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* 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
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*/
package org.apache.spark.sql.catalyst.optimizer
import scala.collection.immutable.HashSet
import scala.collection.mutable.{ArrayBuffer, Stack}
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.expressions.Literal.{FalseLiteral, TrueLiteral}
import org.apache.spark.sql.catalyst.expressions.aggregate._
import org.apache.spark.sql.catalyst.expressions.objects.AssertNotNull
import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._
/*
* Optimization rules defined in this file should not affect the structure of the logical plan.
*/
/**
* Replaces [[Expression Expressions]] that can be statically evaluated with
* equivalent [[Literal]] values.
*/
object ConstantFolding extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsDown {
// Skip redundant folding of literals. This rule is technically not necessary. Placing this
// here avoids running the next rule for Literal values, which would create a new Literal
// object and running eval unnecessarily.
case l: Literal => l
// Fold expressions that are foldable.
case e if e.foldable => Literal.create(e.eval(EmptyRow), e.dataType)
}
}
}
/**
* Substitutes [[Attribute Attributes]] which can be statically evaluated with their corresponding
* value in conjunctive [[Expression Expressions]]
* eg.
* {{{
* SELECT * FROM table WHERE i = 5 AND j = i + 3
* ==> SELECT * FROM table WHERE i = 5 AND j = 8
* }}}
*
* Approach used:
* - Populate a mapping of attribute => constant value by looking at all the equals predicates
* - Using this mapping, replace occurrence of the attributes with the corresponding constant values
* in the AND node.
*/
object ConstantPropagation extends Rule[LogicalPlan] with PredicateHelper {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case f: Filter =>
val (newCondition, _) = traverse(f.condition, replaceChildren = true, nullIsFalse = true)
if (newCondition.isDefined) {
f.copy(condition = newCondition.get)
} else {
f
}
}
type EqualityPredicates = Seq[((AttributeReference, Literal), BinaryComparison)]
/**
* Traverse a condition as a tree and replace attributes with constant values.
* - On matching [[And]], recursively traverse each children and get propagated mappings.
* If the current node is not child of another [[And]], replace all occurrences of the
* attributes with the corresponding constant values.
* - If a child of [[And]] is [[EqualTo]] or [[EqualNullSafe]], propagate the mapping
* of attribute => constant.
* - On matching [[Or]] or [[Not]], recursively traverse each children, propagate empty mapping.
* - Otherwise, stop traversal and propagate empty mapping.
* @param condition condition to be traversed
* @param replaceChildren whether to replace attributes with constant values in children
* @param nullIsFalse whether a boolean expression result can be considered to false e.g. in the
* case of `WHERE e`, null result of expression `e` means the same as if it
* resulted false
* @return A tuple including:
* 1. Option[Expression]: optional changed condition after traversal
* 2. EqualityPredicates: propagated mapping of attribute => constant
*/
private def traverse(condition: Expression, replaceChildren: Boolean, nullIsFalse: Boolean)
: (Option[Expression], EqualityPredicates) =
condition match {
case e @ EqualTo(left: AttributeReference, right: Literal)
if safeToReplace(left, nullIsFalse) =>
(None, Seq(((left, right), e)))
case e @ EqualTo(left: Literal, right: AttributeReference)
if safeToReplace(right, nullIsFalse) =>
(None, Seq(((right, left), e)))
case e @ EqualNullSafe(left: AttributeReference, right: Literal)
if safeToReplace(left, nullIsFalse) =>
(None, Seq(((left, right), e)))
case e @ EqualNullSafe(left: Literal, right: AttributeReference)
if safeToReplace(right, nullIsFalse) =>
(None, Seq(((right, left), e)))
case a: And =>
val (newLeft, equalityPredicatesLeft) =
traverse(a.left, replaceChildren = false, nullIsFalse)
val (newRight, equalityPredicatesRight) =
traverse(a.right, replaceChildren = false, nullIsFalse)
val equalityPredicates = equalityPredicatesLeft ++ equalityPredicatesRight
val newSelf = if (equalityPredicates.nonEmpty && replaceChildren) {
Some(And(replaceConstants(newLeft.getOrElse(a.left), equalityPredicates),
replaceConstants(newRight.getOrElse(a.right), equalityPredicates)))
} else {
if (newLeft.isDefined || newRight.isDefined) {
Some(And(newLeft.getOrElse(a.left), newRight.getOrElse(a.right)))
} else {
None
}
}
(newSelf, equalityPredicates)
case o: Or =>
// Ignore the EqualityPredicates from children since they are only propagated through And.
