cloud-fan commented on a change in pull request #29458:
URL: https://github.com/apache/spark/pull/29458#discussion_r471906037
##########
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:
not many users know the physical nodes. How about
```
In Spark 3.1, Spark always returns null if the sum of decimal overflows
under non-ANSI
mode (`spark.sql.ansi.enabled` is false). In Spark 3.0 or earlier, the sum
of decimal may
fail at runtime under non-ANSI mode (when the query has GROUP BY and is
planned as hash aggregate)
```
##########
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:
not many users know the physical nodes. How about
```
In Spark 3.1, Spark always returns null if the sum of decimal overflows
under non-ANSI
mode (`spark.sql.ansi.enabled` is false). In Spark 3.0 or earlier, the sum
of decimal may
fail at runtime under non-ANSI mode (when the query has GROUP BY and is
planned as hash aggregate)
```
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