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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ package org.apache.spark.sql.catalyst.optimizer

import scala.collection.mutable

import org.apache.spark.internal.Logging
import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.catalog.{InMemoryCatalog, SessionCatalog}
Expand All @@ -36,7 +37,7 @@ import org.apache.spark.util.Utils
* Optimizers can override this.
*/
abstract class Optimizer(sessionCatalog: SessionCatalog)
extends RuleExecutor[LogicalPlan] {
extends RuleExecutor[LogicalPlan] with Logging {

// Check for structural integrity of the plan in test mode. Currently we only check if a plan is
// still resolved after the execution of each rule.
Expand All @@ -46,7 +47,23 @@ abstract class Optimizer(sessionCatalog: SessionCatalog)

protected def fixedPoint = FixedPoint(SQLConf.get.optimizerMaxIterations)

def batches: Seq[Batch] = {
protected def postAnalysisBatches: Seq[Batch] = {
Batch("Eliminate Distinct", Once, EliminateDistinct) ::
// Technically some of the rules in Finish Analysis are not optimizer rules and belong more
// in the analyzer, because they are needed for correctness (e.g. ComputeCurrentTime).
// However, because we also use the analyzer to canonicalized queries (for view definition),

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"to canonicalized" -> "to canonicalize" ?

// we do not eliminate subqueries or compute current time in the analyzer.
Batch("Finish Analysis", Once,
EliminateSubqueryAliases,
EliminateView,
ReplaceExpressions,
ComputeCurrentTime,
GetCurrentDatabase(sessionCatalog),
RewriteDistinctAggregates,
ReplaceDeduplicateWithAggregate) :: Nil
}

protected def optimizationBatches: Seq[Batch] = {

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In optimizationBatches, some rules can't be excluded. Without them, the affected queries can't be executed. For example,

     Batch("Replace Operators", fixedPoint,
      ReplaceIntersectWithSemiJoin,
      ReplaceExceptWithFilter,
      ReplaceExceptWithAntiJoin,
      ReplaceDistinctWithAggregate)

Can we just introduce a black list?

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So can I do black list of batches?

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yes. We need to exclude Batch("Eliminate Distinct"), Batch("Finish Analysis"), Batch("Replace Operators"), Batch("Pullup Correlated Expressions"), and Batch("RewriteSubquery")

val operatorOptimizationRuleSet =
Seq(
// Operator push down
Expand Down Expand Up @@ -100,19 +117,6 @@ abstract class Optimizer(sessionCatalog: SessionCatalog)
rulesWithoutInferFiltersFromConstraints: _*) :: Nil
}

(Batch("Eliminate Distinct", Once, EliminateDistinct) ::
// Technically some of the rules in Finish Analysis are not optimizer rules and belong more
// in the analyzer, because they are needed for correctness (e.g. ComputeCurrentTime).
// However, because we also use the analyzer to canonicalized queries (for view definition),
// we do not eliminate subqueries or compute current time in the analyzer.
Batch("Finish Analysis", Once,
EliminateSubqueryAliases,
EliminateView,
ReplaceExpressions,
ComputeCurrentTime,
GetCurrentDatabase(sessionCatalog),
RewriteDistinctAggregates,
ReplaceDeduplicateWithAggregate) ::
//////////////////////////////////////////////////////////////////////////////////////////
// Optimizer rules start here
//////////////////////////////////////////////////////////////////////////////////////////
Expand All @@ -121,7 +125,7 @@ abstract class Optimizer(sessionCatalog: SessionCatalog)
// extra operators between two adjacent Union operators.
// - Call CombineUnions again in Batch("Operator Optimizations"),
// since the other rules might make two separate Unions operators adjacent.
Batch("Union", Once,
(Batch("Union", Once,
CombineUnions) ::
Batch("Pullup Correlated Expressions", Once,
PullupCorrelatedPredicates) ::
Expand Down Expand Up @@ -175,6 +179,35 @@ abstract class Optimizer(sessionCatalog: SessionCatalog)
* Override to provide additional rules for the operator optimization batch.
*/
def extendedOperatorOptimizationRules: Seq[Rule[LogicalPlan]] = Nil

override def batches: Seq[Batch] = {
val excludedRules =
SQLConf.get.optimizerExcludedRules.toSeq.flatMap(_.split(",").map(_.trim).filter(!_.isEmpty))

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nit: !_.isEmpty -> _.nonEmpty

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Also, you need to handle case-sensitivity.

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There is an auto-generated field ruleName in Rule, so we do exact name matching (case sensitive).

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You can use Utils.stringToSeq?

val filteredOptimizationBatches = if (excludedRules.isEmpty) {
optimizationBatches
} else {
optimizationBatches.flatMap { batch =>
val filteredRules =
batch.rules.filter { rule =>
val exclude = excludedRules.contains(rule.ruleName)
if (exclude) {
logInfo(s"Optimization rule '${rule.ruleName}' is excluded from the optimizer.")
}
!exclude
}
if (batch.rules == filteredRules) {

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Maybe the if, else if and else can be removed? Just return the filtered batch?

