zml1206 commented on code in PR #12473:
URL: https://github.com/apache/gluten/pull/12473#discussion_r3541759554
##########
gluten-ut/spark41/src/test/scala/org/apache/spark/sql/GlutenSubquerySuite.scala:
##########
@@ -32,24 +37,81 @@ class GlutenSubquerySuite extends SubquerySuite with
GlutenSQLTestsTrait {
"SPARK-28441: COUNT bug with attribute ref in subquery input and output
with PythonUDF"
)
- // === Following cases override super class's cases ===
- // TODO: fix in Spark-4.0
- ignoreGluten("SPARK-26893 Allow pushdown of partition pruning subquery
filters to file source") {
+ testGluten("SPARK-26893: Allow pushdown of partition pruning subquery
filters to file source") {
withTable("a", "b") {
spark.range(4).selectExpr("id", "id % 2 AS
p").write.partitionBy("p").saveAsTable("a")
spark.range(2).write.saveAsTable("b")
- // need to execute the query before we can examine fs.inputRDDs()
val df = sql("SELECT * FROM a WHERE p <= (SELECT MIN(id) FROM b)")
checkAnswer(df, Seq(Row(0, 0), Row(2, 0)))
- assert(stripAQEPlan(df.queryExecution.executedPlan).collectFirst {
- case t: WholeStageTransformer => t
- } match {
- case Some(WholeStageTransformer(fs: FileSourceScanExecTransformer, _))
=>
- fs.dynamicallySelectedPartitions.toPartitionArray
- .exists(_.filePath.toString.contains("p=0"))
- case _ => false
+ // need to execute the query before we can examine fs.inputRDDs()
+ val fileSourceScanExec =
collect(stripAQEPlan(df.queryExecution.executedPlan)) {
+ case fs: FileSourceScanExecTransformer => fs
+ }
+ assert(fileSourceScanExec.size === 1)
+ val scan = fileSourceScanExec.head
+ assert(scan.partitionFilters.exists(ExecSubqueryExpression.hasSubquery))
+ val selectedPartitions =
scan.dynamicallySelectedPartitions.toPartitionArray
+ assert(selectedPartitions.nonEmpty)
+ assert(selectedPartitions.forall(_.filePath.toString.contains("p=0")))
+ }
+ }
+
+ testGluten("SPARK-36280: Remove redundant aliases after
RewritePredicateSubquery") {
+ withTable("t1", "t2") {
+ sql("CREATE TABLE t1 USING parquet AS SELECT id AS a, id AS b, id AS c
FROM range(10)")
+ sql("CREATE TABLE t2 USING parquet AS SELECT id AS x, id AS y FROM
range(8)")
+ val df = sql(
+ """
+ |SELECT *
+ |FROM t1
+ |WHERE a IN (SELECT x
+ | FROM (SELECT x AS x,
+ | RANK() OVER (PARTITION BY x ORDER BY
SUM(y) DESC) AS ranking
+ | FROM t2
+ | GROUP BY x) tmp1
+ | WHERE ranking <= 5)
+ |""".stripMargin)
+
+ df.collect()
+ val exchanges = collect(df.queryExecution.executedPlan) {
+ case s: ColumnarShuffleExchangeExec => s
+ }
+ assert(exchanges.size === 1)
+ }
+ }
+
+ testGluten(
+ "SPARK-43402: FileSourceScanExec supports push down data filter with
scalar subquery") {
+ def checkFileSourceScan(query: String, answer: Seq[Row]): Unit = {
+ val df = sql(query)
+ checkAnswer(df, answer)
+ val fileSourceScanExec = collect(df.queryExecution.executedPlan) {
+ case f: FileSourceScanExecTransformer => f
+ }
+ sparkContext.listenerBus.waitUntilEmpty()
+ assert(fileSourceScanExec.size === 1)
+ val scalarSubquery =
fileSourceScanExec.head.dataFilters.flatMap(_.collect {
+ case s: ScalarSubquery => s
})
+ assert(scalarSubquery.length === 1)
+ assert(scalarSubquery.head.plan.isInstanceOf[ReusedSubqueryExec])
+ assert(fileSourceScanExec.head.metrics("numFiles").value === 1)
+ assert(fileSourceScanExec.head.metrics("numOutputRows").value ===
answer.size)
Review Comment:
No, this is Spark's original test logic. This patch only adapts the physical
operator assertions for Gluten. The expectations around reused scalar subquery
and scan metrics are intentionally kept the same as Spark's test.
