Github user wojtek-szymanski commented on a diff in the pull request:
https://github.com/apache/spark/pull/17075#discussion_r104327814
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/MathFunctionsSuite.scala ---
@@ -233,6 +233,18 @@ class MathFunctionsSuite extends QueryTest with
SharedSQLContext {
)
}
+ test("round/bround with data frame from a local Seq of Product") {
+ val df = spark.createDataFrame(Seq(NumericRow(BigDecimal("5.9"))))
--- End diff --
The fundamental difference is in the underlying row type assigned to
dataframe/dataset. Dataframe is based on `GenericInternalRow`, while Dataset
uses `UnsafeRow`. During evaluation of round expression, method `getDecimal` is
called on a row, see
[BoundAttribute.scala#L52](https://github.com/apache/spark/blob/39e2bad6a866d27c3ca594d15e574a1da3ee84cc/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala#L52).
As a result `GenericInternalRow` returns just an element of an array, which
points to the reference of the original column, see
[rows.scala#L200](https://github.com/apache/spark/blob/97594c29b723f372a5c4c061760015bd78d01f50/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala#L200).
Strategy used in `UnsafeRow` is completely different, so new decimal instance
is created, see
[UnsafeRow.java#L399](https://github.com/apache/spark/blob/a1e40b1f5d651305bbd0ba05779263a44f607498/sql/catalyst/src/main/java/org/apache/
spark/sql/catalyst/expressions/UnsafeRow.java#L399).
I hope it helps to explain why only dataframe is affected.
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