peter-toth commented on code in PR #37525:
URL: https://github.com/apache/spark/pull/37525#discussion_r1070949153
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sql/core/src/main/scala/org/apache/spark/sql/execution/AliasAwareOutputExpression.scala:
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@@ -16,24 +16,53 @@
*/
package org.apache.spark.sql.execution
-import org.apache.spark.sql.catalyst.expressions.{Alias, Expression,
NamedExpression, SortOrder}
-import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning,
Partitioning, PartitioningCollection, UnknownPartitioning}
+import scala.collection.mutable
+
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute,
Expression, NamedExpression, SortOrder}
+import org.apache.spark.sql.catalyst.plans.physical.{Partitioning,
PartitioningCollection, UnknownPartitioning}
+import org.apache.spark.sql.internal.SQLConf
/**
* A trait that provides functionality to handle aliases in the
`outputExpressions`.
*/
trait AliasAwareOutputExpression extends UnaryExecNode {
protected def outputExpressions: Seq[NamedExpression]
- private lazy val aliasMap = outputExpressions.collect {
- case a @ Alias(child, _) => child.canonicalized -> a.toAttribute
- }.toMap
+ private lazy val aliasMap = {
+ val aliases = mutable.Map[Expression, mutable.ListBuffer[Attribute]]()
+ // Add aliases to the map. If multiple alias is defined for a source
attribute then add all.
+ outputExpressions.foreach {
+ case a @ Alias(child, _) =>
+ // This prepend is needed to make the first element of the
`ListBuffer` point to the last
+ // occurrence of an aliased child. This is to keep the previous
behavior:
+ // - when we return `Partitioning`s in `outputPartitioning()`, the
first should be same as
+ // it was previously
+ // - when we return a `SortOrder` in `outputOrdering()`, it should be
should be same as
+ // previously
+ a.toAttribute +=: aliases.getOrElseUpdate(child.canonicalized,
mutable.ListBuffer.empty)
+ case _ =>
+ }
+ // Append identity mapping of an attribute to the map if both the
attribute and its aliased
+ // version can be found in `outputExpressions`.
+ outputExpressions.foreach {
+ case a: Attribute if aliases.contains(a.canonicalized) =>
aliases(a.canonicalized) += a
+ case _ =>
+ }
+ aliases
+ }
protected def hasAlias: Boolean = aliasMap.nonEmpty
- protected def normalizeExpression(exp: Expression): Expression = {
+ // This function returns a limited number of alternatives to mapped `exp`.
+ protected def normalizeExpression(exp: Expression): Seq[Expression] = {
+ exp.multiTransform {
+ case e: Expression if aliasMap.contains(e.canonicalized) =>
aliasMap(e.canonicalized).toSeq
Review Comment:
> @peter-toth do you agree that it's better to let the caller decide if the
original expr should be included or not?
Well, yes, that would make the code of `multiTransform` much simpler. But
the construction of `exprAliasMap` would become the burden of the caller. (I.e.
the caller need to identify if the `from` expression in a `from` -> `to`
mapping contais any other `from` expression and put the `from -> to` and the
`from -> from` mappings to the separate `exprAliasMap` map.)
> It seems currently the framework always include the original expr.
That's right, currently the original expr is always included and the
traversal/transformation continues with its children. But if nothing is
transformed under the original expression then the original is not included in
the final result. Details here:
https://github.com/apache/spark/pull/38034#discussion_r1070234296
My initial idea behind of this "automatic traversal/transformation
continuation" was that the `rule` is a partial function which can define
complex mappings possibly with conditional logic, which a simple map can't do.
So I wasn't sure that we can expect to caller to write `case` statements
that need to return the original expression too if other `case` statements can
transform any of the original expressions descendants...
Although, this is not an issue in our case as we define the `rule` based on
simple alias maps.
If we want to keep that "automatic traversal/transformation continuation"
logic then we could define the `rule` parameter as `PartialFunction[BaseType,
(Stream[BaseType], Continuation)]` (or maybe as `PartialFunction[BaseType,
Seq[(BaseType, Continuation)]]`) to let the caller to choose the from 3
different`Continuation` enum elements like `ALWAYS`, `AUTO` or `NEVER`.
So we could either define our multitransform:
```
input.multiTransform {
case e if aliasMap.contains(e) => exprAliasMap(e) -> AUTO
}
```
or
```
input.multiTransform {
case e if exprAliasMap.contains(e) => exprAliasMap(e) -> ALWAYS
case e if attrAliasMap.contains(e) => attrAliasMap(e) -> NEVER
}
```
or
```
input.multiTransform {
case e if exprAliasMap.contains(e) => (e +: exprAliasMap(e)) -> NEVER
case e if attrAliasMap.contains(e) => attrAliasMap(e) -> NEVER
}
```
Seems like we need only `AUTO` and `NEVER` so probably we just need a
boolean flag instead of the enum...
Anyways, I hope you agree that `multiTransform` is useful and efficient
helper function but I'm not sure how general purpose swiss army knife we want
to make it.
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