val (newLeft, _) = traverse(o.left, replaceChildren = true, nullIsFalse)
val (newRight, _) = traverse(o.right, replaceChildren = true, nullIsFalse)
val newSelf = if (newLeft.isDefined || newRight.isDefined) {
Some(Or(left = newLeft.getOrElse(o.left), right = newRight.getOrElse((o.right))))
} else {
None
}
(newSelf, Seq.empty)
case n: Not =>
// Ignore the EqualityPredicates from children since they are only propagated through And.
val (newChild, _) = traverse(n.child, replaceChildren = true, nullIsFalse = false)
(newChild.map(Not), Seq.empty)
case _ => (None, Seq.empty)
}
// We need to take into account if an attribute is nullable and the context of the conjunctive
// expression. E.g. `SELECT * FROM t WHERE NOT(c = 1 AND c + 1 = 1)` where attribute `c` can be
// substituted into `1 + 1 = 1` if 'c' isn't nullable. If 'c' is nullable then the enclosing
// NOT prevents us to do the substitution as NOT flips the context (`nullIsFalse`) of what a
// null result of the enclosed expression means.
private def safeToReplace(ar: AttributeReference, nullIsFalse: Boolean) =
!ar.nullable || nullIsFalse
private def replaceConstants(condition: Expression, equalityPredicates: EqualityPredicates)
: Expression = {
val constantsMap = AttributeMap(equalityPredicates.map(_._1))
val predicates = equalityPredicates.map(_._2).toSet
def replaceConstants0(expression: Expression) = expression transform {
case a: AttributeReference => constantsMap.getOrElse(a, a)
}
condition transform {
case e @ EqualTo(_, _) if !predicates.contains(e) => replaceConstants0(e)
case e @ EqualNullSafe(_, _) if !predicates.contains(e) => replaceConstants0(e)
}
}
}
/**
* Reorder associative integral-type operators and fold all constants into one.
*/
object ReorderAssociativeOperator extends Rule[LogicalPlan] {
private def flattenAdd(
expression: Expression,
groupSet: ExpressionSet): Seq[Expression] = expression match {
case expr @ Add(l, r) if !groupSet.contains(expr) =>
flattenAdd(l, groupSet) ++ flattenAdd(r, groupSet)
case other => other :: Nil
}
private def flattenMultiply(
expression: Expression,
groupSet: ExpressionSet): Seq[Expression] = expression match {
case expr @ Multiply(l, r) if !groupSet.contains(expr) =>
flattenMultiply(l, groupSet) ++ flattenMultiply(r, groupSet)
case other => other :: Nil
}
private def collectGroupingExpressions(plan: LogicalPlan): ExpressionSet = plan match {
case Aggregate(groupingExpressions, aggregateExpressions, child) =>
ExpressionSet.apply(groupingExpressions)
case _ => ExpressionSet(Seq.empty)
}
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan =>
// We have to respect aggregate expressions which exists in grouping expressions when plan
// is an Aggregate operator, otherwise the optimized expression could not be derived from
// grouping expressions.
val groupingExpressionSet = collectGroupingExpressions(q)
q transformExpressionsDown {
case a: Add if a.deterministic && a.dataType.isInstanceOf[IntegralType] =>
val (foldables, others) = flattenAdd(a, groupingExpressionSet).partition(_.foldable)
if (foldables.size > 1) {
val foldableExpr = foldables.reduce((x, y) => Add(x, y))
val c = Literal.create(foldableExpr.eval(EmptyRow), a.dataType)
if (others.isEmpty) c else Add(others.reduce((x, y) => Add(x, y)), c)
} else {
a
}
case m: Multiply if m.deterministic && m.dataType.isInstanceOf[IntegralType] =>
val (foldables, others) = flattenMultiply(m, groupingExpressionSet).partition(_.foldable)
if (foldables.size > 1) {
val foldableExpr = foldables.reduce((x, y) => Multiply(x, y))
val c = Literal.create(foldableExpr.eval(EmptyRow), m.dataType)
if (others.isEmpty) c else Multiply(others.reduce((x, y) => Multiply(x, y)), c)
} else {
m
}
}
}
}
/**
* Optimize IN predicates:
* 1. Converts the predicate to false when the list is empty and
* the value is not nullable.
