Skip to content
Closed
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ import org.apache.spark.sql.connector.catalog.TableChange.{After, ColumnPosition
import org.apache.spark.sql.connector.catalog.functions.UnboundFunction
import org.apache.spark.sql.connector.catalog.procedures.{BoundProcedure, ProcedureParameter, UnboundProcedure}
import org.apache.spark.sql.connector.expressions.{FieldReference, IdentityTransform}
import org.apache.spark.sql.errors.{QueryCompilationErrors, QueryExecutionErrors}
import org.apache.spark.sql.errors.QueryCompilationErrors
import org.apache.spark.sql.execution.datasources.v2.DataSourceV2Relation
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.internal.SQLConf.{PartitionOverwriteMode, StoreAssignmentPolicy}
Expand Down Expand Up @@ -3564,55 +3564,17 @@ class Analyzer(override val catalogManager: CatalogManager) extends RuleExecutor
hint: JoinHint): LogicalPlan = {
import org.apache.spark.sql.catalyst.util._

val leftKeys = joinNames.map { keyName =>
left.output.find(attr => resolver(attr.name, keyName)).getOrElse {
throw QueryCompilationErrors.unresolvedUsingColForJoinError(
keyName, left.schema.fieldNames.sorted.map(toSQLId).mkString(", "), "left")
}
}
val rightKeys = joinNames.map { keyName =>
right.output.find(attr => resolver(attr.name, keyName)).getOrElse {
throw QueryCompilationErrors.unresolvedUsingColForJoinError(
keyName, right.schema.fieldNames.sorted.map(toSQLId).mkString(", "), "right")
}
}
val joinPairs = leftKeys.zip(rightKeys)

val newCondition = (condition ++ joinPairs.map(EqualTo.tupled)).reduceOption(And)

// columns not in joinPairs
val lUniqueOutput = left.output.filterNot(att => leftKeys.contains(att))
val rUniqueOutput = right.output.filterNot(att => rightKeys.contains(att))
Comment on lines -3584 to -3585
Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I changed the return type of computeKeysForNaturalOrUsingJoin from Seq to AttributeSet to avoid quadratic lookups here. I think it makes sense to make this change in this PR, but it can be moved to a followup. Wdyt @cloud-fan @vladimirg-db ?

Copy link
Contributor Author

@mihailotim-db mihailotim-db Feb 19, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Moved to a separate PR: #50010


// the output list looks like: join keys, columns from left, columns from right
val (projectList, hiddenList) = joinType match {
case LeftOuter =>
(leftKeys ++ lUniqueOutput ++ rUniqueOutput.map(_.withNullability(true)),
rightKeys.map(_.withNullability(true)))
case LeftExistence(_) =>
(leftKeys ++ lUniqueOutput, Seq.empty)
case RightOuter =>
(rightKeys ++ lUniqueOutput.map(_.withNullability(true)) ++ rUniqueOutput,
leftKeys.map(_.withNullability(true)))
case FullOuter =>
// In full outer join, we should return non-null values for the join columns
// if either side has non-null values for those columns. Therefore, for each
// join column pair, add a coalesce to return the non-null value, if it exists.
val joinedCols = joinPairs.map { case (l, r) =>
// Since this is a full outer join, either side could be null, so we explicitly
// set the nullability to true for both sides.
Alias(Coalesce(Seq(l.withNullability(true), r.withNullability(true))), l.name)()
}
(joinedCols ++
lUniqueOutput.map(_.withNullability(true)) ++
rUniqueOutput.map(_.withNullability(true)),
leftKeys.map(_.withNullability(true)) ++
rightKeys.map(_.withNullability(true)))
case _ : InnerLike =>
(leftKeys ++ lUniqueOutput ++ rUniqueOutput, rightKeys)
case _ =>
throw QueryExecutionErrors.unsupportedNaturalJoinTypeError(joinType)
}
val (projectList, hiddenList, newCondition) =
NaturalAndUsingJoinResolution.computeJoinOutputsAndNewCondition(
left,
left.output,
right,
right.output,
joinType,
joinNames,
condition,
(attributeName, keyName) => resolver(attributeName, keyName)
)

// use Project to hide duplicated common keys
// propagate hidden columns from nested USING/NATURAL JOINs
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,166 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.spark.sql.catalyst.analysis

import org.apache.spark.sql.catalyst.SQLConfHelper
import org.apache.spark.sql.catalyst.expressions.{
Alias,
And,
Attribute,
Coalesce,
EqualTo,
Expression,
NamedExpression
}
import org.apache.spark.sql.catalyst.plans.{
FullOuter,
InnerLike,
JoinType,
LeftExistence,
LeftOuter,
RightOuter
}
import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
import org.apache.spark.sql.errors.{
DataTypeErrorsBase,
QueryCompilationErrors,
QueryExecutionErrors
}

object NaturalAndUsingJoinResolution extends DataTypeErrorsBase with SQLConfHelper {

