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Add unit tests for GpuPartition, Spark session handling updates (#398)
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tests/src/test/scala/com/nvidia/spark/rapids/GpuPartitioningSuite.scala
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| /* | ||
| * Copyright (c) 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. | ||
| */ | ||
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| package com.nvidia.spark.rapids | ||
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| import java.io.File | ||
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| import ai.rapids.cudf.{Cuda, Table} | ||
| import com.nvidia.spark.rapids.RapidsPluginImplicits._ | ||
| import org.scalatest.FunSuite | ||
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| import org.apache.spark.SparkConf | ||
| import org.apache.spark.sql.SparkSession | ||
| import org.apache.spark.sql.rapids.{GpuShuffleEnv, RapidsDiskBlockManager} | ||
| import org.apache.spark.sql.vectorized.ColumnarBatch | ||
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| class GpuPartitioningSuite extends FunSuite with Arm { | ||
| private def buildBatch(): ColumnarBatch = { | ||
| withResource(new Table.TestBuilder() | ||
| .column(5, null.asInstanceOf[java.lang.Integer], 3, 1, 1, 1, 1, 1, 1, 1) | ||
| .column("five", "two", null, null, "one", "one", "one", "one", "one", "one") | ||
| .column(5.0, 2.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0) | ||
| .build()) { table => | ||
| GpuColumnVector.from(table) | ||
| } | ||
| } | ||
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| private def buildSubBatch(batch: ColumnarBatch, startRow: Int, endRow: Int): ColumnarBatch = { | ||
| val columns = GpuColumnVector.extractBases(batch) | ||
| val sliced = columns.safeMap(c => GpuColumnVector.from(c.subVector(startRow, endRow))) | ||
| new ColumnarBatch(sliced.toArray, endRow - startRow) | ||
| } | ||
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| private def compareBatches(expected: ColumnarBatch, actual: ColumnarBatch): Unit = { | ||
| assertResult(expected.numRows)(actual.numRows) | ||
| assertResult(expected.numCols)(actual.numCols) | ||
| val expectedColumns = GpuColumnVector.extractBases(expected) | ||
| val actualColumns = GpuColumnVector.extractBases(expected) | ||
| expectedColumns.zip(actualColumns).foreach { case (expected, actual) => | ||
| withResource(expected.equalToNullAware(actual)) { compareVector => | ||
| withResource(compareVector.all()) { compareResult => | ||
| assert(compareResult.getBoolean) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| def withGpuSparkSession(conf: SparkConf)(f: SparkSession => Unit): Unit = { | ||
| SparkSession.getActiveSession.foreach(_.close()) | ||
| val spark = SparkSession.builder() | ||
| .master("local[1]") | ||
| .config(conf) | ||
| .config(RapidsConf.SQL_ENABLED.key, "true") | ||
| .config("spark.plugins", "com.nvidia.spark.SQLPlugin") | ||
| .appName(classOf[GpuPartitioningSuite].getSimpleName) | ||
| .getOrCreate() | ||
| try { | ||
| f(spark) | ||
| } finally { | ||
| spark.stop() | ||
| SparkSession.clearActiveSession() | ||
| SparkSession.clearDefaultSession() | ||
| } | ||
| } | ||
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| test("GPU partition") { | ||
| SparkSession.getActiveSession.foreach(_.close()) | ||
| val conf = new SparkConf() | ||
| withGpuSparkSession(conf) { spark => | ||
| GpuShuffleEnv.init(Cuda.memGetInfo()) | ||
| val partitionIndices = Array(0, 2) | ||
| val gp = new GpuPartitioning { | ||
| override val numPartitions: Int = partitionIndices.length | ||
| } | ||
| withResource(buildBatch()) { batch => | ||
| val columns = GpuColumnVector.extractColumns(batch) | ||
| withResource(gp.sliceInternalOnGpu(batch, partitionIndices, columns)) { partitions => | ||
| partitions.zipWithIndex.foreach { case (partBatch, partIndex) => | ||
| val startRow = partitionIndices(partIndex) | ||
| val endRow = if (partIndex < partitionIndices.length - 1) { | ||
| partitionIndices(partIndex + 1) | ||
| } else { | ||
| batch.numRows | ||
| } | ||
| val expectedRows = endRow - startRow | ||
| assertResult(expectedRows)(partBatch.numRows) | ||
| val columns = (0 until partBatch.numCols).map(i => partBatch.column(i)) | ||
| columns.foreach { column => | ||
| assert(column.isInstanceOf[GpuColumnVectorFromBuffer]) | ||
| assertResult(expectedRows)(column.asInstanceOf[GpuColumnVector].getRowCount) | ||
| } | ||
| withResource(buildSubBatch(batch, startRow, endRow)) { expectedBatch => | ||
| compareBatches(expectedBatch, partBatch) | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } |
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