I'm trying to calculate the average turnover time of a piece of equipment in REPAIR status.
I was able to create a query containing a list of equipments with their snapshotted status on each day.
+-----------------+--------------+--------+----------------------+------------+------------------+
| equipmentNumber | snapshotDate | status | previousSnapshotDate | prevStatus | statusChangeFlag |
+-----------------+--------------+--------+----------------------+------------+------------------+
|          123456 | 2018-04-29   | ONHIRE | 2018-04-28           | AVAILABLE  |                1 |
|          123456 | 2018-04-30   | ONHIRE | 2018-04-29           | ONHIRE     |                0 |
|          123456 | 2018-05-01   | ONHIRE | 2018-04-30           | ONHIRE     |                0 |
|          123456 | 2018-05-02   | REPAIR | 2018-05-01           | ONHIRE     |                1 |
|          123456 | 2018-05-03   | REPAIR | 2018-05-02           | REPAIR     |                0 |
|          123456 | 2018-05-04   | ONHIRE | 2018-05-03           | REPAIR     |                1 |
|          654321 | 2018-04-30   | REPAIR | 2018-04-29           | AVAILABLE  |                1 |
|          654321 | 2018-05-01   | REPAIR | 2018-04-30           | REPAIR     |                0 |
|          654321 | 2018-05-02   | REPAIR | 2018-05-01           | REPAIR     |                0 |
+-----------------+--------------+--------+----------------------+------------+------------------+
So, in this example, we have 2 equipments, "123456" was in REPAIR status 2 days on 5/2 and 5/3, and "654321" was in REPAIR status 3 days on 4/30, 5/1, and 5/2. That would be an average repair turnaround time of (2+3) / 2 = 2.5 days.
I tried this algorithm (Detect consecutive dates ranges using SQL) but it doesn't seem to be quite working for my needs.