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by mulmen
805 days ago
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I admit this is a bit outside my wheelhouse so I’m probably still missing something. Isn’t this just a table with 5bn rows of timestamp, page_type, page_views_t1d, page_views_t7d, page_views_t30d, page_views_t60d, and page_views_t180d? You can even compute this incrementally or in parallel by timestamp and/or page_type. What’s the magic Chronon is doing? |
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But even for offline computation, for the same computation logic, the code will be duplicated in lots of places. we have observed the ML practitioners copied sql queries all over. In the end, it is not possible for debugging, feature interpretability and lineage.
Chronon abstracts all those away so that ML practitioners can focus on the core problems they are dealing with, rather than spending time on the ML Ops.
For an extreme use case, one user defined 1000 features with 250 lines of code, which is definitely impossible with SQL queries, not to even mention the extra work to serve those features.