I learned a lot of new information. The most shocking part was discovering that feed preferences use a "ranking algorithm," not just machine learning. I always thought it was only machine learning.
It's also interesting that the feed is pre-calculated in cache before a user visits, saving computer resources.
Great article Neo. Feeds are everywhere nowdays, Substack notes starts to gain popularity too. I'm curious to know how bad is the performance for non active users, who login after a long time with nothing in Redis :)
ranking approach is not explained well, are they fetching IDs from the redis list(linked-list) and sorting and re-inserting or just interesting at the end of the list?
Is it not insanely inefficient to pre-compute everyone's feed? That just seems wild to me. Is that a common approach or is it unique to HashNode?
Great article!
I learned a lot of new information. The most shocking part was discovering that feed preferences use a "ranking algorithm," not just machine learning. I always thought it was only machine learning.
It's also interesting that the feed is pre-calculated in cache before a user visits, saving computer resources.
Thanks, Neo, for teaching us this!
Great article Neo. Feeds are everywhere nowdays, Substack notes starts to gain popularity too. I'm curious to know how bad is the performance for non active users, who login after a long time with nothing in Redis :)
ranking approach is not explained well, are they fetching IDs from the redis list(linked-list) and sorting and re-inserting or just interesting at the end of the list?