To optimize performance for large graphs, I have some ideas that could potentially improve the process. Currently, with every call to pgRouting, there is a time overhead for loading the graph from the PostgreSQL database and building the Boost C++ graph structure internally before running the algorithm.
My idea is to explore two possible approaches:
Keep the Graph in RAM:
It is possible to load the entire graph from the PostgreSQL database into RAM and keep it there during the lifetime of the application or API. By doing so, subsequent calls to the routing algorithm can directly access the graph data in memory, significantly reducing the overhead of loading the graph from the database each time.
Generate Boost Graph Structure in RAM:
If keeping the entire graph in RAM is not feasible due to size constraints, another approach is to generate the Boost C++ graph structure directly in memory and cache it for subsequent algorithm calls.
To optimize performance for large graphs, I have some ideas that could potentially improve the process. Currently, with every call to pgRouting, there is a time overhead for loading the graph from the PostgreSQL database and building the Boost C++ graph structure internally before running the algorithm.
My idea is to explore two possible approaches:
Keep the Graph in RAM:
It is possible to load the entire graph from the PostgreSQL database into RAM and keep it there during the lifetime of the application or API. By doing so, subsequent calls to the routing algorithm can directly access the graph data in memory, significantly reducing the overhead of loading the graph from the database each time.
Generate Boost Graph Structure in RAM:
If keeping the entire graph in RAM is not feasible due to size constraints, another approach is to generate the Boost C++ graph structure directly in memory and cache it for subsequent algorithm calls.