francis0407 commented on a change in pull request #23942: [SPARK-27033][SQL]Add Optimize rule RewriteArithmeticFiltersOnIntOrLongColumn URL: https://github.com/apache/spark/pull/23942#discussion_r263667500
########## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteArithmeticFiltersOnIntOrLongColumn.scala ########## @@ -0,0 +1,147 @@ +/* + * 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.plans.logical.{Filter, LogicalPlan} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.types.{DataType, IntegerType, LongType} + +/** + * Rewrite arithmetic filters on int or long column to its equivalent form, + * leaving attribute alone in one side, so that we can push it down to + * parquet or other file format. + * For example, this rule can optimize + * {{{ + * SELECT * FROM table WHERE i + 3 = 5 + * }}} + * to + * {{{ + * SELECT * FROM table WHERE i = 5 - 3 + * }}} + * when i is Int or Long, and then other rules will further optimize it to + * {{{ + * SELECT * FROM table WHERE i = 2 + * }}} + * The arithmetic operation supports `Add` and `Subtract`. The comparision supports + * '=', '>=', '<=', '>', '<', '!='. It only supports type of `INT` and `LONG`, + * it doesn't support `FLOAT` or `DOUBLE` for precision issues. + */ +object RewriteArithmeticFiltersOnIntOrLongColumn extends Rule[LogicalPlan] with PredicateHelper { + def apply(plan: LogicalPlan): LogicalPlan = plan transform { + case f: Filter => + f transformExpressionsUp { + case e @ BinaryComparison(left: BinaryArithmetic, right: Expression) + if right.foldable && isDataTypeSafe(left.dataType) => + transformLeft(e, left, right) + case e @ BinaryComparison(left: Expression, right: BinaryArithmetic) + if left.foldable && isDataTypeSafe(right.dataType) => + transformRight(e, left, right) + } + } + + private def transformLeft( + bc: BinaryComparison, + left: BinaryArithmetic, + right: Expression): Expression = { + left match { + case Add(ar: AttributeReference, e) if e.foldable && isOptSafe(Subtract(right, e)) => + bc.makeCopy(Array(ar, Subtract(right, e))) + case Add(e, ar: AttributeReference) if e.foldable && isOptSafe(Subtract(right, e)) => + bc.makeCopy(Array(ar, Subtract(right, e))) + case Subtract(ar: AttributeReference, e) if e.foldable && isOptSafe(Add(right, e)) => + bc.makeCopy(Array(ar, Add(right, e))) + case Subtract(e, ar: AttributeReference) if e.foldable && isOptSafe(Subtract(e, right)) => + bc.makeCopy(Array(Subtract(e, right), ar)) + case _ => bc + } + } + + private def transformRight( + bc: BinaryComparison, + left: Expression, + right: BinaryArithmetic): Expression = { + right match { + case Add(ar: AttributeReference, e) if e.foldable && isOptSafe(Subtract(left, e)) => + bc.makeCopy(Array(Subtract(left, e), ar)) + case Add(e, ar: AttributeReference) if e.foldable && isOptSafe(Subtract(left, e)) => + bc.makeCopy(Array(Subtract(left, e), ar)) + case Subtract(ar: AttributeReference, e) if e.foldable && isOptSafe(Add(left, e)) => + bc.makeCopy(Array(Add(left, e), ar)) + case Subtract(e, ar: AttributeReference) if e.foldable && isOptSafe(Subtract(e, left)) => + bc.makeCopy(Array(ar, Subtract(e, left))) + case _ => bc + } + } + + private def isDataTypeSafe(dataType: DataType): Boolean = dataType match { Review comment: Here is an example: ``` scala> spark.sql("select float(1E-8) + float(1E+10) <= float(1E+10)").show() +----------------------------------------------------------------------+ |((CAST(1E-8 AS FLOAT) + CAST(1E+10 AS FLOAT)) <= CAST(1E+10 AS FLOAT))| +----------------------------------------------------------------------+ | true| +----------------------------------------------------------------------+ scala> spark.sql("select float(1E-8) <= float(1E+10) - float(1E+10)").show() +----------------------------------------------------------------------+ |(CAST(1E-8 AS FLOAT) <= (CAST(1E+10 AS FLOAT) - CAST(1E+10 AS FLOAT)))| +----------------------------------------------------------------------+ | false| +----------------------------------------------------------------------+ ``` Although `float(1E-8) + float(1E+10) <= float(1E+10)` should return false. 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