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[SPARK-32163][SQL][3.0] Nested pruning should work even with cosmetic variations #29027

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[SPARK-32163][SQL][3.0] Nested pruning should work even with cosmetic variations #29027

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11 changes: 8 additions & 3 deletions ...atalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NestedColumnAliasing.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -118,10 +118,12 @@ object NestedColumnAliasing {
case _ => false
}

// Note that when we group by extractors with their references, we should remove
// cosmetic variations.
val exclusiveAttrSet = AttributeSet(exclusiveAttrs ++ otherRootReferences)
val aliasSub = nestedFieldReferences.asInstanceOf[Seq[ExtractValue]]
.filter(!_.references.subsetOf(exclusiveAttrSet))
.groupBy(_.references.head)
.groupBy(_.references.head.canonicalized.asInstanceOf[Attribute])
.flatMap { case (attr, nestedFields: Seq[ExtractValue]) =>
// Each expression can contain multiple nested fields.
// Note that we keep the original names to deliver to parquet in a case-sensitive way.
Expand All @@ -132,9 +134,12 @@ object NestedColumnAliasing {

// If all nested fields of `attr` are used, we don't need to introduce new aliases.
// By default, ColumnPruning rule uses `attr` already.
// Note that we need to remove cosmetic variations first, so we only count a
// nested field once.
if (nestedFieldToAlias.nonEmpty &&
nestedFieldToAlias
.map { case (nestedField, _) => totalFieldNum(nestedField.dataType) }
nestedFields.map(_.canonicalized)
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@dongjoon-hyun dongjoon-hyun Jul 7, 2020

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Is this the main difference from 3.0, dedupNestedFields -> nestedFields?

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@viirya viirya Jul 7, 2020

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Yeah, for the change in NestedColumnAliasing. Another difference is test. One test in master branch cannot pass in branch-3.0.

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@dongjoon-hyun dongjoon-hyun Jul 7, 2020

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Yes. Test part looked correct because it's a subset. For this part, it looks a little different and needs more validation.

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@viirya viirya Jul 7, 2020

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Thanks for check. Yes, there is a bit difference between master and branch-3.0 here. So no dedupNestedFields in branch-3.0.

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@maropu maropu Jul 7, 2020

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Ah, I missed this part. I think the added test still fails if we don't have this change. Is this correct?

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@dongjoon-hyun dongjoon-hyun Jul 7, 2020 •
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Yes. It does. The new test case still validate this patch in terms of that part.

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@viirya viirya Jul 7, 2020

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Yes, this test fails in current branch-3.0.

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@maropu maropu Jul 7, 2020

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Nice.

.distinct
.map { nestedField => totalFieldNum(nestedField.dataType) }
.sum < totalFieldNum(attr.dataType)) {
Some(attr.exprId -> nestedFieldToAlias)
} else {
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12 changes: 12 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala
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Expand Up @@ -301,6 +301,18 @@ abstract class SchemaPruningSuite
checkAnswer(query, Row("Y.", 1) :: Row("X.", 1) :: Row(null, 2) :: Row(null, 2) :: Nil)
}

testSchemaPruning("SPARK-32163: nested pruning should work even with cosmetic variations") {
withTempView("contact_alias") {
sql("select * from contacts")
.select(explode(col("friends.first")), col("friends"))
.createOrReplaceTempView("contact_alias")

val query = sql("select friends.middle, col from contact_alias")
checkScan(query, "struct<friends:array<struct<first:string,middle:string>>>")
checkAnswer(query, Row(Array("Z."), "Susan") :: Nil)
}
}

protected def testSchemaPruning(testName: String)(testThunk: => Unit): Unit = {
test(s"Spark vectorized reader - without partition data column - $testName") {
withSQLConf(vectorizedReaderEnabledKey -> "true") {
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