cloud-fan commented on a change in pull request #29458:
URL: https://github.com/apache/spark/pull/29458#discussion_r471947639
##########
File path: docs/sql-migration-guide.md
##########
@@ -36,6 +36,10 @@ license: |
- In Spark 3.1, NULL elements of structures, arrays and maps are converted
to "null" in casting them to strings. In Spark 3.0 or earlier, NULL elements
are converted to empty strings. To restore the behavior before Spark 3.1, you
can set `spark.sql.legacy.castComplexTypesToString.enabled` to `true`.
+ - In Spark 3.1, when `spark.sql.ansi.enabled` is false, sum aggregation of
decimal type column always returns `null` on decimal value overflow. In Spark
3.0 or earlier, when `spark.sql.ansi.enabled` is false and decimal value
overflow happens in sum aggregation of decimal type column:
+ - If it is hash aggregation with `group by` clause, a runtime exception is
thrown.
Review comment:
We can use "default mode".
I don't see a difference between "may fail at runtime" or `may return null`.
They are mutually exclusive.
##########
File path: docs/sql-migration-guide.md
##########
@@ -36,6 +36,10 @@ license: |
- In Spark 3.1, NULL elements of structures, arrays and maps are converted
to "null" in casting them to strings. In Spark 3.0 or earlier, NULL elements
are converted to empty strings. To restore the behavior before Spark 3.1, you
can set `spark.sql.legacy.castComplexTypesToString.enabled` to `true`.
+ - In Spark 3.1, when `spark.sql.ansi.enabled` is false, sum aggregation of
decimal type column always returns `null` on decimal value overflow. In Spark
3.0 or earlier, when `spark.sql.ansi.enabled` is false and decimal value
overflow happens in sum aggregation of decimal type column:
+ - If it is hash aggregation with `group by` clause, a runtime exception is
thrown.
Review comment:
We can use "default mode".
I don't see a difference between "may fail at runtime" or "may return null".
They are mutually exclusive.
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