Github user kiszk commented on a diff in the pull request:
https://github.com/apache/spark/pull/22375#discussion_r219397495
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelperSuite.scala
---
@@ -35,6 +36,13 @@ class ExpressionEvalHelperSuite extends SparkFunSuite
with ExpressionEvalHelper
val e = intercept[RuntimeException] {
checkEvaluation(BadCodegenExpression(), 10) }
assert(e.getMessage.contains("some_variable"))
}
+
+ test("SPARK-25388: checkEvaluation should fail if nullable in DataType
is incorrect") {
+ val e = intercept[RuntimeException] {
+ checkEvaluation(MapIncorrectDataTypeExpression(), Map(3 -> 7, 6 ->
null))
--- End diff --
The your first is correct since this patch addresses only codegen-on case.
We can add another code to address codegen-off case.
Regarding the your second point, have we ever distingished a wrong output
from a bad written UT when we defect the difference between `expression` and
`expected`. I think that the distinguishment is nice to have, but not mandatory
to have.
I have one question about your approach:
```
assert(containsNull(expected) && isNullable(expression.dataType))
```
Since the above two conditions evaluates `expected` and `expression`
independently, how this works for the following case? I think that the
assertion would be passed
```
expression:
dataType = StructType(ArrayType(IntegerType, false), ArrayType(IntegerType,
true))
Struct(Array(0, null), Array(1, 0))
expected:
Struct(Array(0, 0), Array(1, null))
```
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