fix: avoid duplicate CheckOverflow evaluation for decimal division #5225
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−34
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,104 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.comet | ||
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| import org.apache.spark.sql.CometTestBase | ||
| import org.apache.spark.sql.catalyst.expressions.{ArrayContains, AttributeReference, Divide, EvalMode} | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.types.{DecimalType, IntegerType} | ||
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| import org.apache.comet.serde.{CometDivide, ExprOuterClass, QueryPlanSerde, Unsupported} | ||
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| class CometDecimalPromotionSuite extends CometTestBase { | ||
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| private case class Operation( | ||
| name: String, | ||
| symbol: String, | ||
| hasProto: ExprOuterClass.Expr => Boolean) | ||
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| private case class TestMode(name: String, ansiEnabled: Boolean, failOnError: Boolean) | ||
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| test("issue #5190: decimal promotion is idempotent during recursive serialization") { | ||
| val left = "CAST(id AS DECIMAL(10, 0))" | ||
| val right = "CAST(id + 1 AS DECIMAL(10, 0))" | ||
| val divide = Operation(name = "divide", symbol = "/", hasProto = _.hasDivide) | ||
| val operations = Seq( | ||
| Operation(name = "add", symbol = "+", hasProto = _.hasAdd), | ||
| Operation(name = "subtract", symbol = "-", hasProto = _.hasSubtract), | ||
| Operation(name = "multiply", symbol = "*", hasProto = _.hasMultiply), | ||
| divide, | ||
| Operation(name = "remainder", symbol = "%", hasProto = _.hasRemainder)) | ||
| val legacy = TestMode(name = "LEGACY", ansiEnabled = false, failOnError = false) | ||
| val ansi = TestMode(name = "ANSI", ansiEnabled = true, failOnError = true) | ||
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| def check(operation: Operation, mode: TestMode, arithmetic: String): Unit = { | ||
| val name = s"${operation.name} ${mode.name}" | ||
| withSQLConf(SQLConf.ANSI_ENABLED.key -> mode.ansiEnabled.toString) { | ||
| val plan = spark | ||
| .sql(s"SELECT array_contains(array($arithmetic), $arithmetic) FROM range(1, 4)") | ||
| .queryExecution | ||
| .optimizedPlan | ||
| val expression = plan.expressions.head | ||
| val arrayContains = expression.collectFirst { case e: ArrayContains => e }.get | ||
| val promoted = DecimalPrecision.promote(expression) | ||
| assert( | ||
| DecimalPrecision.promote(promoted) == promoted, | ||
| s"$name promotion is not idempotent: $promoted") | ||
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| val arithmeticProto = QueryPlanSerde | ||
| .exprToProto(expression, plan.children.head.output) | ||
| .get | ||
| .getScalarFunc | ||
| .getArgs(1) | ||
| assert(arithmeticProto.hasCheckOverflow, s"$name: $arithmeticProto") | ||
| val overflow = arithmeticProto.getCheckOverflow | ||
| assert( | ||
| overflow.getDatatype === QueryPlanSerde | ||
| .serializeDataType(arrayContains.right.dataType) | ||
| .get, | ||
| s"$name has the wrong CheckOverflow datatype: $arithmeticProto") | ||
| assert(overflow.getFailOnError === mode.failOnError, s"$name: $arithmeticProto") | ||
| assert( | ||
| operation.hasProto(overflow.getChild), | ||
| s"$name has duplicate CheckOverflow: $arithmeticProto") | ||
| } | ||
| } | ||
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| operations.foreach { operation => | ||
| Seq(legacy, ansi).foreach { mode => | ||
| check(operation, mode, s"$left ${operation.symbol} $right") | ||
| } | ||
| } | ||
| check( | ||
| divide, | ||
| TestMode(name = "TRY", ansiEnabled = true, failOnError = false), | ||
| s"try_divide($left, $right)") | ||
| } | ||
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| test("decimal Divide with a non-decimal operand is unsupported") { | ||
| // This is only a sanity check; Spark's type coercion should prevent this case. | ||
| val decimal = AttributeReference("decimal", DecimalType(10, 0))() | ||
| val integer = AttributeReference("integer", IntegerType)() | ||
| val divide = Divide(decimal, integer, EvalMode.LEGACY) | ||
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| assert(divide.dataType === DecimalType(10, 0)) | ||
| assert(CometDivide.getSupportLevel(divide).isInstanceOf[Unsupported]) | ||
| } | ||
| } |
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One thing I want to check here. The guard you removed fired on
expr.dataType.isInstanceOf[DecimalType]alone. Thepromoterule requires both operands to matchDecimalExpressionas well, andgetSupportLevelonly looks atexpr.left.dataType. So if a decimal-typedDividewith a non-decimal operand ever reaches this serde, there is noCheckOverflowanywhere and the nativei128::MAXsentinel comes back as a real value.I could not construct that shape through Spark's type coercion, so I believe it is unreachable today. Since the failure mode is silent wrong data rather than a fallback, would you be up for a defensive guard? Returning
UnsupportedfromgetSupportLevelwhenexpr.dataTypeis decimal but the operands would not matchpromote's pattern would keep the invariant checkable next to the code that depends on it.There was a problem hiding this comment.
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added a sanity check.