MaxGekk commented on code in PR #49658:
URL: https://github.com/apache/spark/pull/49658#discussion_r1939251554
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/NameScope.scala:
##########
@@ -272,122 +394,74 @@ class NameScopeStack extends SQLConfHelper {
}
/**
- * Completely overwrite the top scope state with a named plan output.
+ * Completely overwrite the top scope state with operator `output`.
*
- * See [[NameScope.update]] for more details.
- */
- def overwriteTop(name: String, attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope.update(name, attributes)
-
- stack.pop()
- stack.push(newScope)
- }
-
- /**
- * Completely overwrite the top scope state with an unnamed plan output.
+ * This method is called by the [[Resolver]] when we've calculated the
output of an operator that
+ * is being resolved. The new output is calculated based on the outputs of
operator's children.
+ *
+ * Example for [[SubqueryAlias]], here we rewrite the top [[NameScope]]'s
attributes to prepend
+ * subquery qualifier to their names:
*
- * See [[NameScope.+=]] for more details.
+ * {{{
+ * val qualifier = sa.identifier.qualifier :+ sa.alias
+ * scope.overwriteTop(scope.output.map(attribute =>
attribute.withQualifier(qualifier)))
+ * }}}
+ *
+ * Trivially, we would call this method for every operator in the query plan,
+ * however some operators just propagate the output of their children
without any changes, so
+ * we can omit this call for them (e.g. [[Filter]]).
+ *
+ * This method should be preferred over [[withNewScope]].
*/
- def overwriteTop(attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope += attributes
+ def overwriteTop(output: Seq[Attribute]): Unit = {
+ val newScope = new NameScope(output)
stack.pop()
stack.push(newScope)
}
/**
- * Execute `body` in a context of a fresh scope. It's used during the
[[Project]] or the
- * [[Aggregate]] resolution to avoid calling [[push]] and [[pop]] explicitly.
+ * Execute `body` in a context of a fresh scope.
+ *
+ * This method is called by the [[Resolver]] before recursing into the
operator's child
+ * resolution _only_ in cases where a fresh scope is required.
+ *
+ * For esample, [[Project]] or [[Aggregate]] introduce their own scopes
semantically, so that a
+ * lower resolution can lookup correlated names:
+ *
+ * {{{
+ * CREATE TABLE IF NOT EXISTS t1 (col1 INT, col2 STRING);
+ * CREATE TABLE IF NOT EXISTS t2 (col1 INT, col2 STRING);
+ *
+ * -- Here we need a scope for the upper [[Project]], and a separate scope
for the correlated
+ * -- subquery, because its [[Filter]] need to lookup `t1.col1` from the
upper scope.
+ * -- Those scopes have to be indenepdent to avoid polluting each other's
attributes.
+ * SELECT col1, (SELECT col2 FROM t2 WHERE t2.col1 == t1.col1 LIMIT 1) FROM
t1;
+ * }}}
+ *
+ * Also, we need separate scopes for the operators with multiple children,
so that the next
+ * child's resolution woudn't try to work with the data from it's sibling's
scope, to avoid
Review Comment:
```suggestion
* child's resolution wouldn't try to work with the data from it's
sibling's scope, to avoid
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/NameTarget.scala:
##########
@@ -23,59 +23,76 @@ import
org.apache.spark.sql.catalyst.util.StringUtils.orderSuggestedIdentifiersB
import org.apache.spark.sql.errors.QueryCompilationErrors
/**
- * Class that represents results of name resolution or star expansion. It
encapsulates:
- * - `candidates` - A list of candidates that are possible matches for a
given name.
- * - `aliasName` - If the candidates size is 1 and it's type is
`ExtractValue` (which means that
- * it's a recursive type), then the `aliasName` should be the name with
which the candidate is
- * aliased. Otherwise, `aliasName` should be `None`.
- * - `allAttributes` - A list of all attributes which is used to generate
suggestions for
- * unresolved column error.
+ * [[NameTarget]] is a result of a multipart name resolution of the
+ * [[NameScope.resolveMultipartName]].
