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https://issues.apache.org/jira/browse/HUDI-512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17277247#comment-17277247
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sivabalan narayanan commented on HUDI-512:
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[~vinoth] [~nishith29] [~varadarb] : feel free to comment on author's thoughts. 

> Decouple logical partitioning from physical one. 
> -------------------------------------------------
>
>                 Key: HUDI-512
>                 URL: https://issues.apache.org/jira/browse/HUDI-512
>             Project: Apache Hudi
>          Issue Type: Improvement
>          Components: Common Core
>            Reporter: Alexander Filipchik
>            Priority: Major
>              Labels: features
>
> This one is more inspirational, but, I believe, will be very useful. 
> Currently hudi is following Hive table format, which means that data is 
> logically and physically partitioned into folder structure like:
> table_name
>   2019
>     01
>     02
>        bla.parquet
>  
> This has several issues:
>  1) Modern object stores (AWS S3, GCP) are more performant when each file 
> name starts with some kind of a random value. By definition Hive layout is 
> not perfect
> 2) Hive Metastore stores partitions in the text field in the single table (2 
> tables with very similar information) and doesn't support proper filtering. 
> Data partitioned by day will be stored like:
> 2019/01/10
> 2019/01/11
> so only regexp queries are suported (at least in Hive 2.X.X)
> 3) Having a single POF which relies on non distributed DB is dangerous and 
> creates bottlenecks. 
>  
> The idea is to get rid of logical partitioning all together (and hive 
> metastore as well). If dataset has a time columns, user should be able to 
> query it without understanding what is the physical layout of the table (by 
> specifying those partitions explicitly or ending up with a full table scan 
> accidentally).
> It will require some kind of mapping of time to file locations (similar to 
> Iceberg). I'm also leaning towards the idea that storing table metadata with 
> the table is a good thing as it can be read by the engine in one shot and 
> will be faster that taxing a standalone metastore. 



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