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

["Jason Moore (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-32136?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jason Moore updated SPARK-32136:
--------------------------------
    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:
 

{code:scala}
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("*"))
{code}

Spark 2.4.6 has the expected result:

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

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

But Spark 3.0.0 has an unexpected result:

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

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

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?

  was:
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:
 

{code:scala}
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("*"))
{code}

Spark 2.4.6 has the expected result:

{noformat}
> res.show
+-----+--------+
|    b|count(1)|
+-----+--------+
|   []|       1|
| null|       1|
|[1.0]|       1|
+-----+--------+
> res.collect.foreach(println)
[[null],1]
[null,1]
[[1.0],1]
{noformat}

But Spark 3.0.0 has an unexpected result:

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

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

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?


> Spark producing incorrect groupBy results when key is a struct with nullable properties
> ---------------------------------------------------------------------------------------
>
>                 Key: SPARK-32136
>                 URL: https://issues.apache.org/jira/browse/SPARK-32136
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 3.0.0
>            Reporter: Jason Moore
>            Priority: Major
>
> 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:
>  
> {code:scala}
> 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("*"))
> {code}
> Spark 2.4.6 has the expected result:
> {noformat}
> > res.show
> +-----+--------+
> |    b|count(1)|
> +-----+--------+
> |   []|       1|
> | null|       1|
> |[1.0]|       1|
> +-----+--------+
> > res.collect.foreach(println)
> [[null],1]
> [null,1]
> [[1.0],1]
> {noformat}
> But Spark 3.0.0 has an unexpected result:
> {noformat}
> > res.show
> +-----+--------+
> |    b|count(1)|
> +-----+--------+
> |   []|       2|
> |[1.0]|       1|
> +-----+--------+
> > res.collect.foreach(println)
> [[null],2]
> [[1.0],1]
> {noformat}
> 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?



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