* 2. Removes literal repetitions.
* 3. Replaces [[In (value, seq[Literal])]] with optimized version
* [[InSet (value, HashSet[Literal])]] which is much faster.
*/
object OptimizeIn extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsDown {
case In(v, list) if list.isEmpty =>
// When v is not nullable, the following expression will be optimized
// to FalseLiteral which is tested in OptimizeInSuite.scala
If(IsNotNull(v), FalseLiteral, Literal(null, BooleanType))
case expr @ In(v, list) if expr.inSetConvertible =>
val newList = ExpressionSet(list).toSeq
if (newList.length == 1
// TODO: `EqualTo` for structural types are not working. Until SPARK-24443 is addressed,
// TODO: we exclude them in this rule.
&& !v.isInstanceOf[CreateNamedStruct]
&& !newList.head.isInstanceOf[CreateNamedStruct]) {
EqualTo(v, newList.head)
} else if (newList.length > SQLConf.get.optimizerInSetConversionThreshold) {
val hSet = newList.map(e => e.eval(EmptyRow))
InSet(v, HashSet() ++ hSet)
} else if (newList.length < list.length) {
expr.copy(list = newList)
} else { // newList.length == list.length && newList.length > 1
expr
}
}
}
}
/**
* Simplifies boolean expressions:
* 1. Simplifies expressions whose answer can be determined without evaluating both sides.
* 2. Eliminates / extracts common factors.
* 3. Merge same expressions
* 4. Removes `Not` operator.
*/
object BooleanSimplification extends Rule[LogicalPlan] with PredicateHelper {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsUp {
case TrueLiteral And e => e
case e And TrueLiteral => e
case FalseLiteral Or e => e
case e Or FalseLiteral => e
case FalseLiteral And _ => FalseLiteral
case _ And FalseLiteral => FalseLiteral
case TrueLiteral Or _ => TrueLiteral
case _ Or TrueLiteral => TrueLiteral
case a And b if Not(a).semanticEquals(b) =>
If(IsNull(a), Literal.create(null, a.dataType), FalseLiteral)
case a And b if a.semanticEquals(Not(b)) =>
If(IsNull(b), Literal.create(null, b.dataType), FalseLiteral)
case a Or b if Not(a).semanticEquals(b) =>
If(IsNull(a), Literal.create(null, a.dataType), TrueLiteral)
case a Or b if a.semanticEquals(Not(b)) =>
If(IsNull(b), Literal.create(null, b.dataType), TrueLiteral)
case a And b if a.semanticEquals(b) => a
case a Or b if a.semanticEquals(b) => a
// The following optimizations are applicable only when the operands are not nullable,
// since the three-value logic of AND and OR are different in NULL handling.
// See the chart:
// +---------+---------+---------+---------+
// | operand | operand | OR | AND |
// +---------+---------+---------+---------+
// | TRUE | TRUE | TRUE | TRUE |
// | TRUE | FALSE | TRUE | FALSE |
// | FALSE | FALSE | FALSE | FALSE |
// | UNKNOWN | TRUE | TRUE | UNKNOWN |
// | UNKNOWN | FALSE | UNKNOWN | FALSE |
// | UNKNOWN | UNKNOWN | UNKNOWN | UNKNOWN |
// +---------+---------+---------+---------+
// (NULL And (NULL Or FALSE)) = NULL, but (NULL And FALSE) = FALSE. Thus, a can't be nullable.
case a And (b Or c) if !a.nullable && Not(a).semanticEquals(b) => And(a, c)
// (NULL And (FALSE Or NULL)) = NULL, but (NULL And FALSE) = FALSE. Thus, a can't be nullable.
case a And (b Or c) if !a.nullable && Not(a).semanticEquals(c) => And(a, b)
// ((NULL Or FALSE) And NULL) = NULL, but (FALSE And NULL) = FALSE. Thus, c can't be nullable.
case (a Or b) And c if !c.nullable && a.semanticEquals(Not(c)) => And(b, c)
// ((FALSE Or NULL) And NULL) = NULL, but (FALSE And NULL) = FALSE. Thus, c can't be nullable.
case (a Or b) And c if !c.nullable && b.semanticEquals(Not(c)) => And(a, c)
// (NULL Or (NULL And TRUE)) = NULL, but (NULL Or TRUE) = TRUE. Thus, a can't be nullable.
