com.nvidia.spark.rapids.GatherUtils.scala Maven / Gradle / Ivy
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Creates the distribution package of the RAPIDS plugin for Apache Spark
/*
* Copyright (c) 2021-2023, 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 scala.collection.mutable.ArrayBuffer
import ai.rapids.cudf.ColumnVector
import com.nvidia.spark.rapids.Arm.withResource
import org.apache.spark.sql.vectorized.ColumnarBatch
object GatherUtils {
def gather(cb: ColumnarBatch, rows: ArrayBuffer[Int]): ColumnarBatch = {
val colTypes = GpuColumnVector.extractTypes(cb)
if (rows.isEmpty) {
GpuColumnVector.emptyBatchFromTypes(colTypes)
} else if (cb.numCols() == 0) {
// for count agg, num of cols is 0
val c = GpuColumnVector.emptyBatchFromTypes(colTypes)
c.setNumRows(rows.length)
c
} else {
withResource(ColumnVector.fromInts(rows.toSeq: _*)) { gatherCv =>
withResource(GpuColumnVector.from(cb)) { table =>
// GPU gather
withResource(table.gather(gatherCv)) { gatheredTable =>
GpuColumnVector.from(gatheredTable, colTypes)
}
}
}
}
}
}