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[NSE-1075] Dynamically adjust input partition size #1076
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one or more | ||
| * contributor license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright ownership. | ||
| * The ASF licenses this file to You 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 org.apache.spark.sql.execution.datasources.v2.arrow | ||
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| import org.apache.spark.sql.catalyst.expressions.AttributeReference | ||
| import org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex | ||
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| object ScanUtils { | ||
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| def toAttributes(fileIndex: PartitioningAwareFileIndex): Seq[AttributeReference] = { | ||
| fileIndex.partitionSchema.toAttributes | ||
| } | ||
| } |
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@@ -16,20 +16,27 @@ | |
| */ | ||
| package com.intel.oap.spark.sql.execution.datasources.v2.arrow | ||
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| import com.intel.oap.sql.shims.SparkShimLoader | ||
| import java.util.Locale | ||
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| import scala.collection.JavaConverters._ | ||
| import org.apache.hadoop.fs.Path | ||
| import org.apache.spark.sql.{AnalysisException, SparkSession} | ||
| import org.apache.spark.sql.catalyst.expressions.Expression | ||
| import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection | ||
| import org.apache.spark.sql.connector.read.PartitionReaderFactory | ||
| import org.apache.spark.sql.execution.PartitionedFileUtil | ||
| import org.apache.spark.sql.execution.datasources.{FilePartition, PartitionDirectory, PartitionedFile, PartitioningAwareFileIndex} | ||
| import org.apache.spark.sql.execution.datasources.v2.FileScan | ||
| import org.apache.spark.sql.execution.datasources.v2.arrow.ScanUtils | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.sources.Filter | ||
| import org.apache.spark.sql.types.StructType | ||
| import org.apache.spark.sql.util.CaseInsensitiveStringMap | ||
| import org.apache.spark.util.SerializableConfiguration | ||
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| import scala.collection.mutable.ArrayBuffer | ||
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| case class ArrowScan( | ||
| sparkSession: SparkSession, | ||
| fileIndex: PartitioningAwareFileIndex, | ||
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@@ -41,6 +48,10 @@ case class ArrowScan( | |
| dataFilters: Seq[Expression] = Seq.empty) | ||
| extends FileScan { | ||
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| // Use the default value for org.apache.spark.internal.config.IO_WARNING_LARGEFILETHRESHOLD. | ||
| val IO_WARNING_LARGEFILETHRESHOLD: Long = 1024 * 1024 * 1024 | ||
| var openCostInBytesFinal = sparkSession.sessionState.conf.filesOpenCostInBytes | ||
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| override def isSplitable(path: Path): Boolean = { | ||
| ArrowUtils.isOriginalFormatSplitable( | ||
| new ArrowOptions(new CaseInsensitiveStringMap(options).asScala.toMap)) | ||
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@@ -63,4 +74,146 @@ case class ArrowScan( | |
| override def withFilters(partitionFilters: Seq[Expression], | ||
| dataFilters: Seq[Expression]): FileScan = | ||
| this.copy(partitionFilters = partitionFilters, dataFilters = dataFilters) | ||
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| // compute maxSplitBytes | ||
| // def maxSplitBytes(sparkSession: SparkSession, | ||
| // selectedPartitions: Seq[PartitionDirectory]): Long = { | ||
| // // TODO: unify it with PREFERRED_PARTITION_SIZE_UPPER_BOUND. | ||
| // val defaultMaxSplitBytes = sparkSession.sessionState.conf.filesMaxPartitionBytes | ||
| // val openCostInBytes = sparkSession.sessionState.conf.filesOpenCostInBytes | ||
