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ignore nullable in DeepImageFeaturizer.validateSchema (#143)
In Spark SQL, nullability is a hint used during optimization and codegen to skip nullchecks, but not intended as an enforcement mechanism or as an implication that null values do exist. It might get dropped through the pipeline. This PR switches to DataType.equalsIgnoreNullability for the check * ignore nullable in DeepImageFeaturizer.validateSchema
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src/main/scala/org/apache/spark/sql/types/DataTypeShim.scala
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/* | ||
* Copyright 2017 Databricks, Inc. | ||
* | ||
* Licensed 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.types | ||
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object DataTypeShim { | ||
/** | ||
* Compares two types, ignoring nullability of ArrayType, MapType, StructType. | ||
*/ | ||
def equalsIgnoreNullability(left: DataType, right: DataType): Boolean = { | ||
DataType.equalsIgnoreNullability(left, right) | ||
} | ||
} |
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