##########
gluten-ut/spark40/src/test/scala/org/apache/spark/sql/GlutenSubquerySuite.scala:
##########
@@ -32,24 +37,81 @@ class GlutenSubquerySuite extends SubquerySuite with
GlutenSQLTestsTrait {
"SPARK-28441: COUNT bug with attribute ref in subquery input and output
with PythonUDF"
)
- // === Following cases override super class's cases ===
- // TODO: fix in Spark-4.0
- ignoreGluten("SPARK-26893 Allow pushdown of partition pruning subquery
filters to file source") {
+ testGluten("SPARK-26893: Allow pushdown of partition pruning subquery
filters to file source") {
withTable("a", "b") {
spark.range(4).selectExpr("id", "id % 2 AS
p").write.partitionBy("p").saveAsTable("a")
spark.range(2).write.saveAsTable("b")
- // need to execute the query before we can examine fs.inputRDDs()
val df = sql("SELECT * FROM a WHERE p <= (SELECT MIN(id) FROM b)")
checkAnswer(df, Seq(Row(0, 0), Row(2, 0)))
- assert(stripAQEPlan(df.queryExecution.executedPlan).collectFirst {
- case t: WholeStageTransformer => t
- } match {
- case Some(WholeStageTransformer(fs: FileSourceScanExecTransformer, _))
=>
- fs.dynamicallySelectedPartitions.toPartitionArray
- .exists(_.filePath.toString.contains("p=0"))
- case _ => false
+ // need to execute the query before we can examine fs.inputRDDs()
+ val fileSourceScanExec =
collect(stripAQEPlan(df.queryExecution.executedPlan)) {
+ case fs: FileSourceScanExecTransformer => fs
+ }
+ assert(fileSourceScanExec.size === 1)
+ val scan = fileSourceScanExec.head
+ assert(scan.partitionFilters.exists(ExecSubqueryExpression.hasSubquery))
+ val selectedPartitions =
scan.dynamicallySelectedPartitions.toPartitionArray
+ assert(selectedPartitions.nonEmpty)
+ assert(selectedPartitions.forall(_.filePath.toString.contains("p=0")))
+ }
+ }
+
+ testGluten("SPARK-36280: Remove redundant aliases after
RewritePredicateSubquery") {
+ withTable("t1", "t2") {
+ sql("CREATE TABLE t1 USING parquet AS SELECT id AS a, id AS b, id AS c
FROM range(10)")
+ sql("CREATE TABLE t2 USING parquet AS SELECT id AS x, id AS y FROM
range(8)")
+ val df = sql(
+ """
+ |SELECT *
+ |FROM t1
+ |WHERE a IN (SELECT x
+ | FROM (SELECT x AS x,
+ | RANK() OVER (PARTITION BY x ORDER BY
SUM(y) DESC) AS ranking
+ | FROM t2
+ | GROUP BY x) tmp1
+ | WHERE ranking <= 5)
+ |""".stripMargin)
+
+ df.collect()
+ val exchanges = collect(df.queryExecution.executedPlan) {
+ case s: ColumnarShuffleExchangeExec => s
+ }
+ assert(exchanges.size === 1)
+ }
+ }
+
+ testGluten(
+ "SPARK-43402: FileSourceScanExec supports push down data filter with
scalar subquery") {
+ def checkFileSourceScan(query: String, answer: Seq[Row]): Unit = {
+ val df = sql(query)
+ checkAnswer(df, answer)
+ val fileSourceScanExec = collect(df.queryExecution.executedPlan) {
+ case f: FileSourceScanExecTransformer => f
+ }
+ sparkContext.listenerBus.waitUntilEmpty()
+ assert(fileSourceScanExec.size === 1)
+ val scalarSubquery =
fileSourceScanExec.head.dataFilters.flatMap(_.collect {
+ case s: ScalarSubquery => s
})
+ assert(scalarSubquery.length === 1)
+ assert(scalarSubquery.head.plan.isInstanceOf[ReusedSubqueryExec])
+ assert(fileSourceScanExec.head.metrics("numFiles").value === 1)
+ assert(fileSourceScanExec.head.metrics("numOutputRows").value ===
answer.size)
Review Comment:
ditto.
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