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[SPARK-19993][SQL] Caching logical plans containing subquery expressions does not work. #17330
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Original file line number | Diff line number | Diff line change |
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@@ -59,6 +59,14 @@ abstract class SubqueryExpression( | |
children.zip(p.children).forall(p => p._1.semanticEquals(p._2)) | ||
case _ => false | ||
} | ||
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def canonicalize(attrs: AttributeSeq): SubqueryExpression = { | ||
// Normalize the outer references in the subquery plan. | ||
val subPlan = plan.transformAllExpressions { | ||
case OuterReference(r) => plan.normalizeExprId(r, attrs) | ||
} | ||
withNewPlan(subPlan).canonicalized.asInstanceOf[SubqueryExpression] | ||
} | ||
} | ||
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object SubqueryExpression { | ||
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@@ -236,6 +244,12 @@ case class ScalarSubquery( | |
override def nullable: Boolean = true | ||
override def withNewPlan(plan: LogicalPlan): ScalarSubquery = copy(plan = plan) | ||
override def toString: String = s"scalar-subquery#${exprId.id} $conditionString" | ||
override lazy val canonicalized: Expression = { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I think we can just override There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @cloud-fan preCanonicalize is a method in QueryPlan ? Can we override it here ? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. oh sorry it's expression |
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ScalarSubquery( | ||
plan.canonicalized, | ||
children.map(_.canonicalized), | ||
ExprId(0)) | ||
} | ||
} | ||
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object ScalarSubquery { | ||
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@@ -268,6 +282,12 @@ case class ListQuery( | |
override def nullable: Boolean = false | ||
override def withNewPlan(plan: LogicalPlan): ListQuery = copy(plan = plan) | ||
override def toString: String = s"list#${exprId.id} $conditionString" | ||
override lazy val canonicalized: Expression = { | ||
ListQuery( | ||
plan.canonicalized, | ||
children.map(_.canonicalized), | ||
ExprId(0)) | ||
} | ||
} | ||
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/** | ||
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@@ -290,4 +310,10 @@ case class Exists( | |
override def nullable: Boolean = false | ||
override def withNewPlan(plan: LogicalPlan): Exists = copy(plan = plan) | ||
override def toString: String = s"exists#${exprId.id} $conditionString" | ||
override lazy val canonicalized: Expression = { | ||
Exists( | ||
plan.canonicalized, | ||
children.map(_.canonicalized), | ||
ExprId(0)) | ||
} | ||
} |
Original file line number | Diff line number | Diff line change |
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@@ -401,8 +401,9 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]] extends TreeNode[PlanT | |
* do not use `BindReferences` here as the plan may take the expression as a parameter with type | ||
* `Attribute`, and replace it with `BoundReference` will cause error. | ||
*/ | ||
protected def normalizeExprId[T <: Expression](e: T, input: AttributeSeq = allAttributes): T = { | ||
def normalizeExprId[T <: Expression](e: T, input: AttributeSeq = allAttributes): T = { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. oh, seems we can move this method to There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @cloud-fan Ok. Sounds good wenchen. |
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e.transformUp { | ||
case s: SubqueryExpression => s.canonicalize(input) | ||
case ar: AttributeReference => | ||
val ordinal = input.indexOf(ar.exprId) | ||
if (ordinal == -1) { | ||
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Original file line number | Diff line number | Diff line change |
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@@ -26,7 +26,7 @@ import org.scalatest.concurrent.Eventually._ | |
import org.apache.spark.CleanerListener | ||
import org.apache.spark.sql.catalyst.TableIdentifier | ||
import org.apache.spark.sql.catalyst.expressions.SubqueryExpression | ||
import org.apache.spark.sql.execution.RDDScanExec | ||
import org.apache.spark.sql.execution.{RDDScanExec, SparkPlan} | ||
import org.apache.spark.sql.execution.columnar._ | ||
import org.apache.spark.sql.execution.exchange.ShuffleExchange | ||
import org.apache.spark.sql.functions._ | ||
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@@ -76,6 +76,13 @@ class CachedTableSuite extends QueryTest with SQLTestUtils with SharedSQLContext | |
sum | ||
} | ||
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private def getNumInMemoryTableScanExecs(plan: SparkPlan): Int = { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. we need a better name, this actually get in-memory table recursively, which is different from There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @cloud-fan So we are operating at the physical plan level in this method where as the other method getNumInMemoryRelations operates at a logical plan level. And in here we are simply counting the the InMemoryTableScanExec nodes in the plan. I have changed the function name to getNumInMemoryTablesRecursively. Does it look ok to you ? |
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plan.collect { | ||
