[SPARK-32136] Spark producing incorrect groupBy results when key is a struct with nullable properties

• Type: Bug
• Status: Resolved
• Priority: Blocker
• Resolution: Fixed
• Affects Version/s: 3.0.0
• Fix Version/s: 3.0.1, 3.1.0
• Component/s: SQL
• Labels: correctness
• Target Version/s: 3.0.1
• Assignee: L. C. Hsieh
• Reporter: Jason Moore
• Created: 30/Jun/20 08:59
• Updated: 12/Dec/22 18:11
• Resolved: 02/Jul/20 04:58

Description

I'm in the process of migrating from Spark 2.4.x to Spark 3.0.0 and I'm noticing a behaviour change in a particular aggregation we're doing, and I think I've tracked it down to how Spark is now treating nullable properties within the column being grouped by.
 
Here's a simple test I've been able to set up to repro it:
 

case class B(c: Option[Double])
case class A(b: Option[B])
val df = Seq(
A(None),
A(Some(B(None))),
A(Some(B(Some(1.0))))
).toDF
val res = df.groupBy("b").agg(count("*"))

Spark 2.4.6 has the expected result:

> res.show
+-----+--------+
|    b|count(1)|
+-----+--------+
|   []|       1|
| null|       1|
|[1.0]|       1|
+-----+--------+

> res.collect.foreach(println)
[[null],1]
[null,1]
[[1.0],1]

But Spark 3.0.0 has an unexpected result:

> res.show
+-----+--------+
|    b|count(1)|
+-----+--------+
|   []|       2|
|[1.0]|       1|
+-----+--------+

> res.collect.foreach(println)
[[null],2]
[[1.0],1]

Notice how it has keyed one of the values in be as `[null]`; that is, an instance of B with a null value for the `c` property instead of a null for the overall value itself.

Is this an intended change?

Issue Links

• relates to: SPARK-26448 retain the difference between 0.0 and -0.0
• links to: [Github] Pull Request #28962 (viirya)
• links to: [Github] Pull Request #28962 (viirya)