case a Or (b And c) if !a.nullable && Not(a).semanticEquals(b) => Or(a, c)
// (NULL Or (TRUE And NULL)) = NULL, but (NULL Or TRUE) = TRUE. Thus, a can't be nullable.
case a Or (b And c) if !a.nullable && Not(a).semanticEquals(c) => Or(a, b)
// ((NULL And TRUE) Or NULL) = NULL, but (TRUE Or NULL) = TRUE. Thus, c can't be nullable.
case (a And b) Or c if !c.nullable && a.semanticEquals(Not(c)) => Or(b, c)
// ((TRUE And NULL) Or NULL) = NULL, but (TRUE Or NULL) = TRUE. Thus, c can't be nullable.
case (a And b) Or c if !c.nullable && b.semanticEquals(Not(c)) => Or(a, c)
// Common factor elimination for conjunction
case and @ (left And right) =>
// 1. Split left and right to get the disjunctive predicates,
// i.e. lhs = (a, b), rhs = (a, c)
// 2. Find the common predict between lhsSet and rhsSet, i.e. common = (a)
// 3. Remove common predict from lhsSet and rhsSet, i.e. ldiff = (b), rdiff = (c)
// 4. Apply the formula, get the optimized predicate: common || (ldiff && rdiff)
val lhs = splitDisjunctivePredicates(left)
val rhs = splitDisjunctivePredicates(right)
val common = lhs.filter(e => rhs.exists(e.semanticEquals))
if (common.isEmpty) {
// No common factors, return the original predicate
and
} else {
val ldiff = lhs.filterNot(e => common.exists(e.semanticEquals))
val rdiff = rhs.filterNot(e => common.exists(e.semanticEquals))
if (ldiff.isEmpty || rdiff.isEmpty) {
// (a || b || c || ...) && (a || b) => (a || b)
common.reduce(Or)
} else {
// (a || b || c || ...) && (a || b || d || ...) =>
// ((c || ...) && (d || ...)) || a || b
(common :+ And(ldiff.reduce(Or), rdiff.reduce(Or))).reduce(Or)
}
}
// Common factor elimination for disjunction
case or @ (left Or right) =>
// 1. Split left and right to get the conjunctive predicates,
// i.e. lhs = (a, b), rhs = (a, c)
// 2. Find the common predict between lhsSet and rhsSet, i.e. common = (a)
// 3. Remove common predict from lhsSet and rhsSet, i.e. ldiff = (b), rdiff = (c)
// 4. Apply the formula, get the optimized predicate: common && (ldiff || rdiff)
val lhs = splitConjunctivePredicates(left)
val rhs = splitConjunctivePredicates(right)
val common = lhs.filter(e => rhs.exists(e.semanticEquals))
if (common.isEmpty) {
// No common factors, return the original predicate
or
} else {
val ldiff = lhs.filterNot(e => common.exists(e.semanticEquals))
val rdiff = rhs.filterNot(e => common.exists(e.semanticEquals))
if (ldiff.isEmpty || rdiff.isEmpty) {
// (a && b) || (a && b && c && ...) => a && b
common.reduce(And)
} else {
// (a && b && c && ...) || (a && b && d && ...) =>
// ((c && ...) || (d && ...)) && a && b
(common :+ Or(ldiff.reduce(And), rdiff.reduce(And))).reduce(And)
}
}
case Not(TrueLiteral) => FalseLiteral
case Not(FalseLiteral) => TrueLiteral
case Not(a GreaterThan b) => LessThanOrEqual(a, b)
case Not(a GreaterThanOrEqual b) => LessThan(a, b)
case Not(a LessThan b) => GreaterThanOrEqual(a, b)
case Not(a LessThanOrEqual b) => GreaterThan(a, b)
case Not(a Or b) => And(Not(a), Not(b))
case Not(a And b) => Or(Not(a), Not(b))
case Not(Not(e)) => e
case Not(IsNull(e)) => IsNotNull(e)
case Not(IsNotNull(e)) => IsNull(e)
}
}
}
/**
* Simplifies binary comparisons with semantically-equal expressions:
* 1) Replace '<=>' with 'true' literal.
* 2) Replace '=', '<=', and '>=' with 'true' literal if both operands are non-nullable.
* 3) Replace '<' and '>' with 'false' literal if both operands are non-nullable.
