org.apache.spark.sql.rapids.NormalizeFloatingNumbers.scala Maven / Gradle / Ivy
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Creates the distribution package of the RAPIDS plugin for Apache Spark
/*
* Copyright (c) 2019-2020, NVIDIA CORPORATION.
*
* 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.
*/
package org.apache.spark.sql.rapids
import ai.rapids.cudf.ColumnVector
import com.nvidia.spark.rapids.{GpuColumnVector, GpuUnaryExpression}
import org.apache.spark.sql.catalyst.expressions.{ExpectsInputTypes, Expression}
import org.apache.spark.sql.types.{AbstractDataType, DataType, DoubleType, FloatType, TypeCollection}
// This will ensure that:
// - input NaNs become Float.NaN, or Double.NaN
// - that -0.0f and -0.0d becomes 0.0f, and 0.0d respectively
// TODO: need coalesce as a feature request in cudf
case class GpuNormalizeNaNAndZero(child: Expression) extends GpuUnaryExpression
with ExpectsInputTypes {
override def dataType: DataType = child.dataType
override def inputTypes: Seq[AbstractDataType] = Seq(TypeCollection(FloatType, DoubleType))
override def doColumnar(input: GpuColumnVector): ColumnVector =
input.getBase.normalizeNANsAndZeros()
}