Kimahriman commented on a change in pull request #32338:
URL: https://github.com/apache/spark/pull/32338#discussion_r619831036
##########
File path:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeWithFieldsSuite.scala
##########
@@ -99,7 +99,7 @@ class OptimizeWithFieldsSuite extends PlanTest {
val correctAnswer = testRelation
.select(
Alias(UpdateFields('a, WithField("b1", Literal(5)) :: Nil), "out1")(),
- Alias(UpdateFields('a, WithField("B1", Literal(5)) :: Nil), "out2")())
+ Alias(UpdateFields('a, WithField("b1", Literal(5)) :: Nil), "out2")())
Review comment:
One result is that for case-insensitive cases, the first casing seen for
a field is maintained, rather than the last one. If this isn't what we want, I
can update it to keep the last casing seen
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
##########
@@ -1686,6 +1686,61 @@ class ColumnExpressionSuite extends QueryTest with
SharedSparkSession {
StructType(Seq(StructField("a", IntegerType, nullable = true))))
}
+ test("SPARK-35213: chained withField operations should have correct schema
for new columns") {
+ val df = spark.createDataFrame(
+ sparkContext.parallelize(Row(null) :: Nil),
+ StructType(Seq(StructField("data", NullType))))
Review comment:
Is it possible to just create an empty dataframe with no columns in
Scala? I mostly operate and python and can just do `spark.createDataFrame([[]])`
##########
File path:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeWithFieldsSuite.scala
##########
@@ -126,4 +126,25 @@ class OptimizeWithFieldsSuite extends PlanTest {
comparePlans(optimized, correctAnswer)
}
}
+
+ test("SPARK-35213: ensure optimize WithFields maintains correct struct
ordering") {
+ val originalQuery = testRelation
+ .select(
+ Alias(UpdateFields('a,
+ WithField("a1", Literal(3)) ::
+ WithField("b1", Literal(4)) ::
+ WithField("a1", Literal(5)) ::
+ Nil), "out")())
+
+ val optimized = Optimize.execute(originalQuery.analyze)
+ val correctAnswer = testRelation
+ .select(
+ Alias(UpdateFields('a,
+ WithField("a1", Literal(5)) ::
+ WithField("b1", Literal(4)) ::
+ Nil), "out")())
+ .analyze
+
+ comparePlans(optimized, correctAnswer)
+ }
Review comment:
This was just to sanity check the WithField order does actually stay the
same, the tests on the Column Suite show how it can actually give you an
incorrect schema. I don't fully know how a schema is determined (what part of
the planning phase)
##########
File path:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeWithFieldsSuite.scala
##########
@@ -126,4 +126,25 @@ class OptimizeWithFieldsSuite extends PlanTest {
comparePlans(optimized, correctAnswer)
}
}
+
+ test("SPARK-35213: ensure optimize WithFields maintains correct struct
ordering") {
Review comment:
done
##########
File path:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeWithFieldsSuite.scala
##########
@@ -99,7 +99,7 @@ class OptimizeWithFieldsSuite extends PlanTest {
val correctAnswer = testRelation
.select(
Alias(UpdateFields('a, WithField("b1", Literal(5)) :: Nil), "out1")(),
- Alias(UpdateFields('a, WithField("B1", Literal(5)) :: Nil), "out2")())
+ Alias(UpdateFields('a, WithField("b1", Literal(5)) :: Nil), "out2")())
Review comment:
Changed it to keep the last casing instead
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
##########
@@ -1686,6 +1686,61 @@ class ColumnExpressionSuite extends QueryTest with
SharedSparkSession {
StructType(Seq(StructField("a", IntegerType, nullable = true))))
}
+ test("SPARK-35213: chained withField operations should have correct schema
for new columns") {
+ val df = spark.createDataFrame(
+ sparkContext.parallelize(Row(null) :: Nil),
+ StructType(Seq(StructField("data", NullType))))
+
+ checkAnswer(
+ df.withColumn("data", struct()
+ .withField("a", struct())
+ .withField("b", struct())
+ .withField("a.aa", lit("aa1"))
+ .withField("b.ba", lit("ba1"))
+ .withField("a.ab", lit("ab1"))),
+ Row(Row(Row("aa1", "ab1"), Row("ba1"))) :: Nil,
+ StructType(Seq(
+ StructField("data", StructType(Seq(
+ StructField("a", StructType(Seq(
+ StructField("aa", StringType, nullable = false),
+ StructField("ab", StringType, nullable = false)
+ )), nullable = false),
+ StructField("b", StructType(Seq(
+ StructField("ba", StringType, nullable = false)
+ )), nullable = false)
+ )), nullable = false)
Review comment:
Yeah it's kinda verbose, but I feel like for complicated things the
objects are easier to understand than the DDL strings, especially with structs.
Wasn't sure if there was an easier way to not have to explicitly mark
everything as not nullable at least
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