SPARKC-312: Implementing FilterOptimizer #1019
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| Original file line number | Diff line number | Diff line change |
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| package org.apache.spark.sql.cassandra | ||
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| import org.apache.spark.sql.sources._ | ||
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| /** | ||
| * Optimizer will try to transform pushdown filter into `sum of products`. | ||
| * So that the filter like | ||
| * '(field1 < 3 OR field1 > 7) AND (field2 = 'val1' OR field2 = 'val2')' | ||
| * will become equivalent | ||
| * 'field1 < 3 AND field2 = "val1" OR field1 < 3 AND field2 = "val2" OR | ||
| * field1 > 7 AND field2 = "val1" OR field1 > 7 AND field2 = "val2"' | ||
| * | ||
| * @param filters Array of logical statements [[org.apache.spark.sql.sources.Filter]] | ||
| * that forms `where`-clause with `AND` operator, for example: | ||
| * val Array(f1, f2, ... fn) = ... // such that `where f1 AND f2 AND ... AND fn` | ||
| * | ||
| */ | ||
| class FiltersOptimizer(filters: Array[Filter]) { | ||
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There was a problem hiding this comment. I'm a little confused why there is a separate class here, do we ever use this without calling .build() immediately after? |
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| private val fullFilterAst = | ||
| if (filters.nonEmpty) Some(filters.reduce((left, right) => And(left, right))) else None | ||
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| import FiltersOptimizer._ | ||
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| def build(): List[Array[Filter]] = fullFilterAst match { | ||
| case Some(ast) => (toNNF andThen toDNF andThen traverse andThen groupByAnd).apply(ast) | ||
| case None => List.empty | ||
| } | ||
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| } | ||
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| object FiltersOptimizer{ | ||
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| def apply(filters: Array[Filter]): FiltersOptimizer = new FiltersOptimizer(filters) | ||
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| private[cassandra] def dist(predL: Filter, predR: Filter): Filter = (predL, predR) match { | ||
| case (Or(l, r), p) => Or(dist(l, p), dist(r, p)) | ||
| case (p, Or(l, r)) => Or(dist(p, l), dist(p, r)) | ||
| case (l, r) => And(l, r) | ||
| } | ||
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| /** The 'toNNF' function converts expressions to negation normal form. This | ||
| * function is total: it's defined for all expressions, not just those which | ||
| * only use negation, conjunction and disjunction, although all expressions in | ||
| * negation normal form do in fact only use those connectives. | ||
| * | ||
| * Then de Morgan's laws are applied to convert negated | ||
| * conjunctions and disjunctions into the conjunction or disjunction of the | ||
| * negation of their conjuncts: ¬(φ ∧ ψ) is converted to (¬φ ∨ ¬ψ) | ||
| * while ¬(φ ∨ ψ) becomes (¬φ ∧ ¬ψ). | ||
| */ | ||
| private[cassandra] val toNNF: Filter => Filter = { | ||
| case a@(EqualTo(_, _) | EqualNullSafe(_, _) | GreaterThan(_, _) | | ||
| GreaterThanOrEqual(_, _) | LessThan(_, _) | LessThanOrEqual(_, _) | | ||
| In(_, _) | IsNull(_) | IsNotNull(_) | | ||
| StringStartsWith(_, _) | StringEndsWith(_, _) | StringContains(_, _)) => a | ||
| case a@Not(EqualTo(_, _) | EqualNullSafe(_, _) | In(_, _) | | ||
| StringStartsWith(_, _) | StringEndsWith(_, _) | StringContains(_, _)) => a | ||
| case Not(GreaterThan(a, v)) => LessThanOrEqual(a, v) | ||
| case Not(LessThanOrEqual(a, v)) => GreaterThan(a, v) | ||
| case Not(LessThan(a, v)) => GreaterThanOrEqual(a, v) | ||
| case Not(GreaterThanOrEqual(a, v)) => LessThan(a, v) | ||
| case Not(IsNull(a)) => IsNotNull(a) | ||
| case Not(IsNotNull(a)) => IsNull(a) | ||
| case Not(Not(p)) => p | ||
| case And(l, r) => And(toNNF(l), toNNF(r)) | ||
| case Not(And(l, r)) => toNNF(Or(Not(l), Not(r))) | ||
| case Or(l, r) => Or(toNNF(l), toNNF(r)) | ||
| case Not(Or(l, r)) => toNNF(And(Not(l), Not(r))) | ||
| case p => p | ||
| } | ||
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| /** The 'toDNF' function converts expressions to disjunctive normal form: a | ||
