Suppose I have events (telephone call logs) where each event has:
- start timestamp
- end timestamp
- destination id
I can plot a # of calls distribution along a time interval just by defining the Y-axis as a Count metric and the X-axis as a date histogram on the start timestamp field. Therefore, if the log contains 1000 calls in a day, the sum of the y value of all data points on the resulting distribution will be 1000 (distributed in each hour on an hourly interval, for example). In this case, the semantics of each point is "the number of calls STARTED in this hour interval".
However, I want to plot a distribution based on the whole duration of a call. Therefore, if a call starts at 1pm and ends at 4:30 pm, this single call must add 1 to the 1pm-2pm bucket, 1 to the 2pm-3pm bucket, 1 to the 3pm-4pm bucket and 1 to the 4pm-5pm bucket, and the same occurs for each call in the log. Therefore the sum of the y value of all data points on a 1000 calls log can be more than 1000. The desired semantics is "the number of active calls in this hour interval". Since one call may span several time intervals (x-axis), it should add 1 to each of those hour intervals. I was not able to find a way to define this kind of distribution in Kibana. Any thoughts on that?