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[SPARK-15076][SQL] Add ReorderAssociativeOperator optimizer
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## What changes were proposed in this pull request?

This issue add a new optimizer `ReorderAssociativeOperator` by taking advantage of integral associative property. Currently, Spark works like the following.

1) Can optimize `1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 + 9 + a` into `45 + a`.
2) Cannot optimize `a + 1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 + 9`.

This PR can handle Case 2 for **Add/Multiply** expression whose data types are `ByteType`, `ShortType`, `IntegerType`, and `LongType`. The followings are the plan comparison between `before` and `after` this issue.

**Before**
```scala
scala> sql("select a+1+2+3+4+5+6+7+8+9 from (select explode(array(1)) a)").explain
== Physical Plan ==
WholeStageCodegen
:  +- Project [(((((((((a#7 + 1) + 2) + 3) + 4) + 5) + 6) + 7) + 8) + 9) AS (((((((((a + 1) + 2) + 3) + 4) + 5) + 6) + 7) + 8) + 9)#8]
:     +- INPUT
+- Generate explode([1]), false, false, [a#7]
   +- Scan OneRowRelation[]
scala> sql("select a*1*2*3*4*5*6*7*8*9 from (select explode(array(1)) a)").explain
== Physical Plan ==
*Project [(((((((((a#18 * 1) * 2) * 3) * 4) * 5) * 6) * 7) * 8) * 9) AS (((((((((a * 1) * 2) * 3) * 4) * 5) * 6) * 7) * 8) * 9)#19]
+- Generate explode([1]), false, false, [a#18]
   +- Scan OneRowRelation[]
```

**After**
```scala
scala> sql("select a+1+2+3+4+5+6+7+8+9 from (select explode(array(1)) a)").explain
== Physical Plan ==
WholeStageCodegen
:  +- Project [(a#7 + 45) AS (((((((((a + 1) + 2) + 3) + 4) + 5) + 6) + 7) + 8) + 9)#8]
:     +- INPUT
+- Generate explode([1]), false, false, [a#7]
   +- Scan OneRowRelation[]
scala> sql("select a*1*2*3*4*5*6*7*8*9 from (select explode(array(1)) a)").explain
== Physical Plan ==
*Project [(a#18 * 362880) AS (((((((((a * 1) * 2) * 3) * 4) * 5) * 6) * 7) * 8) * 9)#19]
+- Generate explode([1]), false, false, [a#18]
   +- Scan OneRowRelation[]
```

This PR is greatly generalized by cloud-fan 's key ideas; he should be credited for the work he did.

## How was this patch tested?

Pass the Jenkins tests including new testsuite.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #12850 from dongjoon-hyun/SPARK-15076.
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dongjoon-hyun authored and cloud-fan committed Jun 2, 2016
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Original file line number Diff line number Diff line change
Expand Up @@ -94,6 +94,7 @@ abstract class Optimizer(sessionCatalog: SessionCatalog, conf: CatalystConf)
FoldablePropagation,
OptimizeIn(conf),
ConstantFolding,
ReorderAssociativeOperator,
LikeSimplification,
BooleanSimplification,
SimplifyConditionals,
Expand Down Expand Up @@ -737,6 +738,44 @@ object InferFiltersFromConstraints extends Rule[LogicalPlan] with PredicateHelpe
}
}

/**
* Reorder associative integral-type operators and fold all constants into one.
*/
object ReorderAssociativeOperator extends Rule[LogicalPlan] {
private def flattenAdd(e: Expression): Seq[Expression] = e match {
case Add(l, r) => flattenAdd(l) ++ flattenAdd(r)
case other => other :: Nil
}

private def flattenMultiply(e: Expression): Seq[Expression] = e match {
case Multiply(l, r) => flattenMultiply(l) ++ flattenMultiply(r)
case other => other :: Nil
}

def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case q: LogicalPlan => q transformExpressionsDown {
case a: Add if a.deterministic && a.dataType.isInstanceOf[IntegralType] =>
val (foldables, others) = flattenAdd(a).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).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
}
}
}
}

/**
* Replaces [[Expression Expressions]] that can be statically evaluated with
* equivalent [[Literal]] values.
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,63 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* 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
* limitations under the License.
*/

package org.apache.spark.sql.catalyst.optimizer

import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.dsl.plans._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.PlanTest
import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan}
import org.apache.spark.sql.catalyst.rules.RuleExecutor

class ReorderAssociativeOperatorSuite extends PlanTest {

object Optimize extends RuleExecutor[LogicalPlan] {
val batches =
Batch("ReorderAssociativeOperator", Once,
ReorderAssociativeOperator) :: Nil
}

val testRelation = LocalRelation('a.int, 'b.int, 'c.int)

test("Reorder associative operators") {
val originalQuery =
testRelation
.select(
(Literal(3) + ((Literal(1) + 'a) + 2)) + 4,
'b * 1 * 2 * 3 * 4,
('b + 1) * 2 * 3 * 4,
'a + 1 + 'b + 2 + 'c + 3,
'a + 1 + 'b * 2 + 'c + 3,
Rand(0) * 1 * 2 * 3 * 4)

val optimized = Optimize.execute(originalQuery.analyze)

val correctAnswer =
testRelation
.select(
('a + 10).as("((3 + ((1 + a) + 2)) + 4)"),
('b * 24).as("((((b * 1) * 2) * 3) * 4)"),
(('b + 1) * 24).as("((((b + 1) * 2) * 3) * 4)"),
('a + 'b + 'c + 6).as("(((((a + 1) + b) + 2) + c) + 3)"),
('a + 'b * 2 + 'c + 4).as("((((a + 1) + (b * 2)) + c) + 3)"),
Rand(0) * 1 * 2 * 3 * 4)
.analyze

comparePlans(optimized, correctAnswer)
}
}

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