case InMemoryTableScanExec(_, _, relation) => | ||
getNumInMemoryTableScanExecs(relation.child) + 1 | ||
}.sum | ||
} | ||
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test("withColumn doesn't invalidate cached dataframe") { | ||
var evalCount = 0 | ||
val myUDF = udf((x: String) => { evalCount += 1; "result" }) | ||
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@@ -670,4 +677,139 @@ class CachedTableSuite extends QueryTest with SQLTestUtils with SharedSQLContext | |
assert(spark.read.parquet(path).filter($"id" > 4).count() == 15) | ||
} | ||
} | ||
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test("SPARK-19993 simple subquery caching") { | ||
withTempView("t1", "t2") { | ||
Seq(1).toDF("c1").createOrReplaceTempView("t1") | ||
Seq(1).toDF("c1").createOrReplaceTempView("t2") | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. where is There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @cloud-fan sorry... actually i had some of these tests combined and when i split, i forgot to remove this. Will fix it. |
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sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|NOT EXISTS (SELECT * FROM t1) | ||
""".stripMargin).cache() | ||
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val cachedDs = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|NOT EXISTS (SELECT * FROM t1) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(cachedDs) == 1) | ||
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// Additional predicate in the subquery plan should cause a cache miss | ||
val cachedMissDs = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|NOT EXISTS (SELECT * FROM t1 where c1 = 0) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(cachedMissDs) == 0) | ||
} | ||
} | ||
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test("SPARK-19993 subquery caching with correlated predicates") { | ||
withTempView("t1", "t2") { | ||
Seq(1).toDF("c1").createOrReplaceTempView("t1") | ||
Seq(1).toDF("c1").createOrReplaceTempView("t2") | ||
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// Simple correlated predicate in subquery | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|t1.c1 in (SELECT t2.c1 FROM t2 where t1.c1 = t2.c1) | ||
""".stripMargin).cache() | ||
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val cachedDs = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|t1.c1 in (SELECT t2.c1 FROM t2 where t1.c1 = t2.c1) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(cachedDs) == 1) | ||
} | ||
} | ||
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test("SPARK-19993 subquery with cached underlying relation") { | ||
withTempView("t1", "t2") { | ||
Seq(1).toDF("c1").createOrReplaceTempView("t1") | ||
Seq(1).toDF("c1").createOrReplaceTempView("t2") | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. where is There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @cloud-fan sorry... actually i had some of these tests combined and when i split, i forgot to remove this. Will fix it. |
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spark.catalog.cacheTable("t1") | ||
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// underlying table t1 is cached as well as the query that refers to it. | ||
val ds = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|NOT EXISTS (SELECT * FROM t1) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(ds) == 2) | ||
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val cachedDs = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|NOT EXISTS (SELECT * FROM t1) | ||
""".stripMargin).cache() | ||
assert(getNumInMemoryTableScanExecs(cachedDs.queryExecution.sparkPlan) == 3) | ||
} | ||
} | ||
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test("SPARK-19993 nested subquery caching and scalar + predicate subqueris") { | ||
withTempView("t1", "t2", "t3", "t4") { | ||
Seq(1).toDF("c1").createOrReplaceTempView("t1") | ||
Seq(2).toDF("c1").createOrReplaceTempView("t2") | ||
Seq(1).toDF("c1").createOrReplaceTempView("t3") | ||
Seq(1).toDF("c1").createOrReplaceTempView("t4") | ||
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// Nested predicate subquery | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|c1 IN (SELECT c1 FROM t2 WHERE c1 IN (SELECT c1 FROM t3 WHERE c1 = 1)) | ||
""".stripMargin).cache() | ||
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val cachedDs = | ||
sql( | ||
""" | ||
|SELECT * FROM t1 | ||
|WHERE | ||
|c1 IN (SELECT c1 FROM t2 WHERE c1 IN (SELECT c1 FROM t3 WHERE c1 = 1)) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(cachedDs) == 1) | ||
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// Scalar subquery and predicate subquery | ||
sql( | ||
""" | ||
|SELECT * FROM (SELECT max(c1) FROM t1 GROUP BY c1) | ||
|WHERE | ||
|c1 = (SELECT max(c1) FROM t2 GROUP BY c1) | ||
|OR | ||
|EXISTS (SELECT c1 FROM t3) | ||
|OR | ||
|c1 IN (SELECT c1 FROM t4) | ||
""".stripMargin).cache() | ||
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val cachedDs2 = | ||
sql( | ||
""" | ||
|SELECT * FROM (SELECT max(c1) FROM t1 GROUP BY c1) | ||
|WHERE | ||
|c1 = (SELECT max(c1) FROM t2 GROUP BY c1) | ||
|OR | ||
|EXISTS (SELECT c1 FROM t3) | ||
|OR | ||
|c1 IN (SELECT c1 FROM t4) | ||
""".stripMargin) | ||
assert(getNumInMemoryRelations(cachedDs2) == 1) | ||
} | ||
} | ||
} |
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normalizedPlan