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

There is a newer version: 24.08.1

/*
 * Copyright (c) 2019, 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 com.nvidia.spark.rapids.{GpuColumnVector, GpuExpression, GpuUnaryExpression}

import org.apache.spark.sql.catalyst.expressions.ExpectsInputTypes
import org.apache.spark.sql.types.{AbstractDataType, DataType, DoubleType, FloatType, TypeCollection}
import org.apache.spark.sql.vectorized.ColumnarBatch

// 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: GpuExpression) extends GpuUnaryExpression
    with ExpectsInputTypes {

  override def dataType: DataType = child.dataType

  override def inputTypes: Seq[AbstractDataType] = Seq(TypeCollection(FloatType, DoubleType))

  override def doColumnar(input: GpuColumnVector): GpuColumnVector =
    GpuColumnVector.from(input.getBase.normalizeNANsAndZeros())
}