Hi! My first post here, I have been searching the forums but no other question seems to match my problem
I have 2 tables (I will simplify for the question purposes)
The first one is a set of measurements taken once per second on different vehicles while on the assembly line:
| VIN | Measurement_DateTime | Measurement_Value |
| AABBCCDDEEFFGG | 2023-07-17 14:19:55 | 4.79788 |
| AABBCCDDEEFFGG | 2023-07-17 14:19:56 | 4.89238 |
| ..... | ..... | .... |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:25:45 | 0.408938 |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:25:46 | 0.4075 |
| .... | .... | .... |
The second table is a set of records of vehicles passing through different assembly line stations, relevant fields below:
| VIN | Station_Start_DateTime | Station Name |
| AABBCCDDEEFFGG | 2023-07-17 14:19:01 | Station A |
| AABBCCDDEEFFGG | 2023-07-17 14:29:35 | Station B |
| AABBCCDDEEFFGG | 2023-07-17 14:39:15 | Station C |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:16:15 | Station A |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:23:36 | Station B |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:28:32 | Station C |
Desired Output: For every measurement taken, add a field with the station name where the vehicle was at the DateTime when the measurement was taken. We can assume that each station starts on Station_Start_DateTime and ends just before the next station
| VIN | Measurement_DateTime | Measurement_Value | Station_Name |
| AABBCCDDEEFFGG | 2023-07-17 14:19:55 | 4.79788 | Station A |
| AABBCCDDEEFFGG | 2023-07-17 14:19:56 | 4.89238 | Station A |
| ..... | ..... | .... | |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:25:45 | 0.408938 | Station B |
| HHIIJJKKLLMMNNOO | 2023-07-19 14:25:46 | 0.4075 | Station B |
| .... | .... | .... | |
This is how I am doing it now, but it is extremely inefficient, as the Join block generates GB's of data when combining both tables. My dataset will grow over time, I just measured 2 vehicles and the PC struggles. I need to find a better solution as I need to measure tens of vehicles.

Thank You!
Javier