wForget commented on PR #1428:
URL:
https://github.com/apache/datafusion-comet/pull/1428#issuecomment-2684022663
Integral divide of `decimal` type has inconsistent behavior.
test:
```
test("test integral divide") {
withTable("t1", "t2") {
if (isSpark34Plus) {
// Decimal support requires Spark 3.4 or later
sql("create table t2(c1 DECIMAL(38, 37), c2 DECIMAL(38, 37)) using
parquet")
sql("insert into t2 values(6.0096743305738933273387748827369321010,
6.0096763826458053191384497987259478584)")
checkSparkAnswerAndOperator("select c1 / c2, cast((c1 / c2 ) as
long), c1 div c2 from t2 order by c1")
}
}
}
```
Results do not match:
```
== Results ==
!== Correct Answer - 1 ==
== Spark Answer - 1 ==
struct<(c1 / c2):decimal(38,6),CAST((c1 / c2) AS BIGINT):bigint,(c1 div
c2):bigint> struct<(c1 / c2):decimal(38,6),CAST((c1 / c2) AS
BIGINT):bigint,(c1 div c2):bigint>
![1.000000,1,0]
[1.000000,1,1]
```
This is due to the rounding behavior of `decimal_div`:
https://github.com/apache/datafusion-comet/blob/58a36b62004c1e300d7f3113d9a64713a94c0db9/native/spark-expr/src/math_funcs/div.rs#L72-L76
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