[GitHub] [spark] stczwd edited a comment on pull request #28617: [SPARK-31694][SQL] Add SupportsPartitions APIs on DataSourceV2

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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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