com.nvidia.spark.rapids.dataSourceUtil.scala Maven / Gradle / Ivy
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Creates the distribution package of the RAPIDS plugin for Apache Spark
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/*
* Copyright (c) 2022, 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 org.apache.spark.TaskContext
import org.apache.spark.sql.connector.read.PartitionReader
import org.apache.spark.sql.rapids.execution.TrampolineUtil
import org.apache.spark.sql.vectorized.ColumnarBatch
class PartitionIterator[T](reader: PartitionReader[T]) extends Iterator[T] {
private[this] var valuePrepared = false
override def hasNext: Boolean = {
if (!valuePrepared) {
valuePrepared = reader.next()
}
valuePrepared
}
override def next(): T = {
if (!hasNext) {
throw new java.util.NoSuchElementException("End of stream")
}
valuePrepared = false
reader.get()
}
}
class MetricsBatchIterator(iter: Iterator[ColumnarBatch]) extends Iterator[ColumnarBatch] {
private[this] val inputMetrics = TaskContext.get().taskMetrics().inputMetrics
override def hasNext: Boolean = iter.hasNext
override def next(): ColumnarBatch = {
val batch = iter.next()
TrampolineUtil.incInputRecordsRows(inputMetrics, batch.numRows())
batch
}
}
/** Wraps a columnar PartitionReader to update bytes read metric based on filesystem statistics. */
class PartitionReaderWithBytesRead(reader: PartitionReader[ColumnarBatch])
extends PartitionReader[ColumnarBatch] {
private[this] val inputMetrics = TaskContext.get.taskMetrics().inputMetrics
private[this] val getBytesRead = TrampolineUtil.getFSBytesReadOnThreadCallback()
override def next(): Boolean = {
val result = reader.next()
TrampolineUtil.incBytesRead(inputMetrics, getBytesRead())
result
}
override def get(): ColumnarBatch = reader.get()
override def close(): Unit = reader.close()
}
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