*/
object SimplifyBinaryComparison
extends Rule[LogicalPlan] with PredicateHelper with ConstraintHelper {
private def canSimplifyComparison(
left: Expression,
right: Expression,
notNullExpressions: => ExpressionSet): Boolean = {
if (left.semanticEquals(right)) {
(!left.nullable && !right.nullable) || notNullExpressions.contains(left)
} else {
false
}
}
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case l: LogicalPlan =>
lazy val notNullExpressions = ExpressionSet(l match {
case Filter(fc, _) =>
splitConjunctivePredicates(fc).collect {
case i: IsNotNull => i.child
}
case _ => Seq.empty
})
l transformExpressionsUp {
// True with equality
case a EqualNullSafe b if a.semanticEquals(b) => TrueLiteral
case a EqualTo b if canSimplifyComparison(a, b, notNullExpressions) => TrueLiteral
case a GreaterThanOrEqual b if canSimplifyComparison(a, b, notNullExpressions) =>
TrueLiteral
case a LessThanOrEqual b if canSimplifyComparison(a, b, notNullExpressions) => TrueLiteral
// False with inequality
case a GreaterThan b if canSimplifyComparison(a, b, notNullExpressions) => FalseLiteral
case a LessThan b if canSimplifyComparison(a, b, notNullExpressions) => FalseLiteral
}
}
}
/**
* Simplifies conditional expressions (if / case).
*/
object SimplifyConditionals extends Rule[LogicalPlan] with PredicateHelper {
private def falseOrNullLiteral(e: Expression): Boolean = e match {
case FalseLiteral => true
case Literal(null, _) => true
case _ => false
}
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsUp {
case If(TrueLiteral, trueValue, _) => trueValue
case If(FalseLiteral, _, falseValue) => falseValue
case If(Literal(null, _), _, falseValue) => falseValue
case If(cond, trueValue, falseValue)
if cond.deterministic && trueValue.semanticEquals(falseValue) => trueValue
case e @ CaseWhen(branches, elseValue) if branches.exists(x => falseOrNullLiteral(x._1)) =>
// If there are branches that are always false, remove them.
// If there are no more branches left, just use the else value.
// Note that these two are handled together here in a single case statement because
// otherwise we cannot determine the data type for the elseValue if it is None (i.e. null).
val newBranches = branches.filter(x => !falseOrNullLiteral(x._1))
if (newBranches.isEmpty) {
elseValue.getOrElse(Literal.create(null, e.dataType))
} else {
e.copy(branches = newBranches)
}
case CaseWhen(branches, _) if branches.headOption.map(_._1).contains(TrueLiteral) =>
// If the first branch is a true literal, remove the entire CaseWhen and use the value
// from that. Note that CaseWhen.branches should never be empty, and as a result the
// headOption (rather than head) added above is just an extra (and unnecessary) safeguard.
branches.head._2
case CaseWhen(branches, _) if branches.exists(_._1 == TrueLiteral) =>
// a branch with a true condition eliminates all following branches,
// these branches can be pruned away
val (h, t) = branches.span(_._1 != TrueLiteral)
CaseWhen( h :+ t.head, None)
case e @ CaseWhen(branches, Some(elseValue))
if branches.forall(_._2.semanticEquals(elseValue)) =>
// For non-deterministic conditions with side effect, we can not remove it, or change
// the ordering. As a result, we try to remove the deterministic conditions from the tail.
var hitNonDeterministicCond = false
var i = branches.length
while (i > 0 && !hitNonDeterministicCond) {
hitNonDeterministicCond = !branches(i - 1)._1.deterministic
if (!hitNonDeterministicCond) {
i -= 1
}
}
if (i == 0) {
elseValue
} else {
e.copy(branches = branches.take(i).map(branch => (branch._1, elseValue)))
}
}
}
}
/**
* Simplifies LIKE expressions that do not need full regular expressions to evaluate the condition.
* For example, when the expression is just checking to see if a string starts with a given
* pattern.
*/
object LikeSimplification extends Rule[LogicalPlan] {
// if guards below protect from escapes on trailing %.
// Cases like "something\%" are not optimized, but this does not affect correctness.
private val startsWith = "([^_%]+)%".r
private val endsWith = "%([^_%]+)".r
private val startsAndEndsWith = "([^_%]+)%([^_%]+)".r
private val contains = "%([^_%]+)%".r
private val equalTo = "([^_%]*)".r
def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
case Like(input, Literal(pattern, StringType), escapeChar) =>
if (pattern == null) {
// If pattern is null, return null value directly, since "col like null" == null.
