kazdy commented on issue #7282:
URL: https://github.com/apache/hudi/issues/7282#issuecomment-1327328186

   I think the goal here would be to have good support for users who want to 
have something that resembles a table in DWH/RDBMS but use Hudi.
   I've seen some new users thinking it's a bug that preCombine is required and 
it was confusing at first. 
   
   So happy path would be to make sure Spark SQL supports a model with PK and 
no precombine by default.
   This would hopefully increase adoption and make the learning curve shallow.
   For more advanced users, it's still great to have the option to use 
precombine as it's useful for incremental/streaming/cdc pipelines and event 
deduplication.
   
   Besides what we're missing is a modeling guide for Hudi datasets, it forces 
users to make certain assumptions about how hudi data pipelines should work 
(which is expected for a framework), as precombine and pk constraints are given.
   
   So a part of this work would be to provide a guide for:
   1. pk + no_precombine model 
   2. pk + precombine model
   With clearly described pros and cons of both, when to use what, and how. 
   Describe how to handle surrogate/factless keys for datasets where PK can not 
be clearly defined and so on.
   
   


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