*
- * Example:
+ * Attribute resolution:
*
- * - Attribute resolution:
- * {{{ SELECT col1 FROM VALUES (1); }}} will have a [[NameTarget]] with a
single candidate `col1`.
- * `aliasName` would be `None` in this case because the column is not of
recursive type.
+ * {{{
+ * -- [[NameTarget]] with a single candidate `col1`. `aliasName` is be `None`
in this case because
+ * -- the name is not a field/value/item of some recursive type.
+ * SELECT col1 FROM VALUES (1);
+ * }}}
*
- * - Recursive attribute resolution:
- * {{{ SELECT col1.col1 FROM VALUES(STRUCT(1,2), 3) }}} will have a
[[NameTarget]] with a
- * single candidate `col1` and an `aliasName` of `Some("col1")`.
+ * Attribute resolution ambiguity:
+ *
+ * {{{
+ * -- [[NameTarget]] with candidates `col1`, `col1`. [[pickCandidate]] will
throw
+ * -- `AMBIGUOUS_REFERENCE`.
+ * SELECT col1 FROM VALUES (1) t1, VALUES (2) t2;
+ * }}}
+ *
+ * Struct field resolution:
+ *
+ * {{{
+ * -- [[NameTarget]] with a single candidate `GetStructField(col1, "field1")`.
`aliasName` is
+ * -- `Some("col1")`, since here we extract a field of a struct.
+ * SELECT col1.field1 FROM VALUES (named_struct('field1', 1), 3);
+ * }}}
+ *
+ * @param candidates A list of candidates that are possible matches for a
given name.
+ * @param aliasName If the candidates size is 1 and it's type is
[[ExtractValue]] (which means that
+ * it's a field/value/item from a recursive type), then the `aliasName`
should be the name with
+ * which the candidate needs to be aliased. Otherwise, `aliasName` is `None`.
+ * @param lateralAttributeReference If the candidate is laterally referencing
another column this
+ * field is populated with that column's attribute.
+ * @param output [[output]] of a [[NameSope]] that produced this
[[NameTarget]]. Used to provide
Review Comment:
Probably, `NameScope`:
```suggestion
* @param output [[output]] of a [[NameScope]] that produced this
[[NameTarget]]. Used to provide
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/Resolver.scala:
##########
@@ -139,63 +168,112 @@ class Resolver(
override def resolve(unresolvedPlan: LogicalPlan): LogicalPlan = {
planLogger.logPlanResolutionEvent(unresolvedPlan, "Unresolved plan")
- throwIfNodeWasResolvedEarlier(unresolvedPlan)
-
val resolvedPlan =
unresolvedPlan match {
+ case unresolvedWith: UnresolvedWith =>
+ resolveWith(unresolvedWith)
case unresolvedProject: Project =>
- resolveProject(unresolvedProject)
+ projectResolver.resolve(unresolvedProject)
case unresolvedFilter: Filter =>
resolveFilter(unresolvedFilter)
+ case unresolvedSubqueryColumnAliases: UnresolvedSubqueryColumnAliases
=>
+ resolveSubqueryColumnAliases(unresolvedSubqueryColumnAliases)
case unresolvedSubqueryAlias: SubqueryAlias =>
resolveSubqueryAlias(unresolvedSubqueryAlias)
+ case unresolvedView: View =>
+ viewResolver.resolve(unresolvedView)
case unresolvedGlobalLimit: GlobalLimit =>
resolveGlobalLimit(unresolvedGlobalLimit)
case unresolvedLocalLimit: LocalLimit =>
resolveLocalLimit(unresolvedLocalLimit)
+ case unresolvedDistinct: Distinct =>
+ resolveDistinct(unresolvedDistinct)
case unresolvedRelation: UnresolvedRelation =>
resolveRelation(unresolvedRelation)
+ case unresolvedCteRelationDef: CTERelationDef =>
+ resolveCteRelationDef(unresolvedCteRelationDef)
case unresolvedInlineTable: UnresolvedInlineTable =>
resolveInlineTable(unresolvedInlineTable)
+ case unresolvedUnion: Union =>
+ unionResolver.resolve(unresolvedUnion)
// See the reason why we have to match both [[LocalRelation]] and