| // // val minPartitionNum = sparkSession.sessionState.conf.filesMinPartitionNum | ||
| // // .getOrElse(sparkSession.leafNodeDefaultParallelism) | ||
| // val minPartitionNum = sparkSession.sessionState.conf.filesMinPartitionNum | ||
| // .getOrElse(SparkShimLoader.getSparkShims.leafNodeDefaultParallelism(sparkSession)) | ||
| // val PREFERRED_PARTITION_SIZE_LOWER_BOUND: Long = 256 * 1024 * 1024 | ||
| // val PREFERRED_PARTITION_SIZE_UPPER_BOUND: Long = 1024 * 1024 * 1024 | ||
| // val totalBytes = selectedPartitions.flatMap(_.files.map(_.getLen + openCostInBytes)).sum | ||
| // var maxBytesPerCore = totalBytes / minPartitionNum | ||
| // var bytesPerCoreFinal = maxBytesPerCore | ||
| // var bytesPerCore = maxBytesPerCore | ||
| // | ||
| // if (bytesPerCore > PREFERRED_PARTITION_SIZE_UPPER_BOUND) { | ||
| // // Adjust partition size. | ||
| // var i = 2 | ||
| // while (bytesPerCore > PREFERRED_PARTITION_SIZE_UPPER_BOUND) { | ||
| // bytesPerCore = maxBytesPerCore / i | ||
| // if (bytesPerCore > PREFERRED_PARTITION_SIZE_LOWER_BOUND) { | ||
| // bytesPerCoreFinal = bytesPerCore | ||
| // } | ||
| // i = i + 1 | ||
| // } | ||
| // Math.min(PREFERRED_PARTITION_SIZE_UPPER_BOUND, bytesPerCoreFinal) | ||
| // // Math.min(defaultMaxSplitBytes, Math.max(openCostInBytes, bytesPerCore)) | ||
| // } else { | ||
| // // adjust open cost. | ||
| // var i = 2 | ||
| // while (bytesPerCore < PREFERRED_PARTITION_SIZE_LOWER_BOUND) { | ||
| // val dynamicOpenCostInBytes = openCostInBytesFinal * i | ||
| // val totalBytes = | ||
| // selectedPartitions.flatMap(_.files.map(_.getLen + dynamicOpenCostInBytes)).sum | ||
| // maxBytesPerCore = totalBytes / minPartitionNum | ||
| // if (maxBytesPerCore < PREFERRED_PARTITION_SIZE_UPPER_BOUND) { | ||
| // openCostInBytesFinal = dynamicOpenCostInBytes | ||
| // bytesPerCoreFinal = maxBytesPerCore | ||
| // } | ||
| // i = i + 1 | ||
| // } | ||
| // Math.max(PREFERRED_PARTITION_SIZE_LOWER_BOUND, bytesPerCoreFinal) | ||
| // } | ||
| // } | ||
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| // This implementation is ported from spark FilePartition.scala with changes for | ||
| // adjusting openCost. | ||
| def getFilePartitions(sparkSession: SparkSession, | ||
|
There was a problem hiding this comment. @jackylee-ch, please put your code changes for open cost here. It should be workable. |
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| partitionedFiles: Seq[PartitionedFile], | ||
| maxSplitBytes: Long): Seq[FilePartition] = { | ||
| val partitions = new ArrayBuffer[FilePartition] | ||
| val currentFiles = new ArrayBuffer[PartitionedFile] | ||
| var currentSize = 0L | ||
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| /** Close the current partition and move to the next. */ | ||
| def closePartition(): Unit = { | ||
| if (currentFiles.nonEmpty) { | ||
| // Copy to a new Array. | ||
| val newPartition = FilePartition(partitions.size, currentFiles.toArray) | ||
| partitions += newPartition | ||
| } | ||
| currentFiles.clear() | ||
| currentSize = 0 | ||
| } | ||
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| val openCostInBytes = sparkSession.sessionState.conf.filesOpenCostInBytes | ||
| // Assign files to partitions using "Next Fit Decreasing" | ||
| partitionedFiles.foreach { file => | ||
| if (currentSize + file.length > maxSplitBytes) { | ||
| closePartition() | ||
| } | ||
| // Add the given file to the current partition. | ||
| currentSize += file.length + openCostInBytes | ||
| currentFiles += file | ||
| } | ||
| closePartition() | ||
| partitions.toSeq | ||
| } | ||
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| // This implementation is ported from spark FileScan with only changes for computing | ||
| // maxSplitBytes. | ||
| // override def partitions: Seq[FilePartition] = { | ||
| // val selectedPartitions = fileIndex.listFiles(partitionFilters, dataFilters) | ||
