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56 changes: 56 additions & 0 deletions
56
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala
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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 | ||
|
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| import org.apache.spark.{Partition, TaskContext} | ||
| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.SQLContext | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
|
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| /** | ||
| * A single file that should be read, along with partition column values that | ||
| * need to be prepended to each row. The reading should start at the first | ||
| * valid record found after `offset`. | ||
| */ | ||
| case class PartitionedFile( | ||
| partitionValues: InternalRow, | ||
| filePath: String, | ||
| start: Long, | ||
| length: Long) | ||
|
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| /** | ||
| * A collection of files that should be read as a single task possibly from multiple partitioned | ||
| * directories. | ||
| * | ||
| * IMPLEMENT ME: This is just a placeholder for a future implementation. | ||
| */ | ||
| case class FilePartition(val index: Int, files: Seq[PartitionedFile]) extends Partition | ||
|
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| class FileScanRDD( | ||
| @transient val sqlContext: SQLContext, | ||
| readFunction: (PartitionedFile) => Iterator[InternalRow], | ||
| @transient val filePartitions: Seq[FilePartition]) | ||
| extends RDD[InternalRow](sqlContext.sparkContext, Nil) { | ||
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| override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = { | ||
| throw new NotImplementedError("Not Implemented Yet") | ||
| } | ||
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| override protected def getPartitions: Array[Partition] = Array.empty | ||
| } |
202 changes: 202 additions & 0 deletions
202
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala
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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 | ||
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| import scala.collection.mutable.ArrayBuffer | ||
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| import org.apache.hadoop.fs.Path | ||
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| import org.apache.spark.Logging | ||
| import org.apache.spark.sql._ | ||
| import org.apache.spark.sql.catalyst.expressions | ||
| import org.apache.spark.sql.catalyst.expressions._ | ||
| import org.apache.spark.sql.catalyst.planning.PhysicalOperation | ||
| import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan | ||
| import org.apache.spark.sql.execution.{PhysicalRDD, SparkPlan} | ||
| import org.apache.spark.sql.sources._ | ||
| import org.apache.spark.sql.types._ | ||
|
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| /** | ||
| * A strategy for planning scans over collections of files that might be partitioned or bucketed | ||
| * by user specified columns. | ||
| * | ||
| * At a high level planning occurs in four phases: | ||
| * - Split filters by when they need to be evaluated. | ||
| * - Prune the schema of the data requested based on any projections present. Today this pruning | ||
| * is only done on top level columns, but formats should support pruning of nested columns as | ||
| * well. | ||
| * - Construct a reader function by passing filters and the schema into the FileFormat. | ||
| * - Using an partition pruning predicates, enumerate the list of files that should be read. | ||
| * - Split the files into tasks and construct a FileScanRDD | ||
| * - Add any projection or filters that must be evaluated after the scan. | ||
| * | ||
| * Files are assigned into tasks using the following algorithm: | ||
| * - If the table is bucketed: group files by bucket id into the correct number of partitions. | ||
| * - If the table is not bucketed or bucketing is turned off: | ||
| * - If any file is larger than the threshold, split it into pieces based on that threshold | ||
| * - Sort the files by decreasing file size. | ||
| * - Assign the ordered files to buckets using the following algorithm. If the current partition | ||
| * is under the threshold with the addition of the next file, add it. If not, open a new bucket | ||
| * and add it. Proceed to the next file. | ||
| */ | ||
| private[sql] object FileSourceStrategy extends Strategy with Logging { | ||
| def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { | ||
| case PhysicalOperation(projects, filters, l@LogicalRelation(files: HadoopFsRelation, _, _)) | ||
| if files.fileFormat.toString == "TestFileFormat" => | ||
| // Filters on this relation fall into four categories based on where we can use them to avoid | ||
| // reading unneeded data: | ||
| // - partition keys only - used to prune directories to read | ||
| // - bucket keys only - optionally used to prune files to read | ||
| // - keys stored in the data only - optionally used to skip groups of data in files | ||
| // - filters that need to be evaluated again after the scan | ||
| val filterSet = ExpressionSet(filters) | ||
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| val partitionColumns = | ||
| AttributeSet(l.resolve(files.partitionSchema, files.sqlContext.analyzer.resolver)) | ||
| val partitionKeyFilters = | ||
| ExpressionSet(filters.filter(_.references.subsetOf(partitionColumns))) | ||
| logInfo(s"Pruning directories with: ${partitionKeyFilters.mkString(",")}") | ||
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| val bucketColumns = | ||