[[ResolvedInlineTable]]
// in the [[resolveInlineTable]] scaladoc
case resolvedInlineTable: ResolvedInlineTable =>
- updateNameScopeWithPlanOutput(resolvedInlineTable)
+ handleLeafOperator(resolvedInlineTable)
case localRelation: LocalRelation =>
- updateNameScopeWithPlanOutput(localRelation)
+ handleLeafOperator(localRelation)
case unresolvedOneRowRelation: OneRowRelation =>
- updateNameScopeWithPlanOutput(unresolvedOneRowRelation)
+ handleLeafOperator(unresolvedOneRowRelation)
case _ =>
tryDelegateResolutionToExtension(unresolvedPlan).getOrElse {
handleUnmatchedOperator(unresolvedPlan)
}
}
- markNodeAsResolved(resolvedPlan)
+ if (resolvedPlan.children.nonEmpty) {
+ val missingInput = resolvedPlan.missingInput
+ if (missingInput.nonEmpty) {
+ withPosition(unresolvedPlan) {
+ throwMissingAttributesError(resolvedPlan, missingInput)
+ }
+ }
+ }
+
+ if (!resolvedPlan.resolved) {
+ throwSinglePassFailedToResolveOperator(resolvedPlan)
+ }
planLogger.logPlanResolution(unresolvedPlan, resolvedPlan)
- resolvedPlan
+ preservePlanIdTag(unresolvedPlan, resolvedPlan)
}
/**
- * [[Project]] introduces a new scope to resolve its subtree and project
list expressions. After
- * those are resolved in the child scope we overwrite current scope with
resolved [[Project]]'s
- * output to expose new names to the parent operators.
+ * [[UnresolvedWith]] contains a list of unresolved CTE definitions, which
are represented by
+ * (name, subquery) pairs, and an actual child query. First we resolve the
CTE definitions
+ * strictly in their declaration order, so they become available for other
lower definitions
+ * (lower both in this WITH clause list and in the plan tree) and for the
[[UnresolvedWith]] child
+ * query. After that, we resolve the child query. Optionally, if this is a
root [[CteScope]],
+ * we return a [[WithCTE]] operator with all the resolved
[[CTERelationDef]]s merged together
+ * from this scope and child scopes. Otherwise, we return the resolved child
query so that
+ * the resolved [[CTERelationDefs]] propagate up and will be merged together
later.
+ *
+ * See [[CteScope]] scaladoc for all the details on how CTEs are resolved.
*/
- private def resolveProject(unresolvedProject: Project): LogicalPlan = {
- val resolvedProject = scopes.withNewScope {
- val resolvedChild = resolve(unresolvedProject.child)
- val resolvedProjectList =
- expressionResolver.resolveProjectList(unresolvedProject.projectList)
- Project(resolvedProjectList, resolvedChild)
+ private def resolveWith(unresolvedWith: UnresolvedWith): LogicalPlan = {
+ val childOutputs = new ArrayBuffer[Seq[Attribute]]
+
+ unresolvedWith.cteRelations.map { cteRelation =>
Review Comment:
Since the lambda doesn't return any result, it is better to use `foreach`:
```suggestion
unresolvedWith.cteRelations.foreach { cteRelation =>
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/Resolver.scala:
##########
@@ -252,36 +371,74 @@ class Resolver(
val resolvedChild = resolve(unresolvedLocalLimit.child)
val resolvedLimitExpr = withPosition(unresolvedLocalLimit) {
- limitExpressionResolver.resolve(unresolvedLocalLimit.limitExpr)
+ expressionResolver.resolveLimitExpression(
+ unresolvedLocalLimit.limitExpr,
+ unresolvedLocalLimit
+ )
}
LocalLimit(resolvedLimitExpr, resolvedChild)
}
+ /**
+ * [[Distinct]] operator doesn't require any speciial resolution.
Review Comment:
```suggestion
* [[Distinct]] operator doesn't require any special resolution.
