[SPARK-32638][SQL][FOLLOWUP] Move the plan rewriting methods to QueryPlan #29643
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@@ -17,6 +17,8 @@ | |
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| package org.apache.spark.sql.catalyst.plans | ||
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| import scala.collection.mutable | ||
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| import org.apache.spark.sql.AnalysisException | ||
| import org.apache.spark.sql.catalyst.expressions._ | ||
| import org.apache.spark.sql.catalyst.trees.{CurrentOrigin, TreeNode, TreeNodeTag} | ||
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@@ -168,6 +170,89 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]] extends TreeNode[PlanT | |
| }.toSeq | ||
| } | ||
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| /** | ||
| * A variant of `transformUp`, which takes care of the case that the rule replaces a plan node | ||
| * with a new one that has different output expr IDs, by updating the attribute references in | ||
| * the parent nodes accordingly. | ||
| * | ||
| * @param rule the function to transform plan nodes, and return new nodes with attributes mapping | ||
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There was a problem hiding this comment. Just a question. Why we need to return the attribute mapping from old to new? Can we just detect if the output of new plan is different to old plan, then create the mapping inside There was a problem hiding this comment. Because that's too hard. For example, |
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| * from old attributes to new attributes. The attribute mapping will be used to | ||
| * rewrite attribute references in the parent nodes. | ||
| * @param skipCond a boolean condition to indicate if we can skip transforming a plan node to save | ||
| * time. | ||
| */ | ||
| def transformUpWithNewOutput( | ||
| rule: PartialFunction[PlanType, (PlanType, Seq[(Attribute, Attribute)])], | ||
| skipCond: PlanType => Boolean = _ => false): PlanType = { | ||
| def rewrite(plan: PlanType): (PlanType, Seq[(Attribute, Attribute)]) = { | ||
| if (skipCond(plan)) { | ||
| plan -> Nil | ||
| } else { | ||
| val attrMapping = new mutable.ArrayBuffer[(Attribute, Attribute)]() | ||
| var newPlan = plan.mapChildren { child => | ||
| val (newChild, childAttrMapping) = rewrite(child) | ||
| attrMapping ++= childAttrMapping | ||
| newChild | ||
| } | ||
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| val attrMappingForCurrentPlan = attrMapping.filter { | ||
| // The `attrMappingForCurrentPlan` is used to replace the attributes of the | ||
| // current `plan`, so the `oldAttr` must be part of `plan.references`. | ||
| case (oldAttr, _) => plan.references.contains(oldAttr) | ||
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There was a problem hiding this comment. Shall we skip if child is not resolved ? Although, it would break the one shot rewrite idea. The reason is, call There was a problem hiding this comment. Can we add a base trait for plans that override There was a problem hiding this comment. Ideally a plan should determine its reference by its expressions, but not by its child output attributes. There was a problem hiding this comment. add a new base trait sounds good There was a problem hiding this comment. I send a pr #40154 for it |
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| } | ||
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| val (planAfterRule, newAttrMapping) = CurrentOrigin.withOrigin(origin) { | ||
| rule.applyOrElse(newPlan, (plan: PlanType) => plan -> Nil) | ||
| } | ||
| newPlan = planAfterRule | ||
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| if (attrMappingForCurrentPlan.nonEmpty) { | ||
| assert(!attrMappingForCurrentPlan.groupBy(_._1.exprId) | ||
| .exists(_._2.map(_._2.exprId).distinct.length > 1), | ||
| "Found duplicate rewrite attributes") | ||
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| val attributeRewrites = AttributeMap(attrMappingForCurrentPlan) | ||
| // Using attrMapping from the children plans to rewrite their parent node. | ||
| // Note that we shouldn't rewrite a node using attrMapping from its sibling nodes. | ||
| newPlan = newPlan.transformExpressions { | ||
| case a: AttributeReference => | ||
| updateAttr(a, attributeRewrites) | ||
| case pe: PlanExpression[PlanType] => | ||
| pe.withNewPlan(updateOuterReferencesInSubquery(pe.plan, attributeRewrites)) | ||
| } | ||
| } | ||
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| attrMapping ++= newAttrMapping.filter { | ||
| case (a1, a2) => a1.exprId != a2.exprId | ||
| } | ||
| newPlan -> attrMapping | ||
| } | ||
| } | ||
| rewrite(this)._1 | ||
| } | ||
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| private def updateAttr(attr: Attribute, attrMap: AttributeMap[Attribute]): Attribute = { | ||
| val exprId = attrMap.getOrElse(attr, attr).exprId | ||
| attr.withExprId(exprId) | ||
| } | ||
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| /** | ||
| * The outer plan may have old references and the function below updates the | ||
| * outer references to refer to the new attributes. | ||
| */ | ||
| private def updateOuterReferencesInSubquery( | ||
| plan: PlanType, | ||
| attrMap: AttributeMap[Attribute]): PlanType = { | ||
| plan.transformDown { case currentFragment => | ||
| currentFragment.transformExpressions { | ||
| case OuterReference(a: AttributeReference) => | ||
| OuterReference(updateAttr(a, attrMap)) | ||
| case pe: PlanExpression[PlanType] => | ||
| pe.withNewPlan(updateOuterReferencesInSubquery(pe.plan, attrMap)) | ||
| } | ||
| } | ||
| } | ||
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| lazy val schema: StructType = StructType.fromAttributes(output) | ||
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| /** Returns the output schema in the tree format. */ | ||
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This means that we won't replace attributes in an unresolved plan, which is not sufficient. See the updated test: https://github.com/apache/spark/pull/29643/files#diff-01ecdd038c5c2f53f38118912210fef8R1425
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Good catch! In this unresolved plan, there might be other resolved and replaced attributes.
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Ah, I see. Nice catch.