uros-b commented on code in PR #57629:
URL: https://github.com/apache/spark/pull/57629#discussion_r3689594976
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/InsertMapSortExpression.scala:
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@@ -17,18 +17,21 @@
package org.apache.spark.sql.catalyst.optimizer
+import scala.collection.immutable.VectorMap
import scala.collection.mutable
-import org.apache.spark.sql.catalyst.expressions.{Alias, ArrayTransform,
CreateNamedStruct, Expression, GetStructField, If, IsNull, LambdaFunction,
Literal, MapFromArrays, MapKeys, MapSort, MapValues, NamedExpression,
NamedLambdaVariable}
+import org.apache.spark.sql.catalyst.expressions.{Alias, ArrayTransform,
Attribute, CreateNamedStruct, Expression, GetStructField, If, IsNull,
LambdaFunction, Literal, MapFromArrays, MapKeys, MapSort, MapValues,
NamedExpression, NamedLambdaVariable}
+import
org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression,
AggregateFunction}
import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, LogicalPlan,
Project, RepartitionByExpression}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.catalyst.trees.TreePattern.{AGGREGATE,
REPARTITION_OPERATION}
+import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types.{ArrayType, MapType, StructType}
import org.apache.spark.util.ArrayImplicits.SparkArrayOps
/**
- * Adds [[MapSort]] to [[Aggregate]] expressions containing map columns,
- * as the key/value pairs need to be in the correct order before grouping:
+ * Adds [[MapSort]] to grouping expressions and distinct aggregate arguments
that contain maps,
+ * ensuring key/value pairs have a consistent order before aggregation:
*
Review Comment:
Nit: the rule is still InsertMapSortInGroupingExpressions and every alias it
creates is named _groupingmapsort, including the ones that exist purely for a
distinct argument; so plans will show _groupingmapsort for a column that isn't
a grouping key. The object is nested inside the FinishAnalysis composite rule
and so isn't reachable through spark.sql.optimizer.excludedRules, which makes
renaming it low-risk; at minimum, give the distinct-only aliases their own
name. The scaladoc could also use a distinct-aggregate example alongside the
GROUP BY one, since that's the new behavior.
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