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/ExpressionResolver.scala:
##########
@@ -288,30 +473,148 @@ class ExpressionResolver(
/**
* [[Literal]] resolution doesn't require any specific resolution logic at
this point.
+ */
+ private def resolveLiteral(literal: Literal): Expression = literal
+
+ /**
+ * The [[GetViewColumnByNameAndOrdinal]] is a special internal expression
that is placed by the
+ * [[SessionCatalog]] in the top [[Project]] operator of the freshly
reconstructed unresolved
+ * view plan. Since the view schema is fixed and persisted in the catalog,
we have to extract
+ * the right attributes from the view plan regardless of the underlying
table schema changes.
+ * [[GetViewColumnByNameAndOrdinal]] contains attribute name and it's
ordinal to perform the
+ * necessary matching. If the matching was not successful, or the number of
matched candidates
+ * differs from the recorded one, we throw an error.
+ *
+ * Example of the correct name matching:
+ *
+ * {{{
+ * CREATE TABLE underlying (col1 INT, col2 STRING);
+ * CREATE VIEW all_columns AS SELECT * FROM underlying;
+ *
+ * -- View plan for the SELECT below will contain a Project node on top with
the following
+ * -- expressions:
+ * -- getviewcolumnbynameandordinal(`spark_catalog`.`default`.`all_columns`,
col1, 0, 1)
+ * -- getviewcolumnbynameandordinal(`spark_catalog`.`default`.`all_columns`,
col2, 0, 1)
Review Comment:
Could you restore camel-cases.
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/NameScope.scala:
##########
@@ -272,122 +394,74 @@ class NameScopeStack extends SQLConfHelper {
}
/**
- * Completely overwrite the top scope state with a named plan output.
+ * Completely overwrite the top scope state with operator `output`.
*
- * See [[NameScope.update]] for more details.
- */
- def overwriteTop(name: String, attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope.update(name, attributes)
-
- stack.pop()
- stack.push(newScope)
- }
-
- /**
- * Completely overwrite the top scope state with an unnamed plan output.
+ * This method is called by the [[Resolver]] when we've calculated the
output of an operator that
+ * is being resolved. The new output is calculated based on the outputs of
operator's children.
+ *
+ * Example for [[SubqueryAlias]], here we rewrite the top [[NameScope]]'s
attributes to prepend
+ * subquery qualifier to their names:
*
- * See [[NameScope.+=]] for more details.
+ * {{{
+ * val qualifier = sa.identifier.qualifier :+ sa.alias
+ * scope.overwriteTop(scope.output.map(attribute =>
attribute.withQualifier(qualifier)))
+ * }}}
+ *
+ * Trivially, we would call this method for every operator in the query plan,
+ * however some operators just propagate the output of their children
without any changes, so
+ * we can omit this call for them (e.g. [[Filter]]).
+ *
+ * This method should be preferred over [[withNewScope]].
*/
- def overwriteTop(attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope += attributes
+ def overwriteTop(output: Seq[Attribute]): Unit = {
+ val newScope = new NameScope(output)
stack.pop()
stack.push(newScope)
}
/**
- * Execute `body` in a context of a fresh scope. It's used during the
[[Project]] or the
- * [[Aggregate]] resolution to avoid calling [[push]] and [[pop]] explicitly.
+ * Execute `body` in a context of a fresh scope.
+ *
+ * This method is called by the [[Resolver]] before recursing into the
operator's child
+ * resolution _only_ in cases where a fresh scope is required.
+ *
+ * For esample, [[Project]] or [[Aggregate]] introduce their own scopes
semantically, so that a
+ * lower resolution can lookup correlated names:
+ *
+ * {{{
+ * CREATE TABLE IF NOT EXISTS t1 (col1 INT, col2 STRING);
+ * CREATE TABLE IF NOT EXISTS t2 (col1 INT, col2 STRING);
+ *
+ * -- Here we need a scope for the upper [[Project]], and a separate scope
for the correlated
+ * -- subquery, because its [[Filter]] need to lookup `t1.col1` from the
upper scope.
+ * -- Those scopes have to be indenepdent to avoid polluting each other's
attributes.
