Has anyone done a similar thing with Spark and Postgresql for large graphs ? I'm curious to know how you write and structure your algorithms, given that graph p

Has anyone done a similar thing with Spark and Postgresql for large graphs ? I'm curious to know how you write and structure your algorithms, given that graph partitioning is quite tricky (and not possible for a lot of algorithms). I'm guessing Google uses a variant of this at scale - but not sure if their label propagation algorithms can be implemented on something like Spark and Postgres.