| * disjunction of clauses, where a clause is a conjunction of literals | ||
| * (variables and negated variables). | ||
| * | ||
| * The conversion is carried out by first converting the expression into | ||
| * negation normal form, and then applying the distributive law. | ||
| */ | ||
| private[cassandra] val toDNF: Filter => Filter = { | ||
| case And(l, r) => dist(toDNF(l), toDNF(r)) | ||
| case Or(l, r) => Or(toDNF(l), toDNF(r)) | ||
| case p => p | ||
| } | ||
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| /** | ||
| * Traverse over disjunctive clauses of AST | ||
| */ | ||
| private[cassandra] val traverse: Filter => List[Filter] = { | ||
| case Or(l, r) => traverse(l) ++ traverse(r) | ||
| case a => a :: Nil | ||
| } | ||
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| /** | ||
| * Group all conjunctive clauses into Array[Filter] | ||
| * f1 && f2 && ... && fn => Array(f1, f2, ... fn) | ||
| */ | ||
| private[cassandra] val andToArray: Filter => Array[Filter] = { | ||
| case And(l, r) => andToArray(l) ++ andToArray(r) | ||
| case a => Array(a) | ||
| } | ||
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| private[cassandra] val groupByAnd: List[Filter] => List[Array[Filter]] = _.map(andToArray) | ||
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| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,63 @@ | ||
| package org.apache.spark.sql.cassandra | ||
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| import org.apache.spark.sql.sources._ | ||
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| import org.scalacheck._ | ||
| import org.scalacheck.Prop.forAll | ||
| import org.scalatest.prop.PropertyChecks | ||
| import org.scalatest.{FlatSpec, ShouldMatchers} | ||
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| class FiltersOptimizerCheck extends FlatSpec with PropertyChecks with ShouldMatchers { | ||
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| // For testing purpose | ||
| case object True extends Filter | ||
| case object False extends Filter | ||
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| val genFullTree = for { | ||
| size <- Gen.choose(0, 500) | ||
| tree <- genTree(size) | ||
| } yield tree | ||
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| def genTree(maxDepth: Int): Gen[Filter] = | ||
| if (maxDepth == 0) leaf else Gen.oneOf(leaf, genAnd(maxDepth), genOr(maxDepth), genNot(maxDepth)) | ||
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| def genAnd(maxDepth: Int): Gen[Filter] = for { | ||
| depthL <- Gen.choose(0, maxDepth - 1) | ||
| depthR <- Gen.choose(0, maxDepth - 1) | ||
| left <- genTree(depthL) | ||
| right <- genTree(depthR) | ||
| } yield And(left, right) | ||
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| def genOr(maxDepth: Int): Gen[Filter] = for { | ||
| depthL <- Gen.choose(0, maxDepth - 1) | ||
| depthR <- Gen.choose(0, maxDepth - 1) | ||
| left <- genTree(depthL) | ||
| right <- genTree(depthR) | ||
| } yield Or(left, right) | ||
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| def genNot(maxDepth: Int): Gen[Filter] = for { | ||
| depth <- Gen.choose(0, maxDepth - 1) | ||
| expr <- genTree(depth) | ||
| } yield Not(expr) | ||
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| def leaf: Gen[Filter] = Gen.oneOf(True, False) | ||
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| /** | ||
| * Evaluate logical ADT | ||
| **/ | ||
| private def eval(clause: Filter): Boolean = clause match { | ||
| case And(left, right) => eval(left) && eval(right) | ||
| case Or(left, right) => eval(left) || eval(right) | ||
| case Not(predicate) => !eval(predicate) | ||
| case True => true | ||
| case False => false | ||
| } | ||
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| "FiltersOptimizer" should "generate equivalent disjunction normal form for arbitrary logical statement" in { | ||
| forAll(genFullTree){ expr => | ||
| val dnf = (FiltersOptimizer.toNNF andThen FiltersOptimizer.toDNF).apply(expr) | ||
| assert(eval(dnf) == eval(expr)) | ||
| } | ||
| } | ||
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| } |
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Replace the string here with the parameter defined in the conf file
EnableWhereClauseOptimizationParam.namejust in case we change things later :)