Literal(null, BooleanType)
} else {
val escapeStr = String.valueOf(escapeChar)
pattern.toString match {
case startsWith(prefix) if !prefix.endsWith(escapeStr) =>
StartsWith(input, Literal(prefix))
case endsWith(postfix) =>
EndsWith(input, Literal(postfix))
// 'a%a' pattern is basically same with 'a%' && '%a'.
// However, the additional `Length` condition is required to prevent 'a' match 'a%a'.
case startsAndEndsWith(prefix, postfix) if !prefix.endsWith(escapeStr) =>
And(GreaterThanOrEqual(Length(input), Literal(prefix.length + postfix.length)),
And(StartsWith(input, Literal(prefix)), EndsWith(input, Literal(postfix))))
case contains(infix) if !infix.endsWith(escapeStr) =>
Contains(input, Literal(infix))
case equalTo(str) =>
EqualTo(input, Literal(str))
case _ => Like(input, Literal.create(pattern, StringType), escapeChar)
}
}
}
}
/**
* Replaces [[Expression Expressions]] that can be statically evaluated with
* equivalent [[Literal]] values. This rule is more specific with
* Null value propagation from bottom to top of the expression tree.
*/
object NullPropagation extends Rule[LogicalPlan] {
private def isNullLiteral(e: Expression): Boolean = e match {
case Literal(null, _) => true
case _ => false
}
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsUp {
case e @ WindowExpression(Cast(Literal(0L, _), _, _), _) =>
Cast(Literal(0L), e.dataType, Option(SQLConf.get.sessionLocalTimeZone))
case e @ AggregateExpression(Count(exprs), _, _, _, _) if exprs.forall(isNullLiteral) =>
Cast(Literal(0L), e.dataType, Option(SQLConf.get.sessionLocalTimeZone))
case ae @ AggregateExpression(Count(exprs), _, false, _, _) if !exprs.exists(_.nullable) =>
// This rule should be only triggered when isDistinct field is false.
ae.copy(aggregateFunction = Count(Literal(1)))
case IsNull(c) if !c.nullable => Literal.create(false, BooleanType)
case IsNotNull(c) if !c.nullable => Literal.create(true, BooleanType)
case EqualNullSafe(Literal(null, _), r) => IsNull(r)
case EqualNullSafe(l, Literal(null, _)) => IsNull(l)
case AssertNotNull(c, _) if !c.nullable => c
// For Coalesce, remove null literals.
case e @ Coalesce(children) =>
val newChildren = children.filterNot(isNullLiteral)
if (newChildren.isEmpty) {
Literal.create(null, e.dataType)
} else if (newChildren.length == 1) {
newChildren.head
} else {
Coalesce(newChildren)
}
// If the value expression is NULL then transform the In expression to null literal.
case In(Literal(null, _), _) => Literal.create(null, BooleanType)
case InSubquery(Seq(Literal(null, _)), _) => Literal.create(null, BooleanType)
// Non-leaf NullIntolerant expressions will return null, if at least one of its children is
// a null literal.
case e: NullIntolerant if e.children.exists(isNullLiteral) =>
Literal.create(null, e.dataType)
}
}
}
/**
* Replace attributes with aliases of the original foldable expressions if possible.
* Other optimizations will take advantage of the propagated foldable expressions. For example,
* this rule can optimize
* {{{
* SELECT 1.0 x, 'abc' y, Now() z ORDER BY x, y, 3
* }}}
* to
* {{{
* SELECT 1.0 x, 'abc' y, Now() z ORDER BY 1.0, 'abc', Now()
* }}}
* and other rules can further optimize it and remove the ORDER BY operator.
*/
object FoldablePropagation extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = {
var foldableMap = AttributeMap(plan.flatMap {
case Project(projectList, _) => projectList.collect {
case a: Alias if a.child.foldable => (a.toAttribute, a)
}
case _ => Nil
})
val replaceFoldable: PartialFunction[Expression, Expression] = {
case a: AttributeReference if foldableMap.contains(a) => foldableMap(a)
}
if (foldableMap.isEmpty) {
plan
} else {
CleanupAliases(plan.transformUp {
// We can only propagate foldables for a subset of unary nodes.
case u: UnaryNode if foldableMap.nonEmpty && canPropagateFoldables(u) =>
u.transformExpressions(replaceFoldable)
// Join derives the output attributes from its child while they are actually not the
// same attributes. For example, the output of outer join is not always picked from its
// children, but can also be null. We should exclude these miss-derived attributes when
// propagating the foldable expressions.
