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Original file line number Diff line number Diff line change
Expand Up @@ -325,9 +325,6 @@ class Analyzer(override val catalogManager: CatalogManager) extends RuleExecutor
new ResolveIdentifierClause(earlyBatches) ::
ResolveUnion ::
ResolveRowLevelCommandAssignments ::
RewriteDeleteFromTable ::
RewriteUpdateTable ::
RewriteMergeIntoTable ::
typeCoercionRules ++
Seq(
ResolveWithCTE,
Expand All @@ -351,6 +348,14 @@ class Analyzer(override val catalogManager: CatalogManager) extends RuleExecutor
UpdateAttributeNullability),
Batch("UDF", Once,
ResolveEncodersInUDF),
// The rewrite rules might move resolved query plan into subquery. Once the resolved plan
// contains ScalaUDF, their encoders won't be resolved if `ResolveEncodersInUDF` is not
// applied before the rewrite rules. So we need to apply `ResolveEncodersInUDF` before the
// rewrite rules.
Batch("DML rewrite", fixedPoint,
RewriteDeleteFromTable,
RewriteUpdateTable,
RewriteMergeIntoTable),
Batch("Subquery", Once,
UpdateOuterReferences),
Batch("Cleanup", fixedPoint,
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,95 @@
/*
* 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.dsl.expressions._
import org.apache.spark.sql.catalyst.dsl.plans._
import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Exists, ScalaUDF}
import org.apache.spark.sql.catalyst.plans.logical.{Assignment, Filter, MergeIntoTable, ReplaceData, UpdateAction}
import org.apache.spark.sql.catalyst.trees.TreePattern
import org.apache.spark.sql.connector.catalog.InMemoryRowLevelOperationTable
import org.apache.spark.sql.execution.datasources.v2.DataSourceV2Relation
import org.apache.spark.sql.types.{DoubleType, IntegerType, StringType, StructField, StructType}
import org.apache.spark.sql.util.CaseInsensitiveStringMap

class ResolveEncodersInUDFSuite extends AnalysisTest {
test("SPARK-48921: ScalaUDF encoders in subquery should be resolved for MergeInto") {
val table = new InMemoryRowLevelOperationTable("table",
StructType(StructField("a", IntegerType) ::
StructField("b", DoubleType) ::
StructField("c", StringType) :: Nil),
Array.empty,
new java.util.HashMap[String, String]()
)
val relation = DataSourceV2Relation(table,
Seq(AttributeReference("a", IntegerType)(),
AttributeReference("b", DoubleType)(),
AttributeReference("c", StringType)()),
None,
None,
CaseInsensitiveStringMap.empty()
)


val string = relation.output(2)
val udf = ScalaUDF((_: String) => "x", StringType, string :: Nil,
Option(ExpressionEncoder[String]()) :: Nil)

val mergeIntoSource =
relation
.where($"c" === udf)
.select($"a", $"b")
.limit(1)
val cond = mergeIntoSource.output(0) == relation.output(0) &&
mergeIntoSource.output(1) == relation.output(1)

val mergePlan = MergeIntoTable(
relation,
mergeIntoSource,
cond,
Seq(UpdateAction(None,
Seq(Assignment(relation.output(0), relation.output(0)),
Assignment(relation.output(1), relation.output(1)),
Assignment(relation.output(2), relation.output(2))))),
Seq.empty,
Seq.empty)

val replaceData = mergePlan.analyze.asInstanceOf[ReplaceData]

val existsPlans = replaceData.groupFilterCondition.map(_.collect {
case e: Exists =>
e.plan.collect {
case f: Filter if f.containsPattern(TreePattern.SCALA_UDF) => f
}
}.flatten)

assert(existsPlans.isDefined)

val udfs = existsPlans.get.map(_.expressions.flatMap(e => e.collect {
case s: ScalaUDF =>
assert(s.inputEncoders.nonEmpty)
val encoder = s.inputEncoders.head
assert(encoder.isDefined)
assert(encoder.get.objDeserializer.resolved)

s
})).flatten
assert(udfs.size == 1)
}
}