StartDate > s2.StartDate AND s1.StartDate <= s2.EndDate) prevents merging distinct intervals that have the same start date but a different end date. This ensures that only unique intervals are represented in the result.
4. Selecting Non-Overlapping Intervals: By correlating subqueries and utilizing NOT EXISTS conditions, the query effectively identifies and merges overlapping intervals while excluding duplicate or indirectly connected intervals.

This approach offers improved performance and clarity compared to the iterative UPDATE method, making it a preferred solution for merging overlapping date intervals in SQL environments.

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