For the threads with the older one on the left: https://lemmy.world/post/14859950
(Thank you @Nelots@lemm.ee )
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I know everyone here likes to circle jerk over "le Reddit so incompetent" but at the end of the day they are a (multi) billion dollar company and it's willfully ignorant to infer that there isn't a single engineer at the company who knows how to measure string similarity between two comment trees (hint:
import difflibin python)You think in Reddit's 20 year history no one has thought of indexing comments for data science workloads? A cursory glance at their engineering blog indicates they perform much more computationally demanding tasks on comment data already for purposes of content filtering
Analytics workflows are never run on the production database, always on read replicas which are taken asynchronously and built from the transaction logs so as not to affect production database read/write performance
Reddit's entire monetization strategy is collecting user data and selling it to advertisers - It's incredibly naive to think that they don't have a vested interest in identifying organic engagement
I'm sure they have, but an index doesn't have anything to do with the python library you mentioned.
Sure, either that or aggregating live streams of data, but either way it doesn't have anything to do with ElasticSearch.
It's still totally possible to sync things to ElasticSearch in a way that won't affect performance on the production servers, but I'm just saying it's not entirely trivial, especially at the scale reddit operates at, and there's a cost for those extra servers and storage to consider as well.
It's hard for us to say if that math works out.
You would think, but you could say the same about Facebook and I know from experience that they don't give a fuck about bots. If anything they actually like the bots because it looks like they have more users.