ClickHouse SQL Engineering: How to Identify Overlapping Date Ranges

To identify overlapping date ranges in ClickHouse, you can use SQL queries that compare the start and end dates of each range to determine if there are any overlaps.

Example to identify Overlapping Date Ranges

Here’s an example using a real-life dataset of employee vacation schedules. Assume we have a ClickHouse table called “vacation_schedule” with the following structure:

CREATE TABLE vacation_schedule (
employee_id UInt32,
start_date Date,
end_date Date
) ENGINE = MergeTree()
ORDER BY (employee_id, start_date);

The table contains employee vacation schedules with their respective start and end dates. To identify overlapping date ranges, we can execute the following SQL query:

SELECT a.employee_id AS employee1,
b.employee_id AS employee2,
a.start_date AS start_date1,
a.end_date AS end_date1,
b.start_date AS start_date2,
b.end_date AS end_date2
FROM vacation_schedule AS a
JOIN vacation_schedule AS b
ON a.employee_id < b.employee_id
AND a.start_date <= b.end_date
AND a.end_date >= b.start_date;

This query performs a self-join on the “vacation_schedule” table, comparing each employee’s vacation schedule with all other employees’ schedules. It selects rows where the employee IDs are different and where the date ranges overlap.

The result will include rows indicating overlapping date ranges between employees, along with the corresponding dates:

employee1 | employee2 | start_date1 | end_date1 | start_date2 | end_date2
------------------------------------------------------------------------
1         | 2         |  2022-08-01 | 2022-08-10|  2022-08-05 | 2022-08-12
2         | 3         |  2022-09-01 | 2022-09-10|  2022-09-08 | 2022-09-15

In this example, we can see that employee 1 and employee 2 have overlapping vacation schedules from August 5th to August 10th. Similarly, employee 2 and employee 3 have overlapping schedules from September 8th to September 10th.

Conclusion

By adapting this approach to your specific dataset and date range criteria, you can effectively identify overlapping date ranges in ClickHouse.

To read more about SQL Engineering in ClickHouse, do consider reading the below articles

About Shiv Iyer 215 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.