Review Comment:
```suggestion
* -- Those scopes have to be independent to avoid polluting each other's
attributes.
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/ExpressionResolver.scala:
##########
@@ -199,16 +279,97 @@ class ExpressionResolver(
* from the [[Resolver]] during [[Project]] resolution.
*
* The output sequence can be larger than the input sequence due to
[[UnresolvedStar]] expansion.
+ *
+ * @returns The list of resolved expressions along with flags indicating
whether the resolved
+ * project list contains aggregate expressions or attributes (encapsulated in
+ * [[ResolvedProjectList]]) which are used during the further resolution of
the tree.
+ *
+ * The following query:
+ *
+ * {{{ SELECT COUNT(col1), 2 FROM VALUES(1); }}}
+ *
+ * would have a project list with two expressions: `COUNT(col1)` and `2`.
After the resolution it
+ * would return the following result:
+ * ResolvedProjectList(
+ * expressions = [count(col1) as count(col1), 2 AS 2],
+ * hasAggregateExpressions = true, // because it contains `count(col1)` in
the project list
+ * hasAttributes = false // because it doesn't contain any
[[AttributeReference]]s in the
+ * // project list (only under the aggregate
expression, please check
+ * // [[AggregateExpressionResolver]] for more
details).
*/
- def resolveProjectList(unresolvedProjectList: Seq[NamedExpression]):
Seq[NamedExpression] = {
- unresolvedProjectList.flatMap {
+ def resolveProjectList(
+ unresolvedProjectList: Seq[NamedExpression],
+ operator: LogicalPlan): ResolvedProjectList = {
+ val projectListResolutionContext = new ExpressionResolutionContext
+ val resolvedProjectList = unresolvedProjectList.flatMap {
case unresolvedStar: UnresolvedStar =>
resolveStar(unresolvedStar)
case other =>
- Seq(resolveNamedExpression(other, isTopOfProjectList =
true).asInstanceOf[NamedExpression])
+ val (resolvedElement, resolvedElementContext) =
+ resolveExpressionTreeInOperatorImpl(other, operator)
+ projectListResolutionContext.merge(resolvedElementContext)
+ Seq(resolvedElement.asInstanceOf[NamedExpression])
}
+ ResolvedProjectList(
+ expressions = resolvedProjectList,
+ hasAggregateExpressions =
projectListResolutionContext.hasAggregateExpressionsInASubtree,
+ hasAttributes = projectListResolutionContext.hasAttributeInASubtree,
+ hasLateralColumnAlias =
projectListResolutionContext.hasLateralColumnAlias
+ )
}
+ /**
+ * Resolves [[Expression]] only by resolving its children. This resolution
method is used for
+ * nodes that don't require any special resolution other than resolving its
children.
+ */
+ def resolveExpressionGenerically(expression: Expression): Expression =
Review Comment:
Can be a private?
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/Resolver.scala:
##########
@@ -17,29 +17,50 @@
package org.apache.spark.sql.catalyst.analysis.resolver
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.SparkException
import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.EvaluateUnresolvedInlineTable
import org.apache.spark.sql.catalyst.analysis.{
withPosition,
+ AnalysisErrorAt,
FunctionResolution,
- NamedRelation,
+ MultiInstanceRelation,
RelationResolution,
ResolvedInlineTable,
UnresolvedInlineTable,
- UnresolvedRelation
+ UnresolvedRelation,
+ UnresolvedSubqueryColumnAliases
+}
+import org.apache.spark.sql.catalyst.expressions.{
+ Alias,
+ Attribute,
+ AttributeSet,
+ Expression,
+ NamedExpression
}
import org.apache.spark.sql.catalyst.plans.logical.{
+ AnalysisHelper,
+ CTERelationDef,
+ CTERelationRef,
+ Distinct,
Filter,
GlobalLimit,
+ LeafNode,
LocalLimit,
LocalRelation,
LogicalPlan,
OneRowRelation,
Project,
- SubqueryAlias
+ SubqueryAlias,
+ Union,
+ UnresolvedWith,
+ View,
+ WithCTE
}
-import org.apache.spark.sql.connector.catalog.CatalogManager
-import org.apache.spark.sql.errors.{QueryCompilationErrors, QueryErrorsBase}
+import org.apache.spark.sql.connector.catalog.{CatalogManager}
Review Comment:
```suggestion
import org.apache.spark.sql.connector.catalog.CatalogManager
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/ExpressionResolver.scala:
##########
@@ -123,18 +182,18 @@ class ExpressionResolver(
override def resolve(unresolvedExpression: Expression): Expression = {
planLogger.logExpressionTreeResolutionEvent(unresolvedExpression,
"Unresolved expression tree")
- if (unresolvedExpression
- .getTagValue(ExpressionResolver.SINGLE_PASS_SUBTREE_BOUNDARY)
- .nonEmpty) {
+ if (tryPopSinglePassSubtreeBoundary(unresolvedExpression)) {
unresolvedExpression
} else {
- throwIfNodeWasResolvedEarlier(unresolvedExpression)
+ pushResolutionContext()
- val resolvedExpression = unresolvedExpression match {
+ var resolvedExpression = unresolvedExpression match {
Review Comment:
Is it really needed?
