Kimahriman commented on a change in pull request #33040:
URL: https://github.com/apache/spark/pull/33040#discussion_r657328398
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveUnion.scala
##########
@@ -20,137 +20,66 @@ package org.apache.spark.sql.catalyst.analysis
import scala.collection.mutable
import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.optimizer.{CombineUnions,
OptimizeUpdateFields}
+import org.apache.spark.sql.catalyst.optimizer.{CombineUnions}
import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project,
Union}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.catalyst.trees.TreePattern.UNION
import org.apache.spark.sql.errors.QueryCompilationErrors
import org.apache.spark.sql.types._
import org.apache.spark.sql.util.SchemaUtils
-import org.apache.spark.unsafe.types.UTF8String
/**
* Resolves different children of Union to a common set of columns.
*/
object ResolveUnion extends Rule[LogicalPlan] {
/**
- * This method sorts columns recursively in a struct expression based on
column names.
+ * Adds missing fields recursively into given `col` expression, based on the
expected struct
+ * fields from merging the two schemas. This is called by
`compareAndAddFields` when we find two
+ * struct columns with same name but different nested fields. This method
will recursively
+ * return a new struct with all of the expected fields, adding null values
when `col` doesn't
+ * already contain them. Currently we don't support merging structs nested
inside of arrays
+ * or maps.
*/
- private def sortStructFields(expr: Expression): Expression = {
- val existingExprs =
expr.dataType.asInstanceOf[StructType].fieldNames.zipWithIndex.map {
- case (name, i) =>
- val fieldExpr = GetStructField(KnownNotNull(expr), i)
- if (fieldExpr.dataType.isInstanceOf[StructType]) {
- (name, sortStructFields(fieldExpr))
- } else {
- (name, fieldExpr)
- }
- }.sortBy(_._1).flatMap(pair => Seq(Literal(pair._1), pair._2))
-
- val newExpr = CreateNamedStruct(existingExprs)
- if (expr.nullable) {
- If(IsNull(expr), Literal(null, newExpr.dataType), newExpr)
- } else {
- newExpr
- }
- }
-
- /**
- * Assumes input expressions are field expression of `CreateNamedStruct`.
This method
- * sorts the expressions based on field names.
- */
- private def sortFieldExprs(fieldExprs: Seq[Expression]): Seq[Expression] = {
- fieldExprs.grouped(2).map { e =>
- Seq(e.head, e.last)
- }.toSeq.sortBy { pair =>
- assert(pair.head.isInstanceOf[Literal])
- pair.head.eval().asInstanceOf[UTF8String].toString
- }.flatten
- }
-
- /**
- * This helper method sorts fields in a `UpdateFields` expression by field
name.
- */
- private def sortStructFieldsInWithFields(expr: Expression): Expression =
expr transformUp {
- case u: UpdateFields if u.resolved =>
- u.evalExpr match {
- case i @ If(IsNull(_), _, CreateNamedStruct(fieldExprs)) =>
- val sorted = sortFieldExprs(fieldExprs)
- val newStruct = CreateNamedStruct(sorted)
- i.copy(trueValue = Literal(null, newStruct.dataType), falseValue =
newStruct)
- case CreateNamedStruct(fieldExprs) =>
- val sorted = sortFieldExprs(fieldExprs)
- val newStruct = CreateNamedStruct(sorted)
- newStruct
- case other =>
- throw new IllegalStateException(s"`UpdateFields` has incorrect
expression: $other. " +
- "Please file a bug report with this error message, stack trace,
and the query.")
- }
- }
-
- /**
- * Adds missing fields recursively into given `col` expression, based on the
target `StructType`.
- * This is called by `compareAndAddFields` when we find two struct columns
with same name but
- * different nested fields. This method will find out the missing nested
fields from `col` to
- * `target` struct and add these missing nested fields. Currently we don't
support finding out
- * missing nested fields of struct nested in array or struct nested in map.
