I am trying to find the shortest distance and shortest travel time from one point to another point. However, I have a large number of data (140 000s). I break my data to smaller feature classes of 10 000 and run the model. However, it took more than 12 hours to run one model, since I have broken down my data to 15 sets, it will take a long time for me to run the model. I also need to find the straight distance between the points thus, i have three model running for the data. It takes a lot of time and I have to do this quite frequent. I am wondering if there is a better ways of doing this. there are probably other ways of doing this but I am not sure about it.
Currently, this is how my model looks like:
I used iterator to iterate through each records (there are 10 000 records). Each point will have destination.
I am finding the shortest route and the shortest travel time thus I will run this model twice with different impedance (Minute and Km).
After the network route is solved, it will append to a holding file (I think the whole model take a long time to run due to the append).