[GitHub] [spark] cloud-fan commented on a change in pull request #29565: [SPARK-24994][SQL] Add UnwrapCastInBinaryComparison optimizer to simplify literal types

[GitBox <gi...@apache.org>]

cloud-fan commented on a change in pull request #29565:
URL: https://github.com/apache/spark/pull/29565#discussion_r486044204



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparison.scala
##########
@@ -0,0 +1,204 @@
+/*
+ * 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(fromExp, toType) > value` ==> if(isnull(fromExp), null, false)
+ *  - `cast(fromExp, toType) >= value` ==> if(isnull(fromExp), null, false)
+ *  - `cast(fromExp, toType) === value` ==> if(isnull(fromExp), null, false)
+ *  - `cast(fromExp, toType) <=> value` ==> false (only if `fromExp` is deterministic)
+ *  - `cast(fromExp, toType) <= value` ==> if(isnull(fromExp), null, true)
+ *  - `cast(fromExp, toType) < value` ==> if(isnull(fromExp), null, true)
+ *
+ * if `value == max`, the cases are of following:
+ *  - `cast(fromExp, toType) > value` ==> if(isnull(fromExp), null, false)
+ *  - `cast(fromExp, toType) >= value` ==> fromExp == max
+ *  - `cast(fromExp, toType) === value` ==> fromExp == max
+ *  - `cast(fromExp, toType) <=> value` ==> fromExp == max
+ *  - `cast(fromExp, toType) <= value` ==> if(isnull(fromExp), null, true)
+ *  - `cast(fromExp, toType) < value` ==> fromExp =!= max
+ *
+ * Similarly for the cases when `value == min` and `value < min`.
+ *
+ * Further, the above `if(isnull(fromExp), null, false)` is represented using conjunction
+ * `and(isnull(fromExp), null)`, to enable further optimization and filter pushdown to data sources.
+ * Similarly, `if(isnull(fromExp), null, true)` is represented with `or(isnotnull(fromExp), null)`.
+ */
+object UnwrapCastInBinaryComparison 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 {
+    // 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.
+    case BinaryComparison(Literal(_, toType: IntegralType), Cast(fromExp, _: IntegralType, _))
+        if canImplicitlyCast(fromExp, toType) =>
+      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)))
+
+    // In case both sides have integral type, optimize the comparison by removing casts or
+    // moving cast to the literal side.
+    case be @ BinaryComparison(
+      Cast(fromExp, toType: IntegralType, _), Literal(value, _: IntegralType))
+        if canImplicitlyCast(fromExp, toType) =>
+      simplifyIntegral(be, fromExp, toType, 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: BinaryComparison,
+      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)
+    val lit = Cast(Literal(value), fromType)
+
+    (minCmp.signum, maxCmp.signum, exp) match {
+      case (_, 1, EqualTo(_, _) | GreaterThan(_, _) | GreaterThanOrEqual(_, _)) =>
+        fromExp.falseIfNotNull
+      case (_, 1, LessThan(_, _) | LessThanOrEqual(_, _)) =>
+        fromExp.trueIfNotNull
+      // make sure the expression is evaluated if it is non-deterministic
+      case (_, 1, EqualNullSafe(_, _)) if exp.deterministic =>
+        FalseLiteral
+      case (_, 1, _) => exp // impossible but safe guard, same below
+
+      case (_, 0, GreaterThan(_, _)) =>
+        fromExp.falseIfNotNull
+      case (_, 0, LessThanOrEqual(_, _)) =>
+        fromExp.trueIfNotNull
+      case (_, 0, LessThan(_, _)) =>
+        Not(EqualTo(fromExp, Literal(max, fromType)))
+      case (_, 0, GreaterThanOrEqual(_, _) | EqualTo(_, _) | EqualNullSafe(_, _)) =>
+        EqualTo(fromExp, Literal(max, fromType))
+      case (_, 0, _) => exp
+
+      case (-1, _, GreaterThan(_, _) | GreaterThanOrEqual(_, _)) =>
+        fromExp.trueIfNotNull
+      case (-1, _, LessThan(_, _) | LessThanOrEqual(_, _) | EqualTo(_, _)) =>
+        fromExp.falseIfNotNull
+      // make sure the expression is evaluated if it is non-deterministic
+      case (-1, _, EqualNullSafe(_, _)) if exp.deterministic =>
+        FalseLiteral
+      case (-1, _, _) => exp
+
+      case (0, _, LessThan(_, _)) =>
+        fromExp.falseIfNotNull
+      case (0, _, GreaterThanOrEqual(_, _)) =>
+        fromExp.trueIfNotNull
+      case (0, _, GreaterThan(_, _)) =>
+        Not(EqualTo(fromExp, Literal(min, fromType)))
+      case (0, _, LessThanOrEqual(_, _) | EqualTo(_, _) | EqualNullSafe(_, _)) =>
+        EqualTo(fromExp, Literal(min, fromType))
+      case (0, _, _) => exp
+
+      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)
+      case (_, _, _) => exp
+    }
+  }
+
+  /**
+   * Check if the input `fromExp` can be safely cast to `toType` without any loss of precision,
+   * i.e., the conversion is injective. Note this only handles the case when both sides are of
+   * integral type.
+   */
+  private def canImplicitlyCast(fromExp: Expression, toType: DataType): Boolean = {
+    fromExp.dataType.isInstanceOf[IntegralType] && toType.isInstanceOf[IntegralType] &&
+      Cast.canUpCast(fromExp.dataType, toType)

Review comment:
       For `cast(long_col as int) = int_literal`, we don't support it?




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