tanelk commented on a change in pull request #29565: URL: https://github.com/apache/spark/pull/29565#discussion_r479672380
########## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCast.scala ########## @@ -0,0 +1,214 @@ +/* + * 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.expressions._ +import org.apache.spark.sql.catalyst.expressions.Literal.FalseLiteral +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.types._ + +/** + * Unwrap casts in binary comparison operations with patterns like following: + * + * `BinaryComparison(Cast(fromExp, toType), Literal(value, toType))` + * or + * `BinaryComparison(Literal(value, toType), Cast(fromExp, toType))` + * + * This rule optimizes expressions with the above pattern by either replacing the cast with simpler + * constructs, or moving the cast from the expression side to the literal side, which enables them + * to be optimized away later and pushed down to data sources. + * + * Currently this only handles cases where `fromType` (of `fromExp`) and `toType` are of integral + * types (i.e., byte, short, int and long). The rule checks to see if the literal `value` is + * within range `(min, max)`, where `min` and `max` are the minimum and maximum value of + * `fromType`, respectively. If this is true then it means we can safely cast `value` to `fromType` + * and thus able to move the cast to the literal side. + * + * If the `value` is not within range `(min, max)`, the rule breaks the scenario into different + * cases and try to replace each with simpler constructs. + * + * if `value > max`, the cases are of following: + * - `cast(exp, ty) > value` ==> if(isnull(exp), null, false) + * - `cast(exp, ty) >= value` ==> if(isnull(exp), null, false) + * - `cast(exp, ty) === value` ==> if(isnull(exp), null, false) + * - `cast(exp, ty) <=> value` ==> false + * - `cast(exp, ty) <= value` ==> if(isnull(exp), null, true) + * - `cast(exp, ty) < value` ==> if(isnull(exp), null, true) + * + * if `value == max`, the cases are of following: + * - `cast(exp, ty) > value` ==> if(isnull(exp), null, false) + * - `cast(exp, ty) >= value` ==> exp == max + * - `cast(exp, ty) === value` ==> exp == max + * - `cast(exp, ty) <=> value` ==> exp == max + * - `cast(exp, ty) <= value` ==> if(isnull(exp), null, true) + * - `cast(exp, ty) < value` ==> exp =!= max + * + * Similarly for the cases when `value == min` and `value < min`. + * + * Further, the above `if(isnull(exp), null, false)` is represented using conjunction + * `and(isnull(exp), null)`, to enable further optimization and filter pushdown to data sources. + * Similarly, `if(isnull(exp), null, true)` is represented with `or(isnotnull(exp), null)`. + */ +object UnwrapCast extends Rule[LogicalPlan] { + override def apply(plan: LogicalPlan): LogicalPlan = plan transform { + case l: LogicalPlan => l transformExpressionsUp { + case e @ BinaryComparison(_, _) => unwrapCast(e) + } + } + + private def unwrapCast(exp: Expression): Expression = exp match { + case BinaryComparison(Literal(_, _), Cast(_, _, _)) => + // Not a canonical form. In this case we first canonicalize the expression by swapping the + // literal and cast side, then process the result and swap the literal and cast again to + // restore the original order. + def swap(e: Expression): Expression = e match { + case GreaterThan(left, right) => LessThan(right, left) + case GreaterThanOrEqual(left, right) => LessThanOrEqual(right, left) + case EqualTo(left, right) => EqualTo(right, left) + case EqualNullSafe(left, right) => EqualNullSafe(right, left) + case LessThanOrEqual(left, right) => GreaterThanOrEqual(right, left) + case LessThan(left, right) => GreaterThan(right, left) + case _ => e + } + + swap(unwrapCast(swap(exp))) + + case BinaryComparison(Cast(fromExp, _, _), Literal(value, toType)) + if canImplicitlyCast(fromExp, toType) => + + // In case both sides have integral type, optimize the comparison by removing casts or + // moving cast to the literal side. + simplifyIntegral(exp, fromExp, toType.asInstanceOf[IntegralType], value) + + case _ => exp + } + + /** + * Check if the input `value` is within range `(min, max)` of the `fromType`, where `min` and + * `max` are the minimum and maximum value of the `fromType`. If the above is true, this + * optimizes the expression by moving the cast to the literal side. Otherwise if result is not + * true, this replaces the input binary comparison `exp` with simpler expressions. + */ + private def simplifyIntegral( + exp: Expression, + fromExp: Expression, + toType: IntegralType, + value: Any): Expression = { + + val fromType = fromExp.dataType + val (min, max) = getRange(fromType) + val (minInToType, maxInToType) = { + (Cast(Literal(min), toType).eval(), Cast(Literal(max), toType).eval()) + } + val ordering = toType.ordering.asInstanceOf[Ordering[Any]] + val minCmp = ordering.compare(value, minInToType) + val maxCmp = ordering.compare(value, maxInToType) + + if (maxCmp > 0) { + exp match { + case EqualTo(_, _) | GreaterThan(_, _) | GreaterThanOrEqual(_, _) => + falseIfNotNull(fromExp) + case LessThan(_, _) | LessThanOrEqual(_, _) => + trueIfNotNull(fromExp) + case EqualNullSafe(_, _) => + FalseLiteral + case _ => exp // impossible but safe guard, same below + } + } else if (maxCmp == 0) { + exp match { + case GreaterThan(_, _) => + falseIfNotNull(fromExp) + case LessThanOrEqual(_, _) => + trueIfNotNull(fromExp) + case LessThan(_, _) => + Not(EqualTo(fromExp, Literal(max, fromType))) + case GreaterThanOrEqual(_, _) | EqualTo(_, _) | EqualNullSafe(_, _) => + EqualTo(fromExp, Literal(max, fromType)) + case _ => exp + } + } else if (minCmp < 0) { + exp match { + case GreaterThan(_, _) | GreaterThanOrEqual(_, _) => + trueIfNotNull(fromExp) + case LessThan(_, _) | LessThanOrEqual(_, _) | EqualTo(_, _) => + falseIfNotNull(fromExp) + case EqualNullSafe(_, _) => + FalseLiteral + case _ => exp + } + } else if (minCmp == 0) { + exp match { + case LessThan(_, _) => + falseIfNotNull(fromExp) + case GreaterThanOrEqual(_, _) => + trueIfNotNull(fromExp) + case GreaterThan(_, _) => + Not(EqualTo(fromExp, Literal(min, fromType))) + case LessThanOrEqual(_, _) | EqualTo(_, _) | EqualNullSafe(_, _) => + EqualTo(fromExp, Literal(min, fromType)) + case _ => exp + } + } else { + // This means `value` is within range `(min, max)`. Optimize this by moving the cast to the + // literal side. + val lit = Cast(Literal(value), fromType) + exp match { + case GreaterThan(_, _) => GreaterThan(fromExp, lit) + case GreaterThanOrEqual(_, _) => GreaterThanOrEqual(fromExp, lit) + case EqualTo(_, _) => EqualTo(fromExp, lit) + case EqualNullSafe(_, _) => EqualNullSafe(fromExp, lit) + case LessThan(_, _) => LessThan(fromExp, lit) + case LessThanOrEqual(_, _) => LessThanOrEqual(fromExp, lit) Review comment: nit: missing safe guard case ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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