petern48 commented on code in PR #2447:
URL: https://github.com/apache/sedona/pull/2447#discussion_r2462357514
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spark/common/src/test/scala/org/apache/sedona/sql/SpatialJoinSuite.scala:
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@@ -268,6 +268,15 @@ class SpatialJoinSuite extends TestBaseScala with
TableDrivenPropertyChecks {
assert(resultRows.isEmpty)
}
}
+
+ it("ST_Distance join involving empty geometries should evaluate to false")
{
+ val result1 = sparkSession.sql(
Review Comment:
I know, this *technically* isn't a spatial join (so yeah, maybe I can change
the test name), but isn't this sufficient for what we want to test? If I were
to write a test for this behavior that **is technically** a spatial join. I
would join an existing df with a table with all empty geometries. That would be
equivalent to just testing against a constant empty geometry, wouldn't it?
Doing this was just more convenient since an empty geom df didn't already exist.
Personally, I didn't find a need to test distance joins. We're just
modifying the behavior of a predicate. This shouldn't change anything in the
spatial join outside of whether the predicate evaluates to true or not.
`null < 1` -> `null`. And a result of `null` is treated as `False` for
joining purposes. It evaluates to something successfully and doesn't error.
Should be simple as that, right? I don't see any other way for things to fail.
If you disagree, is there a certain case you'd be concerned about? Or do you
have a suggestion for how to test instead?
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