dcoliversun commented on a change in pull request #35823:
URL: https://github.com/apache/spark/pull/35823#discussion_r825562687
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -779,15 +779,19 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
checkAnswer(df, Seq(Row(1d), Row(1d), Row(null)))
}
- test("scan with aggregate push-down: aggregate over alias NOT push down") {
+ test("scan with aggregate push-down: aggregate over alias push down") {
Review comment:
Hi. Is it better to specify `SPARK-38533` ?
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
+ val df = spark.table("h2.test.employee")
+ .select($"DEPT", $"SALARY".as("mySalary"))
+ .groupBy($"DEPT")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
Review comment:
Why not use `camel case` naming?
https://docs.scala-lang.org/style/naming-conventions.html
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
Review comment:
ditto
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
+ val df = spark.table("h2.test.employee")
+ .select($"DEPT", $"SALARY".as("mySalary"))
+ .groupBy($"DEPT")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df, expected_plan_fragment)
+ }
+ checkAnswer(df, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+
+ val df2 = spark.table("h2.test.employee")
+ .select($"DEPT".as("myDept"), $"SALARY".as("mySalary"))
+ .groupBy($"myDept")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df2)
+ df2.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df2, expected_plan_fragment)
+ }
+ checkAnswer(df2, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+ }
+
+ test("scan with aggregate push-down: partial push-down aggregate with
alias") {
Review comment:
ditto
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
+ val df = spark.table("h2.test.employee")
+ .select($"DEPT", $"SALARY".as("mySalary"))
+ .groupBy($"DEPT")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df, expected_plan_fragment)
+ }
+ checkAnswer(df, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+
+ val df2 = spark.table("h2.test.employee")
+ .select($"DEPT".as("myDept"), $"SALARY".as("mySalary"))
+ .groupBy($"myDept")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df2)
+ df2.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df2, expected_plan_fragment)
+ }
+ checkAnswer(df2, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+ }
+
+ test("scan with aggregate push-down: partial push-down aggregate with
alias") {
+ val df = spark.read
+ .option("partitionColumn", "DEPT")
+ .option("lowerBound", "0")
+ .option("upperBound", "2")
+ .option("numPartitions", "2")
+ .table("h2.test.employee")
+ .select($"NAME", $"SALARY".as("mySalary"))
+ .groupBy($"NAME")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df, false)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
Review comment:
ditto
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
+ val df = spark.table("h2.test.employee")
+ .select($"DEPT", $"SALARY".as("mySalary"))
+ .groupBy($"DEPT")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df, expected_plan_fragment)
+ }
+ checkAnswer(df, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+
+ val df2 = spark.table("h2.test.employee")
+ .select($"DEPT".as("myDept"), $"SALARY".as("mySalary"))
+ .groupBy($"myDept")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df2)
+ df2.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
Review comment:
ditto
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
##########
@@ -1032,4 +1036,76 @@ class JDBCV2Suite extends QueryTest with
SharedSparkSession with ExplainSuiteHel
|ON h2.test.view1.`|col1` = h2.test.view2.`|col1`""".stripMargin)
checkAnswer(df, Seq.empty[Row])
}
+
+ test("scan with aggregate push-down: complete push-down aggregate with
alias") {
+ val df = spark.table("h2.test.employee")
+ .select($"DEPT", $"SALARY".as("mySalary"))
+ .groupBy($"DEPT")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df, expected_plan_fragment)
+ }
+ checkAnswer(df, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+
+ val df2 = spark.table("h2.test.employee")
+ .select($"DEPT".as("myDept"), $"SALARY".as("mySalary"))
+ .groupBy($"myDept")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df2)
+ df2.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [DEPT]"
+ checkKeywordsExistsInExplain(df2, expected_plan_fragment)
+ }
+ checkAnswer(df2, Seq(Row(1, 19000.00), Row(2, 22000.00), Row(6, 12000.00)))
+ }
+
+ test("scan with aggregate push-down: partial push-down aggregate with
alias") {
+ val df = spark.read
+ .option("partitionColumn", "DEPT")
+ .option("lowerBound", "0")
+ .option("upperBound", "2")
+ .option("numPartitions", "2")
+ .table("h2.test.employee")
+ .select($"NAME", $"SALARY".as("mySalary"))
+ .groupBy($"NAME")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df, false)
+ df.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
+ "PushedAggregates: [SUM(SALARY)], PushedFilters: [],
PushedGroupByColumns: [NAME]"
+ checkKeywordsExistsInExplain(df, expected_plan_fragment)
+ }
+ checkAnswer(df, Seq(Row("alex", 12000.00), Row("amy", 10000.00),
+ Row("cathy", 9000.00), Row("david", 10000.00), Row("jen", 12000.00)))
+
+ val df2 = spark.read
+ .option("partitionColumn", "DEPT")
+ .option("lowerBound", "0")
+ .option("upperBound", "2")
+ .option("numPartitions", "2")
+ .table("h2.test.employee")
+ .select($"NAME".as("myName"), $"SALARY".as("mySalary"))
+ .groupBy($"myName")
+ .agg(sum($"mySalary").as("total"))
+ .filter($"total" > 1000)
+ checkAggregateRemoved(df2, false)
+ df2.queryExecution.optimizedPlan.collect {
+ case _: DataSourceV2ScanRelation =>
+ val expected_plan_fragment =
Review comment:
ditto
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanRelationPushDown.scala
##########
@@ -92,23 +92,38 @@ object V2ScanRelationPushDown extends Rule[LogicalPlan]
with PredicateHelper {
// update the scan builder with agg pushdown and return a new plan with
agg pushed
case aggNode @ Aggregate(groupingExpressions, resultExpressions, child) =>
child match {
- case ScanOperation(project, filters, sHolder: ScanBuilderHolder)
- if filters.isEmpty &&
project.forall(_.isInstanceOf[AttributeReference]) =>
+ case ScanOperation(project, filters, sHolder: ScanBuilderHolder) if
filters.isEmpty &&
+ project.forall(p => p.isInstanceOf[AttributeReference] ||
p.isInstanceOf[Alias]) =>
sHolder.builder match {
case r: SupportsPushDownAggregates =>
+ val aliasAttrToOriginAttr = mutable.HashMap.empty[Expression,
AttributeReference]
+ val originAttrToAliasAttr = mutable.HashMap.empty[Expression,
Attribute]
+ collectAliases(project, aliasAttrToOriginAttr,
originAttrToAliasAttr)
+ val newResultExpressions = resultExpressions.map { expr =>
+ expr.transform {
+ case r: AttributeReference if
aliasAttrToOriginAttr.contains(r.canonicalized) =>
+ aliasAttrToOriginAttr(r.canonicalized)
+ }
+ }.asInstanceOf[Seq[NamedExpression]]
+ val newGroupingExpressions = groupingExpressions.map { expr =>
+ expr.transform {
+ case r: AttributeReference if
aliasAttrToOriginAttr.contains(r.canonicalized) =>
+ aliasAttrToOriginAttr(r.canonicalized)
Review comment:
These two lambda expressions behave the same, we can consider reusing a
function
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