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The procedure throws an exception if column definition between a source and a target table doesn't exctly match. We could add a function argument which tweaks the validation because the schema can be a little different.
Probably, we should still disallow the following situation even if the option is enabled:
schema is completely different: (a int) ↔︎ (y string)
different column types with same column name: (a int) ↔︎ (a string)
this is allowed in Spark's add_files procedure, but it throws an exception when reading tables
The procedure throws an exception if column definition between a source and a target table doesn't exctly match. We could add a function argument which tweaks the validation because the schema can be a little different.
Probably, we should still disallow the following situation even if the option is enabled:
(a int)
↔︎(y string)
(a int)
↔︎(a string)
add_files
procedure, but it throws an exception when reading tablesRelates to #22751 (comment) by @cwsteinbach
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