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My understanding is that it is written that way to allow for logging

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It is to:

  1. avoid unnecessary object creation if all rules have been preserved.
  2. avoid empty batches if all rules in the batch have been removed.

Some(batch)
} else if (filteredRules.nonEmpty) {
Some(Batch(batch.name, batch.strategy, filteredRules: _*))
} else {
logInfo(s"Optimization batch '${batch.name}' is excluded from the optimizer " +
s"as all enclosed rules have been excluded.")
None
}
}
}
postAnalysisBatches ++ filteredOptimizationBatches
}
}

/**
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -127,6 +127,14 @@ object SQLConf {
}
}

val OPTIMIZER_EXCLUDED_RULES = buildConf("spark.sql.optimizer.excludedRules")

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If we allow this here, this will affect Spark's caching/uncaching plans and tables inconsistently. For the purpose of this PR, StaticSQLConf.scala would be a perfect place for this.

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Are you talking about SQL cache? I don't think optimizer has anything to do with SQL cache though, since the logical plans used to match cache entries are "analyzed" plans not "optimized" plans.

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Since an optimizer should not change query semantics(results), it should work well for the case @dongjoon-hyun described. If this is mainly used for debugging uses, I think it would be nice to use this conf on runtime.

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+1 on debugging purpose. Still, CacheManager matches the analyzed plan not the optimized plan.

.doc("Configures a list of rules to be disabled in the optimizer, in which the rules are " +
"specified by their rule names and separated by comma. It is not guaranteed that all the " +
"rules in this configuration will eventually be excluded, as some rules are necessary " +

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I don't understand the optimizer at a low level (I'd be one of those users for which it is a blackbox), would you think it would be feasible to enumerate the rules that cannot be excluded ? Maybe even logging a WARNING when validating the config parameters if it contains required rules

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Nice suggestion! @gatorsmile's other suggestion was to introduce a blacklist, in which case this enumeration of rules that cannot be excluded can be made possible. I can do a warning as well.

"for correctness. The optimizer will log the rules that have indeed been excluded.")
.stringConf
.createOptional

val OPTIMIZER_MAX_ITERATIONS = buildConf("spark.sql.optimizer.maxIterations")
.internal()
.doc("The max number of iterations the optimizer and analyzer runs.")
Expand Down Expand Up @@ -1383,6 +1391,8 @@ class SQLConf extends Serializable with Logging {

/** ************************ Spark SQL Params/Hints ******************* */

def optimizerExcludedRules: Option[String] = getConf(OPTIMIZER_EXCLUDED_RULES)

def optimizerMaxIterations: Int = getConf(OPTIMIZER_MAX_ITERATIONS)

def optimizerInSetConversionThreshold: Int = getConf(OPTIMIZER_INSET_CONVERSION_THRESHOLD)
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,84 @@
/*
* 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.plans.PlanTest
import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
import org.apache.spark.sql.internal.SQLConf.OPTIMIZER_EXCLUDED_RULES


class OptimizerRuleExclusionSuite extends PlanTest {

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Any test case for when a required rule is being passed as a "to be excluded" rule ?

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Added :)


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

private def verifyExcludedRules(excludedRuleNames: Seq[String]) {
val optimizer = new SimpleTestOptimizer()
// Batches whose rules are all to be excluded should be removed as a whole.
val excludedBatchNames = optimizer.batches
.filter(batch => batch.rules.forall(rule => excludedRuleNames.contains(rule.ruleName)))
.map(_.name)

withSQLConf(
OPTIMIZER_EXCLUDED_RULES.key -> excludedRuleNames.foldLeft("")((l, r) => l + "," + r)) {
val batches = optimizer.batches
assert(batches.forall(batch => !excludedBatchNames.contains(batch.name)))
assert(
batches
.forall(batch => batch.rules.forall(rule => !excludedRuleNames.contains(rule.ruleName))))
}
}

test("Exclude a single rule from multiple batches") {
verifyExcludedRules(
Seq(
PushPredicateThroughJoin.ruleName))
}

test("Exclude multiple rules from single or multiple batches") {
verifyExcludedRules(
Seq(
CombineUnions.ruleName,
RemoveLiteralFromGroupExpressions.ruleName,
RemoveRepetitionFromGroupExpressions.ruleName))
}

test("Exclude non-existent rule with other valid rules") {
verifyExcludedRules(
Seq(
LimitPushDown.ruleName,
InferFiltersFromConstraints.ruleName,
"DummyRuleName"))
}

test("Verify optimized plan after excluding CombineUnions rule") {
val excludedRules = Seq(
ConvertToLocalRelation.ruleName,
PropagateEmptyRelation.ruleName,
CombineUnions.ruleName)

withSQLConf(
OPTIMIZER_EXCLUDED_RULES.key -> excludedRules.foldLeft("")((l, r) => l + "," + r)) {
val optimizer = new SimpleTestOptimizer()
val originalQuery = testRelation.union(testRelation.union(testRelation)).analyze
val optimized = optimizer.execute(originalQuery)
comparePlans(originalQuery, optimized)
}
}
}