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As a contributor, I think it's interesting when comments focus on the language (Python vs Rust) vs the architecture (local vs remote). Inference is embarrassing
by montanalow 4y ago
As a contributor, I think it's interesting when comments focus on the language (Python vs Rust) vs the architecture (local vs remote). Inference is embarrassingly parallelizable, with Python Flask or Postgres replicas. I think the interesting thing is that data retrieval costs tend to dominate other costs, and yet are often ignored.
ML algorithms get a lot focus and hype. Data retrieval, not as much.
- chaps 4y agoFor anyone who skips the intro and just goes to the results, this is what they see: https://imgur.com/tEK73e8 https://imgur.com/tEK73e8 A suggestion: clean up the blog post's charts and headers to make it much, much more clear that what's being compared isn't python vs postgresml.
- montanalow 4y agoAnother suggestion: Don't build you identity around a language or platform. They come and go. Except SQL. It's been around for longer than either of us.
- chaps 4y agoAgreed, which is why I use postgres for most of my work unless I can't avoid it.
- deepstack 4y agothat is reason many older developer tend to do everything biz logic etc all in db store procedure/functions/view, etc. The cost of getting the data is native, no connection pooling needed, and with V8/python integration in the PG, it is non trivial what language you use. If you are dealing with large amount of data in a db, why not just do everything there. DB like sql has cursor, merge, that makes manipulating large set of data much easier than moving it on to another language environment.