| // // val maxSplitBytes = FilePartition.maxSplitBytes(sparkSession, selectedPartitions) | ||
| // val maxSplitBytes = this.maxSplitBytes(sparkSession, selectedPartitions) | ||
| // // val partitionAttributes = fileIndex.partitionSchema.toAttributes | ||
| // val partitionAttributes = ScanUtils.toAttributes(fileIndex) | ||
| // val attributeMap = partitionAttributes.map(a => normalizeName(a.name) -> a).toMap | ||
| // val readPartitionAttributes = readPartitionSchema.map { readField => | ||
| // attributeMap.get(normalizeName(readField.name)).getOrElse { | ||
| // // throw QueryCompilationErrors.cannotFindPartitionColumnInPartitionSchemaError( | ||
| // // readField, fileIndex.partitionSchema) | ||
| // throw new RuntimeException(s"Can't find required partition column ${readField.name} " + | ||
| // s"in partition schema ${fileIndex.partitionSchema}") | ||
| // } | ||
| // } | ||
| // lazy val partitionValueProject = | ||
| // GenerateUnsafeProjection.generate(readPartitionAttributes, partitionAttributes) | ||
| // val splitFiles = selectedPartitions.flatMap { partition => | ||
| // // Prune partition values if part of the partition columns are not required. | ||
| // val partitionValues = if (readPartitionAttributes != partitionAttributes) { | ||
| // partitionValueProject(partition.values).copy() | ||
| // } else { | ||
| // partition.values | ||
| // } | ||
| // partition.files.flatMap { file => | ||
| // val filePath = file.getPath | ||
| // PartitionedFileUtil.splitFiles( | ||
| // sparkSession = sparkSession, | ||
| // file = file, | ||
| // filePath = filePath, | ||
| // isSplitable = isSplitable(filePath), | ||
| // maxSplitBytes = maxSplitBytes, | ||
| // partitionValues = partitionValues | ||
| // ) | ||
| // }.toArray.sortBy(_.length)(implicitly[Ordering[Long]].reverse) | ||
| // } | ||
| // | ||
| // if (splitFiles.length == 1) { | ||
| // val path = new Path(splitFiles(0).filePath) | ||
| // if (!isSplitable(path) && splitFiles(0).length > | ||
| // IO_WARNING_LARGEFILETHRESHOLD) { | ||
| // logWarning(s"Loading one large unsplittable file ${path.toString} with only one " + | ||
| // s"partition, the reason is: ${getFileUnSplittableReason(path)}") | ||
| // } | ||
| // } | ||
| // | ||
| // FilePartition.getFilePartitions(sparkSession, splitFiles, maxSplitBytes) | ||
| // } | ||
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| private val isCaseSensitive = sparkSession.sessionState.conf.caseSensitiveAnalysis | ||
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| private def normalizeName(name: String): String = { | ||
| if (isCaseSensitive) { | ||
| name | ||
| } else { | ||
| name.toLowerCase(Locale.ROOT) | ||
| } | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,28 @@ | ||
| /* | ||
| * Copyright 2020 Intel 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 org.apache.spark.sql.util | ||
|
|
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| import org.apache.spark.sql.SparkSession | ||
| import org.apache.spark.sql.internal.SQLConf | ||
|
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| object ShimUtils { | ||
|
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| def leafNodeDefaultParallelism(sparkSession: SparkSession): Int = { | ||
| sparkSession.conf.get(SQLConf.LEAF_NODE_DEFAULT_PARALLELISM).getOrElse( | ||
| sparkSession.sparkContext.defaultParallelism) | ||
| } | ||
| } |
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@jackylee-ch, I note you have introduced a sort of computation for taskParallelismNum, is it as same as minPartitionNum? This piece of code is ported from spark source code.
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No, they are not same. The
taskParallelismNumis actually thespark.sql.files.expectedPartitionNum, which can be configured by the user and the default value is the maximum number of tasks that can be parallelized in the current application.