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/*
 * Copyright (c) 2022-2023, 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 com.nvidia.spark.rapids

import ai.rapids.cudf.{ColumnVector, DType}
import com.nvidia.spark.rapids.Arm.withResource

object BoolUtils {

  /**
   * Whether all the valid rows in 'col' are true. An empty column will get true.
   * null rows are skipped.
   */
  def isAllValidTrue(col: ColumnVector): Boolean = {
    assert(DType.BOOL8 == col.getType, "input column type is not bool")
    if (col.getRowCount == 0) {
      return true
    }

    if (col.getRowCount == col.getNullCount) {
      // all is null, equal to empty, since nulls should be skipped.
      return true
    }
    withResource(col.all()) { allTrue =>
      // Guaranteed there is at least one row and not all of the rows are null,
      // so result scalar must be valid
      allTrue.getBoolean
    }
  }

  /**
   * Whether there is any valid row in 'col' and it is true. An empty column will get false.
   * null rows are skipped.
   */
  def isAnyValidTrue(col: ColumnVector): Boolean = {
    assert(DType.BOOL8 == col.getType, "input column type is not bool")

    if (col.getRowCount == col.getNullCount) {
      // all is null, return false since nulls should be skipped.
      return false
    }
    withResource(col.any()) { anyTrue =>
      // Guaranteed there is at least one row and not all of the rows are null,
      // so result scalar must be valid
      anyTrue.getBoolean
    }
  }
}




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