stczwd edited a comment on pull request #28617:
URL: https://github.com/apache/spark/pull/28617#issuecomment-667083355


   @cloud-fan Thanks for paying attention on this PR. This can be changed to 
`WIP` if we still have some conflicts.
   
   > What is the reason to extend `TableCatalog` instead of `Table`? I think it 
would be better to support partitions at a table level.
   > 
   > Doing it this way creates more complexity for implementations because they 
need to handle more cases. For example, if the table doesn't exist, this should 
throw `NoSuchTableException` just like `loadTable`. It would be simpler for the 
API if these methods were used to manipulate a table, not to load _and_ 
manipulate a table. Loading should be orthogonal to partition operations.
   > 
   > Another issue is that this assumes a table catalog contains tables that 
support partitions, or tables that do not. But Spark's built-in catalog 
supports some sources that don't expose partitions and some that do. This would 
cause more work for many catalogs, which would need to detect whether a table 
has support and throw `UnsupportedOperationException` if it does not. That also 
makes integration more difficult for Spark because it can't check a table in 
the analyzer to determine whether it supports the operation or not. Instead, 
Spark would need to handle exceptions at runtime.
   
   
   This is the comment given by @rdblue before, and I also agree with it.
   Firstly, in many sources, except hive external table, the partition 
operation may modify actual table data.
   Secondly, most of partition commands, such as 
`AlterTableAddPartitionCommand`, we need loadTable before operate the partition.
   Finally, it will be easily to do more partition operations on Table, such as 
truncate partition in mysql.


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