/**
* For a given [[Join]], computes output, hidden output and new condition, if such exists.
*/
def computeJoinOutputsAndNewCondition(
left: LogicalPlan,
leftOutput: Seq[Attribute],
right: LogicalPlan,
rightOutput: Seq[Attribute],
joinType: JoinType,
joinNames: Seq[String],
condition: Option[Expression],
resolveName: (String, String) => Boolean)
: (Seq[NamedExpression], Seq[Attribute], Option[Expression]) = {
val (leftKeys, rightKeys) = resolveKeysForNaturalAndUsingJoin(
left,
leftOutput,
right,
rightOutput,
joinNames,
resolveName
)
val joinPairs = leftKeys.zip(rightKeys)

val newCondition = (condition ++ joinPairs.map(EqualTo.tupled)).reduceOption(And)

// the output list looks like: join keys, columns from left, columns from right
val (output, hiddenOutput) = computeOutputAndHiddenOutput(
leftOutput,
leftKeys,
rightOutput,
rightKeys,
joinPairs,
joinType
)
(output, hiddenOutput, newCondition)
}

/**
* Returns resolved keys for joining based on the output of [[Join]]'s children or throws and
* error if a key name doesn't exist.
*/
private def resolveKeysForNaturalAndUsingJoin(
left: LogicalPlan,
leftOutput: Seq[Attribute],
right: LogicalPlan,
rightOutput: Seq[Attribute],
joinNames: Seq[String],
resolveName: (String, String) => Boolean): (Seq[Attribute], Seq[Attribute]) = {
val leftKeys = joinNames.map { keyName =>
leftOutput.find(attribute => resolveName(attribute.name, keyName)).getOrElse {
throw QueryCompilationErrors.unresolvedUsingColForJoinError(
keyName,
left.schema.fieldNames.sorted.map(toSQLId).mkString(", "),
"left"
)
}
}
val rightKeys = joinNames.map { keyName =>
rightOutput.find(attribute => resolveName(attribute.name, keyName)).getOrElse {
throw QueryCompilationErrors.unresolvedUsingColForJoinError(
keyName,
right.schema.fieldNames.sorted.map(toSQLId).mkString(", "),
"right"
)
}
}
(leftKeys, rightKeys)
}

/**
* Computes the output and hidden output for a given [[Join]], based on the output of its
* children.
*/
private def computeOutputAndHiddenOutput(
leftOutput: Seq[Attribute],
leftKeys: Seq[Attribute],
rightOutput: Seq[Attribute],
rightKeys: Seq[Attribute],
joinPairs: Seq[(Attribute, Attribute)],
joinType: JoinType): (Seq[NamedExpression], Seq[Attribute]) = {
// columns not in joinPairs
val lUniqueOutput = leftOutput.filterNot(att => leftKeys.contains(att))
val rUniqueOutput = rightOutput.filterNot(att => rightKeys.contains(att))
joinType match {
case LeftOuter =>
(
leftKeys ++ lUniqueOutput ++ rUniqueOutput.map(_.withNullability(true)),
rightKeys.map(_.withNullability(true))
)
case LeftExistence(_) =>
(leftKeys ++ lUniqueOutput, Seq.empty)
case RightOuter =>
(
rightKeys ++ lUniqueOutput.map(_.withNullability(true)) ++ rUniqueOutput,
leftKeys.map(_.withNullability(true))
)
case FullOuter =>
// In full outer join, we should return non-null values for the join columns
// if either side has non-null values for those columns. Therefore, for each
// join column pair, add a coalesce to return the non-null value, if it exists.
val joinedCols = joinPairs.map {
case (l, r) =>
// Since this is a full outer join, either side could be null, so we explicitly
// set the nullability to true for both sides.
Alias(Coalesce(Seq(l.withNullability(true), r.withNullability(true))), l.name)()
}
(
joinedCols ++
lUniqueOutput.map(_.withNullability(true)) ++
rUniqueOutput.map(_.withNullability(true)),
leftKeys.map(_.withNullability(true)) ++
rightKeys.map(_.withNullability(true))
)
case _: InnerLike =>
(leftKeys ++ lUniqueOutput ++ rUniqueOutput, rightKeys)
case _ =>
throw QueryExecutionErrors.unsupportedNaturalJoinTypeError(joinType)
}
}
}