Nn/spark 31620

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/BaseAggregateExec.scala

@@ -0,0 +1,53 @@
+/*
+ * 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.execution.aggregate
+
+import org.apache.spark.sql.catalyst.expressions.Attribute
+import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Final, PartialMerge}
+import org.apache.spark.sql.execution.UnaryExecNode
+
+/**
+ * Holds common logic for aggregate operators
+ */
+trait BaseAggregateExec extends UnaryExecNode {
+  def aggregateExpressions: Seq[AggregateExpression]
+
+  protected def inputAttributes: Seq[Attribute] = {
+    val modes = aggregateExpressions.map(_.mode).distinct
+    if (modes.contains(Final) || modes.contains(PartialMerge)) {
+      // SPARK-31620: when planning aggregates, the partial aggregate uses aggregate function's
+      // `inputAggBufferAttributes` as its output. And Final and PartialMerge aggregate rely on the
+      // output to bind references for `DeclarativeAggregate.mergeExpressions`. But if we copy the
+      // aggregate function somehow after aggregate planning, like `PlanSubqueries`, the
+      // `DeclarativeAggregate` will be replaced by a new instance with new
+      // `inputAggBufferAttributes` and `mergeExpressions`. Then Final and PartialMerge aggregate
+      // can't bind the `mergeExpressions` with the output of the partial aggregate, as they use
+      // the `inputAggBufferAttributes` of the original `DeclarativeAggregate` before copy. Instead,
+      // we shall use `inputAggBufferAttributes` after copy to match the new `mergeExpressions`.
+      val aggAttrs = aggregateExpressions
+        // there're exactly four cases needs `inputAggBufferAttributes` from child according to the
+        // agg planning in `AggUtils`: Partial -> Final, PartialMerge -> Final,
+        // Partial -> PartialMerge, PartialMerge -> PartialMerge.
+        .filter(a => a.mode == Final || a.mode == PartialMerge).map(_.aggregateFunction)
+        .flatMap(_.inputAggBufferAttributes)
+      child.output.dropRight(aggAttrs.length) ++ aggAttrs
+    } else {
+      child.output
+    }
+  }
+}

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala

@@ -47,7 +47,7 @@ case class HashAggregateExec(
     initialInputBufferOffset: Int,
     resultExpressions: Seq[NamedExpression],
     child: SparkPlan)
-  extends UnaryExecNode with BlockingOperatorWithCodegen {
+  extends BaseAggregateExec with BlockingOperatorWithCodegen {
 
   private[this] val aggregateBufferAttributes = {
     aggregateExpressions.flatMap(_.aggregateFunction.aggBufferAttributes)
@@ -121,7 +121,7 @@ case class HashAggregateExec(
             resultExpressions,
             (expressions, inputSchema) =>
               newMutableProjection(expressions, inputSchema, subexpressionEliminationEnabled),
-            child.output,
+            inputAttributes,
             iter,
             testFallbackStartsAt,
             numOutputRows,
@@ -254,7 +254,7 @@ case class HashAggregateExec(
   private def doConsumeWithoutKeys(ctx: CodegenContext, input: Seq[ExprCode]): String = {
     // only have DeclarativeAggregate
     val functions = aggregateExpressions.map(_.aggregateFunction.asInstanceOf[DeclarativeAggregate])
-    val inputAttrs = functions.flatMap(_.aggBufferAttributes) ++ child.output
+    val inputAttrs = functions.flatMap(_.aggBufferAttributes) ++ inputAttributes
     val updateExpr = aggregateExpressions.flatMap { e =>
       e.mode match {
         case Partial | Complete =>
@@ -817,7 +817,7 @@ case class HashAggregateExec(
       }
     }
 
-    val inputAttr = aggregateBufferAttributes ++ child.output
+    val inputAttr = aggregateBufferAttributes ++ inputAttributes
     // Here we set `currentVars(0)` to `currentVars(numBufferSlots)` to null, so that when
     // generating code for buffer columns, we use `INPUT_ROW`(will be the buffer row), while
     // generating input columns, we use `currentVars`.

