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[SPARK-26572][SQL] fix aggregate codegen result evaluation #23731

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[SPARK-26572][SQL] fix aggregate codegen result evaluation #23731

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b906c8c
[SPARK-26572][SQL] fix aggregate codegen result evaluation
peter-toth Feb 3, 2019
b5d079c
indentation fix
peter-toth Feb 3, 2019
567f8f6
incorporate suggested changes
peter-toth Feb 5, 2019
5ae9add
fix review findings
peter-toth Feb 13, 2019
af861d5
fix var name
peter-toth Feb 14, 2019
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12 changes: 12 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/WholeStageCodegenExec.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -290,6 +290,18 @@ trait CodegenSupport extends SparkPlan {
evaluateVars.toString()
}

/**
* Returns source code to evaluate the variables for non-deterministic expressions, and clear the
* code of evaluated variables, to prevent them to be evaluated twice.
*/
protected def evaluateNondeterministicVariables(
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@rednaxelafx rednaxelafx Feb 12, 2019

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Nitpick on naming: "variables" are never non-deterministic, only expressions can have the property of being deterministic or not. Two options:

  • I'd prefer naming this utility function evaluateNondeterministicResults to emphasis this should (mostly) be used on the results of an output projection list.
  • But the existing utility function evaluateRequiredVariables uses the "variable" notion, so keeping consistency there is fine too.

I'm fine either way.

Also, historically Spark SQL's WSCG would use variable names like eval for the ExprCode type, e.g. evals: Seq[ExprCode]. Not sure why it started that way but you can see that naming pattern throughout the WSCG code base.
Again, your new utility function follows the same names used in evaluateRequiredVariables so that's fine. Local consistency is good enough.

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@maropu maropu Feb 13, 2019

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To keep the consistent naming, +1 for evaluateNondeterministicVariables .

attributes: Seq[Attribute],
variables: Seq[ExprCode],
expressions: Seq[NamedExpression]): String = {
val nondeterministicAttrs = expressions.filterNot(_.deterministic).map(_.toAttribute)
evaluateRequiredVariables(attributes, variables, AttributeSet(nondeterministicAttrs))
}

/**
* The subset of inputSet those should be evaluated before this plan.
*
Expand Down
12 changes: 10 additions & 2 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala
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Expand Up @@ -466,10 +466,13 @@ case class HashAggregateExec(
val resultVars = bindReferences[Expression](
resultExpressions,
inputAttrs).map(_.genCode(ctx))
val evaluateNondeterministicResults =
evaluateNondeterministicVariables(output, resultVars, resultExpressions)
s"""
$evaluateKeyVars
$evaluateBufferVars
$evaluateAggResults
$evaluateNondeterministicResults
${consume(ctx, resultVars)}
"""
} else if (modes.contains(Partial) || modes.contains(PartialMerge)) {
Expand Down Expand Up @@ -506,10 +509,15 @@ case class HashAggregateExec(
// generate result based on grouping key
ctx.INPUT_ROW = keyTerm
ctx.currentVars = null
val eval = bindReferences[Expression](
val resultVars = bindReferences[Expression](
resultExpressions,
groupingAttributes).map(_.genCode(ctx))
consume(ctx, eval)
val evaluateNondeterministicResults =
evaluateNondeterministicVariables(output, resultVars, resultExpressions)
s"""
$evaluateNondeterministicResults
${consume(ctx, resultVars)}
"""
}
ctx.addNewFunction(funcName,
s"""
Expand Down
30 changes: 29 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
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Expand Up @@ -25,7 +25,7 @@ import org.apache.spark.sql.execution.columnar.InMemoryTableScanExec
import org.apache.spark.sql.execution.joins.BroadcastHashJoinExec
import org.apache.spark.sql.execution.joins.SortMergeJoinExec
import org.apache.spark.sql.expressions.scalalang.typed
import org.apache.spark.sql.functions.{avg, broadcast, col, lit, max}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.test.SharedSQLContext
import org.apache.spark.sql.types.{IntegerType, StringType, StructType}
Expand Down Expand Up @@ -339,4 +339,32 @@ class WholeStageCodegenSuite extends QueryTest with SharedSQLContext {

checkAnswer(df, Seq(Row(1, 3), Row(2, 3)))
}

test("SPARK-26572: evaluate non-deterministic expressions for aggregate results") {
withSQLConf(
SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> Long.MaxValue.toString,
SQLConf.SHUFFLE_PARTITIONS.key -> "1") {
val baseTable = Seq(1, 1).toDF("idx")

// BroadcastHashJoinExec with a HashAggregateExec child containing no aggregate expressions
val distinctWithId = baseTable.distinct().withColumn("id", monotonically_increasing_id())
.join(baseTable, "idx")
assert(distinctWithId.queryExecution.executedPlan.collectFirst {
case WholeStageCodegenExec(
ProjectExec(_, BroadcastHashJoinExec(_, _, _, _, _, _: HashAggregateExec, _))) => true
}.isDefined)
checkAnswer(distinctWithId, Seq(Row(1, 0), Row(1, 0)))

// BroadcastHashJoinExec with a HashAggregateExec child containing a Final mode aggregate
// expression
val groupByWithId =
baseTable.groupBy("idx").sum().withColumn("id", monotonically_increasing_id())
.join(baseTable, "idx")
assert(groupByWithId.queryExecution.executedPlan.collectFirst {
case WholeStageCodegenExec(
ProjectExec(_, BroadcastHashJoinExec(_, _, _, _, _, _: HashAggregateExec, _))) => true
}.isDefined)
checkAnswer(groupByWithId, Seq(Row(1, 2, 0), Row(1, 2, 0)))
}
}
}