I'm working with an event dataset as the one in the example below:
Event_Type Event_Timestamp Is_Active A 2010-10-01 00:00:00 1 B 2010-10-01 00:00:01 1 A 2010-10-01 00:00:02 0 D 2010-10-01 00:00:03 1 B 2010-10-01 00:00:04 0 C 2010-10-01 00:00:05 1 A 2010-10-01 00:00:06 1 A 2010-10-01 00:00:07 1 A 2010-10-01 00:00:08 0
The dataset is ordered by the timestamp of the events and the data grows as events happens in real time. More event types could be included in the dataset at any time (not limited to only A, B, C, D as in the example) and the same event type could appear in the table multiple times. The Is_Active boolean field serves as a way to indicate whether the event is still active (1) or not (0).
In this sense, I tried to do some transformations on this data by using SQL Window Functions. I'm not necessarily restricted to a specific product or technology, so feel free to tell how you would address the problem below.
What I want to do is dynamically pair each event of the same type when they have opposite Is_Active values and then get how long that event was active. In other words, given an event X, I would need to get the Event_Timestamp for it when Is_Active had 1 for the first time (Begin_Timestamp), and then ignore the rest of the rows for this event X with Is_Active 1 until I get Is_Active 0, so I could take the Event_Timestamp again (End_Timestamp). Then, I would continue applying this logic when I find event X having 1 in the Is_Active column again.
An example of the resulting table would be:
Event_Type Begin_Timestamp End_Timestamp Duration A 2010-10-01 00:00:00 2010-10-01 00:00:02 2 seconds B 2010-10-01 00:00:01 2010-10-01 00:00:04 3 seconds D 2010-10-01 00:00:03 null null C 2010-10-01 00:00:05 null null A 2010-10-01 00:00:06 2010-10-01 00:00:08 2 seconds
Is there any window function that would help me get these pairs of events so I could compute the duration of each event?