| AttributeSet( | ||
| files.bucketSpec | ||
| .map(_.bucketColumnNames) | ||
| .getOrElse(Nil) | ||
| .map(l.resolveQuoted(_, files.sqlContext.conf.resolver) | ||
| .getOrElse(sys.error("")))) | ||
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| // Partition keys are not available in the statistics of the files. | ||
| val dataFilters = filters.filter(_.references.intersect(partitionColumns).isEmpty) | ||
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| // Predicates with both partition keys and attributes need to be evaluated after the scan. | ||
| val afterScanFilters = filterSet -- partitionKeyFilters | ||
| logInfo(s"Post-Scan Filters: ${afterScanFilters.mkString(",")}") | ||
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| val selectedPartitions = files.location.listFiles(partitionKeyFilters.toSeq) | ||
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| val filterAttributes = AttributeSet(afterScanFilters) | ||
| val requiredExpressions: Seq[NamedExpression] = filterAttributes.toSeq ++ projects | ||
| val requiredAttributes = AttributeSet(requiredExpressions).map(_.name).toSet | ||
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| val prunedDataSchema = | ||
| StructType( | ||
| files.dataSchema.filter(f => requiredAttributes.contains(f.name))) | ||
| logInfo(s"Pruned Data Schema: ${prunedDataSchema.simpleString(5)}") | ||
|
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| val pushedDownFilters = dataFilters.flatMap(DataSourceStrategy.translateFilter) | ||
| logInfo(s"Pushed Filters: ${pushedDownFilters.mkString(",")}") | ||
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| val readFile = files.fileFormat.buildReader( | ||
| sqlContext = files.sqlContext, | ||
| partitionSchema = files.partitionSchema, | ||
| dataSchema = prunedDataSchema, | ||
| filters = pushedDownFilters, | ||
| options = files.options) | ||
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| val plannedPartitions = files.bucketSpec match { | ||
| case Some(bucketing) if files.sqlContext.conf.bucketingEnabled => | ||
| logInfo(s"Planning with ${bucketing.numBuckets} buckets") | ||
| val bucketed = | ||
| selectedPartitions | ||
| .flatMap { p => | ||
| p.files.map(f => PartitionedFile(p.values, f.getPath.toUri.toString, 0, f.getLen)) | ||
| }.groupBy { f => | ||
| BucketingUtils | ||
| .getBucketId(new Path(f.filePath).getName) | ||
| .getOrElse(sys.error(s"Invalid bucket file ${f.filePath}")) | ||
| } | ||
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| (0 until bucketing.numBuckets).map { bucketId => | ||
| FilePartition(bucketId, bucketed.getOrElse(bucketId, Nil)) | ||
| } | ||
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| case _ => | ||
| val maxSplitBytes = files.sqlContext.conf.filesMaxPartitionBytes | ||
| logInfo(s"Planning scan with bin packing, max size: $maxSplitBytes bytes") | ||
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| val splitFiles = selectedPartitions.flatMap { partition => | ||
| partition.files.flatMap { file => | ||
| assert(file.getLen != 0) | ||
| (0L to file.getLen by maxSplitBytes).map { offset => | ||
| val remaining = file.getLen - offset | ||
| val size = if (remaining > maxSplitBytes) maxSplitBytes else remaining | ||
| PartitionedFile(partition.values, file.getPath.toUri.toString, offset, size) | ||
| } | ||
| } | ||
| }.toArray.sortBy(_.length)(implicitly[Ordering[Long]].reverse) | ||
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| val partitions = new ArrayBuffer[FilePartition] | ||
| val currentFiles = new ArrayBuffer[PartitionedFile] | ||
| var currentSize = 0L | ||
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| /** Add the given file to the current partition. */ | ||
| def addFile(file: PartitionedFile): Unit = { | ||
| currentSize += file.length | ||
| currentFiles.append(file) | ||
| } | ||
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| /** Close the current partition and move to the next. */ | ||
| def closePartition(): Unit = { | ||
| if (currentFiles.nonEmpty) { | ||
| val newPartition = | ||
| FilePartition( | ||
| partitions.size, | ||
| currentFiles.toArray.toSeq) // Copy to a new Array. | ||
| partitions.append(newPartition) | ||
| } | ||
| currentFiles.clear() | ||
| currentSize = 0 | ||
| } | ||
|
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| // Assign files to partitions using "First Fit Decreasing" (FFD) | ||
| // TODO: consider adding a slop factor here? | ||
| splitFiles.foreach { file => | ||
| if (currentSize + file.length > maxSplitBytes) { | ||
| closePartition() | ||
| addFile(file) | ||
| } else { | ||
| addFile(file) | ||
| } | ||
| } | ||
| closePartition() | ||
| partitions | ||
| } | ||
|
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| val scan = | ||
| PhysicalRDD( | ||
| l.output, | ||
| new FileScanRDD( | ||
| files.sqlContext, | ||
| readFile, | ||
| plannedPartitions), | ||
| "FileScan", | ||
| Map("format" -> files.fileFormat.toString)) | ||
|
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| val afterScanFilter = afterScanFilters.toSeq.reduceOption(expressions.And) | ||
| val withFilter = afterScanFilter.map(execution.Filter(_, scan)).getOrElse(scan) | ||
| val withProjections = if (projects.forall(_.isInstanceOf[AttributeReference])) { | ||
| withFilter | ||
| } else { | ||
| execution.Project(projects, withFilter) | ||
| } | ||
|
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| withProjections :: Nil | ||
|
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| case _ => Nil | ||
| } | ||
| } |
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