Fokko opened a new pull request #26737: [SPARK-30103][SQL] Consolidate Schema 
merge logic
URL: https://github.com/apache/spark/pull/26737
 
 
   While working at https://github.com/apache/spark/pull/26644 I've noticed 
something strange in behavior.
   
   https://github.com/apache/spark/pull/26644 focusses on merging 
UserDefinedTypes into Spark's native types. Delta checks if the schema is still 
compatible, so as an integration test I tried to union two DF's, where one has 
a UserDefinedTypes, which should then be merged into a native type. To mimic 
this, I've used an union there, because we don't have the Delta extension, and 
Spark does not check schema compatibility on write, so it is impossible to 
reproduce the situation that we've observed with Delta.
   
   However, when Delta checks compatibility, it merges the schema using the 
`StructType.merge()`, and when Spark checks compatibility, it uses the 
`TypeCoercion`:
   
https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala#L314-L323
   
   Since this is complex code, I think we should merge these two to get similar 
behavior. Curious what your opinion is on this, and why these so similar 
functions are kept separately.
   
   ### What changes were proposed in this pull request?
   
   Removing the `StructType.merge()`, and use 
`TypeCoercion.findTightestCommonType()` instead. The one in TypeCoercion looks 
more complete.
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   ### Why are the changes needed?
   
   To simplify the codebase, and consolidate the behavior of merging schemas.
   
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   ### Does this PR introduce any user-facing change?
   
   Not in UI/Console, possibly in behavior.
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   ### How was this patch tested?
   
   Existing unit tests,
   
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