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### What changes were proposed in this pull request? Refactor `UpCast` resolution out of the `Analyzer`. ### Why are the changes needed? To reuse this code in single-pass `Resolver`. ### Does this PR introduce _any_ user-facing change? No, just a refactoring. ### How was this patch tested? Existing tests. ### Was this patch authored or co-authored using generative AI tooling? Copilot.nvim. Closes #49669 from vladimirg-db/vladimirg-db/refactor-upcast-resolution-out. Authored-by: Vladimir Golubev <[email protected]> Signed-off-by: Max Gekk <[email protected]>
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/UpCastResolution.scala
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/* | ||
* 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.catalyst.analysis | ||
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import org.apache.spark.SparkException | ||
import org.apache.spark.sql.catalyst.SQLConfHelper | ||
import org.apache.spark.sql.catalyst.expressions.{Cast, Expression, UpCast} | ||
import org.apache.spark.sql.catalyst.expressions.objects.LambdaVariable | ||
import org.apache.spark.sql.errors.QueryCompilationErrors | ||
import org.apache.spark.sql.internal.SQLConf | ||
import org.apache.spark.sql.types.{AtomicType, DataType, DecimalType, StringType} | ||
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object UpCastResolution extends SQLConfHelper { | ||
def resolve(unresolvedUpCast: UpCast): Expression = unresolvedUpCast match { | ||
case UpCast(_, target, _) if target != DecimalType && !target.isInstanceOf[DataType] => | ||
throw SparkException.internalError( | ||
s"UpCast only supports DecimalType as AbstractDataType yet, but got: $target" | ||
) | ||
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case UpCast(child, target, walkedTypePath) | ||
if target == DecimalType | ||
&& child.dataType.isInstanceOf[DecimalType] => | ||
assert( | ||
walkedTypePath.nonEmpty, | ||
"object DecimalType should only be used inside ExpressionEncoder" | ||
) | ||
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// SPARK-31750: if we want to upcast to the general decimal type, and the `child` is | ||
// already decimal type, we can remove the `Upcast` and accept any precision/scale. | ||
// This can happen for cases like `spark.read.parquet("/tmp/file").as[BigDecimal]`. | ||
child | ||
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case UpCast(child, target: AtomicType, _) | ||
if conf.getConf(SQLConf.LEGACY_LOOSE_UPCAST) && | ||
child.dataType == StringType => | ||
Cast(child, target.asNullable) | ||
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case unresolvedUpCast @ UpCast(child, _, walkedTypePath) | ||
if !Cast.canUpCast(child.dataType, unresolvedUpCast.dataType) => | ||
fail(child, unresolvedUpCast.dataType, walkedTypePath) | ||
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case unresolvedUpCast @ UpCast(child, _, _) => | ||
Cast(child, unresolvedUpCast.dataType) | ||
} | ||
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private def fail(from: Expression, to: DataType, walkedTypePath: Seq[String]) = { | ||
val fromStr = from match { | ||
case l: LambdaVariable => "array element" | ||
case e => e.sql | ||
} | ||
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throw QueryCompilationErrors.upCastFailureError(fromStr, from, to, walkedTypePath) | ||
} | ||
} |