- */
- private def addFields(col: NamedExpression, target: StructType): Expression
= {
+ private def addFields(col: Expression, targetType: StructType): Expression =
{
assert(col.dataType.isInstanceOf[StructType], "Only support StructType.")
val resolver = conf.resolver
- val missingFieldsOpt =
- StructType.findMissingFields(col.dataType.asInstanceOf[StructType],
target, resolver)
-
- // We need to sort columns in result, because we might add another column
in other side.
- // E.g., we want to union two structs "a int, b long" and "a int, c
string".
- // If we don't sort, we will have "a int, b long, c string" and
- // "a int, c string, b long", which are not compatible.
- if (missingFieldsOpt.isEmpty) {
- sortStructFields(col)
- } else {
- missingFieldsOpt.map { s =>
- val struct = addFieldsInto(col, s.fields)
- // Combines `WithFields`s to reduce expression tree.
- val reducedStruct =
struct.transformUp(OptimizeUpdateFields.optimizeUpdateFields)
- val sorted = sortStructFieldsInWithFields(reducedStruct)
- sorted
- }.get
+ val colType = col.dataType.asInstanceOf[StructType]
+
+ val newStructFields = mutable.ArrayBuffer.empty[Expression]
+
+ val targetStructFields = targetType.fields.foreach { expectedField =>
+ val currentField = colType.fields.find(f => resolver(f.name,
expectedField.name))
+
+ val newExpression = (currentField, expectedField.dataType) match {
+ case (Some(cf), expectedType: StructType) if
cf.dataType.isInstanceOf[StructType] =>
+ val extractedValue = ExtractValue(col, Literal(cf.name), resolver)
+ val combinedStruct = addFields(extractedValue, expectedType)
+ if (extractedValue.nullable) {
+ If(IsNull(extractedValue),
+ Literal(null, combinedStruct.dataType),
+ combinedStruct)
+ } else {
+ combinedStruct
+ }
+ case (Some(cf), _) =>
+ ExtractValue(col, Literal(cf.name), resolver)
+ case (None, expectedType) =>
+ Literal(null, expectedType)
+ }
+ newStructFields ++= Literal(expectedField.name) :: newExpression :: Nil
}
- }
- /**
- * Adds missing fields recursively into given `col` expression. The missing
fields are given
- * in `fields`. For example, given `col` as "z struct<z:int, y:int>, x int",
and `fields` is
- * "z struct<w:long>, w string". This method will add a nested `z.w` field
and a top-level
- * `w` field to `col` and fill null values for them. Note that because we
might also add missing
- * fields at other side of Union, we must make sure corresponding attributes
at two sides have
- * same field order in structs, so when we adding missing fields, we will
sort the fields based on
- * field names. So the data type of returned expression will be
- * "w string, x int, z struct<w:long, y:int, z:int>".
- */
- private def addFieldsInto(
- col: Expression,
- fields: Seq[StructField]): Expression = {
- fields.foldLeft(col) { case (currCol, field) =>
- field.dataType match {
- case st: StructType =>
- val resolver = conf.resolver
- val colField = currCol.dataType.asInstanceOf[StructType]
- .find(f => resolver(f.name, field.name))
- if (colField.isEmpty) {
- // The whole struct is missing. Add a null.
- UpdateFields(currCol, field.name, Literal(null, st))
- } else {
- UpdateFields(currCol, field.name,
- addFieldsInto(ExtractValue(currCol, Literal(field.name),
resolver), st.fields))
- }
- case dt =>
- UpdateFields(currCol, field.name, Literal(null, dt))
+ colType.fields
+ .filter(f => targetType.fields.find(tf => resolver(f.name,
tf.name)).isEmpty)
+ .foreach { f =>
+ newStructFields ++= Literal(f.name) :: ExtractValue(col,
Literal(f.name), resolver) :: Nil
Review comment:
And then leftChild is created from the fields in rightChild which
already has all the fields as that point, which is the left fields and then the
right fields
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