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/ObjectHashAggregateExec.scala

@@ -65,7 +65,7 @@ case class ObjectHashAggregateExec(
     initialInputBufferOffset: Int,
     resultExpressions: Seq[NamedExpression],
     child: SparkPlan)
-  extends UnaryExecNode {
+  extends BaseAggregateExec {
 
   private[this] val aggregateBufferAttributes = {
     aggregateExpressions.flatMap(_.aggregateFunction.aggBufferAttributes)
@@ -121,7 +121,7 @@ case class ObjectHashAggregateExec(
             resultExpressions,
             (expressions, inputSchema) =>
               newMutableProjection(expressions, inputSchema, subexpressionEliminationEnabled),
-            child.output,
+            inputAttributes,
             iter,
             fallbackCountThreshold,
             numOutputRows)

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/SortAggregateExec.scala

@@ -24,7 +24,7 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.aggregate._
 import org.apache.spark.sql.catalyst.plans.physical._
 import org.apache.spark.sql.catalyst.util.truncatedString
-import org.apache.spark.sql.execution.{SparkPlan, UnaryExecNode}
+import org.apache.spark.sql.execution.SparkPlan
 import org.apache.spark.sql.execution.metric.SQLMetrics
 
 /**
@@ -38,7 +38,7 @@ case class SortAggregateExec(
     initialInputBufferOffset: Int,
     resultExpressions: Seq[NamedExpression],
     child: SparkPlan)
-  extends UnaryExecNode {
+  extends BaseAggregateExec {
 
   private[this] val aggregateBufferAttributes = {
     aggregateExpressions.flatMap(_.aggregateFunction.aggBufferAttributes)
@@ -86,7 +86,7 @@ case class SortAggregateExec(
         val outputIter = new SortBasedAggregationIterator(
           partIndex,
           groupingExpressions,
-          child.output,
+          inputAttributes,
           iter,
           aggregateExpressions,
           aggregateAttributes,

sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala

@@ -772,4 +772,43 @@ class DataFrameAggregateSuite extends QueryTest with SharedSQLContext {
       Row(Seq(0.0f, 0.0f), Row(0.0d, Double.NaN), Seq(Row(0.0d, Double.NaN)), 2)
     )
   }
+
+  Seq(true, false).foreach { value =>
+    test(s"SPARK-31620: agg with subquery (whole-stage-codegen = $value)") {
+      withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> value.toString) {
+        withTempView("t1", "t2") {
+          sql("create temporary view t1 as select * from values (1, 2) as t1(a, b)")
+          sql("create temporary view t2 as select * from values (3, 4) as t2(c, d)")
+
+          // test without grouping keys
+          checkAnswer(sql("select sum(if(c > (select a from t1), d, 0)) as csum from t2"),
+            Row(4) :: Nil)
+
+          // test with grouping keys
+          checkAnswer(sql("select c, sum(if(c > (select a from t1), d, 0)) as csum from " +
+            "t2 group by c"), Row(3, 4) :: Nil)
+
+          // test with distinct
+          checkAnswer(sql("select avg(distinct(d)), sum(distinct(if(c > (select a from t1)," +
+            " d, 0))) as csum from t2 group by c"), Row(4, 4) :: Nil)
+
+          // test subquery with agg
+          checkAnswer(sql("select sum(distinct(if(c > (select sum(distinct(a)) from t1)," +
+            " d, 0))) as csum from t2 group by c"), Row(4) :: Nil)
+
+          // test SortAggregateExec
+          var df = sql("select max(if(c > (select a from t1), 'str1', 'str2')) as csum from t2")
+          assert(df.queryExecution.executedPlan
+            .find { case _: SortAggregateExec => true }.isDefined)
+          checkAnswer(df, Row("str1") :: Nil)
+
+          // test ObjectHashAggregateExec
+          df = sql("select collect_list(d), sum(if(c > (select a from t1), d, 0)) as csum from t2")
+          assert(df.queryExecution.executedPlan
+            .find { case _: ObjectHashAggregateExec => true }.isDefined)
+          checkAnswer(df, Row(Array(4), 4) :: Nil)
+        }
+      }
+    }
+  }
 }