mihailom-db opened a new pull request, #48054:
URL: https://github.com/apache/spark/pull/48054
### What changes were proposed in this pull request?
Removal of suggestion to turn off ansi when experiencing CAST_INVALID_INPUT
or CAST_OVERFLOW.
### Why are the changes needed?
These errors already contain sufficient suggestions, amongst which one is to
use `try_cast` in place of `cast`. This removal of ANSI turn off suggestion is
part of a movement keep suggestions of not using ANSI in code to minimum.
### Does this PR introduce _any_ user-facing change?
Yes. This PR is changing user-facing error message.
Previous state:
`
SELECT CAST('a' AS INT)
org.apache.spark.SparkNumberFormatException: [CAST_INVALID_INPUT] The value
'a' of the type "STRING" cannot be cast to "INT" because it is malformed.
Correct the value as per the syntax, or change its target type. Use `try_cast`
to tolerate malformed input and return NULL instead. If necessary set
"spark.sql.ansi.enabled" to "false" to bypass this error.
SELECT CAST(2147483648L AS INT);
org.apache.spark.SparkArithmeticException: [CAST_OVERFLOW] The value
2147483648L of the type "BIGINT" cannot be cast to "INT" due to an overflow.
Use `try_cast` to tolerate overflow and return NULL instead. If necessary set
"spark.sql.ansi.enabled" to "false" to bypass this error.
`
Current state:
`
SELECT CAST('a' AS INT)
org.apache.spark.SparkNumberFormatException: [CAST_INVALID_INPUT] The value
'a' of the type "STRING" cannot be cast to "INT" because it is malformed.
Correct the value as per the syntax, or change its target type. Use `try_cast`
to tolerate malformed input and return NULL instead.
SELECT CAST(2147483648L AS INT);
org.apache.spark.SparkArithmeticException: [CAST_OVERFLOW] The value
2147483648L of the type "BIGINT" cannot be cast to "INT" due to an overflow.
Use `try_cast` to tolerate overflow and return NULL instead.
`
### How was this patch tested?
Existing tests check for existence of ansiConfig message parameter.
### Was this patch authored or co-authored using generative AI tooling?
No.
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