// TODO(cloud-fan): It seems more reasonable to use new attributes as the output attributes
// of outer join.
case j @ Join(left, right, joinType, _, _) if foldableMap.nonEmpty =>
val newJoin = j.transformExpressions(replaceFoldable)
val missDerivedAttrsSet: AttributeSet = AttributeSet(joinType match {
case _: InnerLike | LeftExistence(_) => Nil
case LeftOuter => right.output
case RightOuter => left.output
case FullOuter => left.output ++ right.output
})
foldableMap = AttributeMap(foldableMap.baseMap.values.filterNot {
case (attr, _) => missDerivedAttrsSet.contains(attr)
}.toSeq)
newJoin
// We can not replace the attributes in `Expand.output`. If there are other non-leaf
// operators that have the `output` field, we should put them here too.
case expand: Expand if foldableMap.nonEmpty =>
expand.copy(projections = expand.projections.map { projection =>
projection.map(_.transform(replaceFoldable))
})
// For other plans, they are not safe to apply foldable propagation, and they should not
// propagate foldable expressions from children.
case other if foldableMap.nonEmpty =>
val childrenOutputSet = AttributeSet(other.children.flatMap(_.output))
foldableMap = AttributeMap(foldableMap.baseMap.values.filterNot {
case (attr, _) => childrenOutputSet.contains(attr)
}.toSeq)
other
})
}
}
/**
* Whitelist of all [[UnaryNode]]s for which allow foldable propagation.
*/
private def canPropagateFoldables(u: UnaryNode): Boolean = u match {
case _: Project => true
case _: Filter => true
case _: SubqueryAlias => true
case _: Aggregate => true
case _: Window => true
case _: Sample => true
case _: GlobalLimit => true
case _: LocalLimit => true
case _: Generate => true
case _: Distinct => true
case _: AppendColumns => true
case _: AppendColumnsWithObject => true
case _: RepartitionByExpression => true
case _: Repartition => true
case _: Sort => true
case _: TypedFilter => true
case _ => false
}
}
/**
* Removes [[Cast Casts]] that are unnecessary because the input is already the correct type.
*/
object SimplifyCasts extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
case Cast(e, dataType, _) if e.dataType == dataType => e
case c @ Cast(e, dataType, _) => (e.dataType, dataType) match {
case (ArrayType(from, false), ArrayType(to, true)) if from == to => e
case (MapType(fromKey, fromValue, false), MapType(toKey, toValue, true))
if fromKey == toKey && fromValue == toValue => e
case _ => c
}
}
}
/**
* Removes nodes that are not necessary.
*/
object RemoveDispensableExpressions extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
case UnaryPositive(child) => child
}
}
/**
* Removes the inner case conversion expressions that are unnecessary because
* the inner conversion is overwritten by the outer one.
*/
object SimplifyCaseConversionExpressions extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsUp {
case Upper(Upper(child)) => Upper(child)
case Upper(Lower(child)) => Upper(child)
case Lower(Upper(child)) => Lower(child)
case Lower(Lower(child)) => Lower(child)
}
}
}
/**
* Combine nested [[Concat]] expressions.
*/
object CombineConcats extends Rule[LogicalPlan] {
private def flattenConcats(concat: Concat): Concat = {
val stack = Stack[Expression](concat)
val flattened = ArrayBuffer.empty[Expression]
while (stack.nonEmpty) {
stack.pop() match {
case Concat(children) =>
stack.pushAll(children.reverse)
// If `spark.sql.function.concatBinaryAsString` is false, nested `Concat` exprs possibly
// have `Concat`s with binary output. Since `TypeCoercion` casts them into strings,
// we need to handle the case to combine all nested `Concat`s.
case c @ Cast(Concat(children), StringType, _) =>
val newChildren = children.map { e => c.copy(child = e) }
stack.pushAll(newChildren.reverse)
case child =>
flattened += child
}
}
Concat(flattened)
}
private def hasNestedConcats(concat: Concat): Boolean = concat.children.exists {
case c: Concat => true
case c @ Cast(Concat(children), StringType, _) => true
case _ => false
}
def apply(plan: LogicalPlan): LogicalPlan = plan.transformExpressionsDown {
case concat: Concat if hasNestedConcats(concat) =>
flattenConcats(concat)
}
}
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