[GitHub] [spark] dilipbiswal edited a comment on issue #25331: [SPARK-27768][SQL] Support Infinity/NaN-related float/double literals case-insensitively

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dilipbiswal edited a comment on issue #25331: [SPARK-27768][SQL] Support Infinity/NaN-related float/double literals case-insensitively
URL: https://github.com/apache/spark/pull/25331#issuecomment-521431770
 
 
   Hello @DylanGuedes 
   
   Don't think its related to case sensitivity. I have not looked at it in detail, but from a cursory look it seems like we are not able to promote the col2 values to a common type in this code path. Removing windowing all together, the following fails :
   
   ```
   spark-sql> select * from (VALUES(1,1),(2,2),(3,'NaN'),(4,3),(5,4));
   Error in query: incompatible types found in column col2 for inline table; line 1 pos 15
   ```
   What is the table definition for `numerics` ? In case of normal table, the target type is known and so we try to implicitly convert the input values to the target type. It is slightly different in case of inline tables.
   

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