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/MetadataResolver.scala:
##########
@@ -52,7 +58,7 @@ class MetadataResolver(
* [[RelationResolution]] wasn't successful, we resort to using
[[extensions]].
* Otherwise, we fail with an exception.
*/
- def resolve(unresolvedPlan: LogicalPlan): Unit = {
+ override def resolve(unresolvedPlan: LogicalPlan): Unit = {
traverseLogicalPlanTree(unresolvedPlan) { unresolvedOperator =>
unresolvedOperator match {
Review Comment:
```suggestion
traverseLogicalPlanTree(unresolvedPlan) {
case unresolvedRelation: UnresolvedRelation =>
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/resolver/NameScope.scala:
##########
@@ -272,122 +394,74 @@ class NameScopeStack extends SQLConfHelper {
}
/**
- * Completely overwrite the top scope state with a named plan output.
+ * Completely overwrite the top scope state with operator `output`.
*
- * See [[NameScope.update]] for more details.
- */
- def overwriteTop(name: String, attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope.update(name, attributes)
-
- stack.pop()
- stack.push(newScope)
- }
-
- /**
- * Completely overwrite the top scope state with an unnamed plan output.
+ * This method is called by the [[Resolver]] when we've calculated the
output of an operator that
+ * is being resolved. The new output is calculated based on the outputs of
operator's children.
+ *
+ * Example for [[SubqueryAlias]], here we rewrite the top [[NameScope]]'s
attributes to prepend
+ * subquery qualifier to their names:
*
- * See [[NameScope.+=]] for more details.
+ * {{{
+ * val qualifier = sa.identifier.qualifier :+ sa.alias
+ * scope.overwriteTop(scope.output.map(attribute =>
attribute.withQualifier(qualifier)))
+ * }}}
+ *
+ * Trivially, we would call this method for every operator in the query plan,
+ * however some operators just propagate the output of their children
without any changes, so
+ * we can omit this call for them (e.g. [[Filter]]).
+ *
+ * This method should be preferred over [[withNewScope]].
*/
- def overwriteTop(attributes: Seq[Attribute]): Unit = {
- val newScope = new NameScope
- newScope += attributes
+ def overwriteTop(output: Seq[Attribute]): Unit = {
+ val newScope = new NameScope(output)
stack.pop()
stack.push(newScope)
}
/**
- * Execute `body` in a context of a fresh scope. It's used during the
[[Project]] or the
- * [[Aggregate]] resolution to avoid calling [[push]] and [[pop]] explicitly.
+ * Execute `body` in a context of a fresh scope.
+ *
+ * This method is called by the [[Resolver]] before recursing into the
operator's child
+ * resolution _only_ in cases where a fresh scope is required.
+ *
+ * For esample, [[Project]] or [[Aggregate]] introduce their own scopes
semantically, so that a
Review Comment:
```suggestion
* For example, [[Project]] or [[Aggregate]] introduce their own scopes
semantically, so that a
```
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