zhztheplayer commented on code in PR #10186: URL: https://github.com/apache/incubator-gluten/pull/10186#discussion_r2256877006
########## gluten-paimon/src-paimon/main/scala/org/apache/gluten/execution/PaimonScanTransformer.scala: ########## @@ -0,0 +1,210 @@ +/* + * 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. + */ +package org.apache.gluten.execution + +import org.apache.gluten.exception.GlutenNotSupportException +import org.apache.gluten.sql.shims.SparkShimLoader +import org.apache.gluten.substrait.rel.{PaimonLocalFilesBuilder, SplitInfo} +import org.apache.gluten.substrait.rel.LocalFilesNode.ReadFileFormat + +import org.apache.spark.rdd.RDD +import org.apache.spark.softaffinity.SoftAffinity +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.catalog.ExternalCatalogUtils +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, DynamicPruningExpression, Expression, Literal} +import org.apache.spark.sql.catalyst.plans.QueryPlan +import org.apache.spark.sql.connector.catalog.Table +import org.apache.spark.sql.connector.read.{InputPartition, Scan} +import org.apache.spark.sql.execution.datasources.v2.BatchScanExec +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.vectorized.ColumnarBatch + +import org.apache.paimon.CoreOptions +import org.apache.paimon.spark.{PaimonInputPartition, PaimonScan} +import org.apache.paimon.table.{DataTable, FileStoreTable} +import org.apache.paimon.table.source.DataSplit +import org.apache.paimon.utils.InternalRowPartitionComputer + +import java.lang.{Long => JLong} +import java.util.{HashMap => JHashMap, Map => JMap} + +import scala.collection.JavaConverters._ +import scala.collection.mutable + +case class PaimonScanTransformer( + override val output: Seq[AttributeReference], + @transient override val scan: Scan, + override val runtimeFilters: Seq[Expression], + @transient override val table: Table, + override val keyGroupedPartitioning: Option[Seq[Expression]] = None, + override val commonPartitionValues: Option[Seq[(InternalRow, Int)]] = None) + extends BatchScanExecTransformerBase( + output = output, + scan = scan, + runtimeFilters = runtimeFilters, + table = table, + keyGroupedPartitioning = keyGroupedPartitioning, + commonPartitionValues = commonPartitionValues + ) { + + private lazy val coreOptions: CoreOptions = scan match { + case scan: PaimonScan => + scan.table match { + case dataTable: DataTable => + dataTable.coreOptions() + case _ => + throw new GlutenNotSupportException("Only support Paimon DataTable.") + } + case _ => + throw new GlutenNotSupportException("Only support PaimonScan.") + } + + override def filterExprs(): Seq[Expression] = pushdownFilters + + override def getPartitionSchema: StructType = scan match { + case paimonScan: PaimonScan => + val partitionKeys = paimonScan.table.partitionKeys() + StructType(scan.readSchema().filter(field => partitionKeys.contains(field.name))) + case _ => + throw new GlutenNotSupportException("Only support PaimonScan.") + } + + override def getDataSchema: StructType = new StructType() + + override lazy val fileFormat: ReadFileFormat = { + val formatStr = coreOptions.fileFormatString() + if ("parquet".equalsIgnoreCase(formatStr)) { + ReadFileFormat.ParquetReadFormat + } else if ("orc".equalsIgnoreCase(formatStr)) { + ReadFileFormat.OrcReadFormat + } else { + ReadFileFormat.UnknownFormat + } + } + + override def doValidateInternal(): ValidationResult = { + scan match { + case paimonScan: PaimonScan => + paimonScan.table match { + case table: FileStoreTable => + if (fileFormat == ReadFileFormat.UnknownFormat) { + return ValidationResult.failed("Only support parquet/orc Paimon table.") + } + if (!table.primaryKeys().isEmpty || coreOptions.deletionVectorsEnabled()) { + return ValidationResult.failed("Not support Paimon PK/DV table.") + } + case table => + return ValidationResult.failed( + s"Not support Paimon ${table.getClass.getSimpleName} table.") + } + case _ => + return ValidationResult.failed("Only support PaimonScan.") + } + super.doValidateInternal() + } + + override def doExecuteColumnar(): RDD[ColumnarBatch] = throw new UnsupportedOperationException() + + override def getSplitInfosFromPartitions(partitions: Seq[InputPartition]): Seq[SplitInfo] = { + val partitionComputer = PaimonScanTransformer.getRowDataPartitionComputer(scan) + getPartitions.zipWithIndex.map { + case (p, index) => + p match { + case partition: PaimonInputPartition => + val paths = mutable.ListBuffer.empty[String] + val starts = mutable.ListBuffer.empty[JLong] + val lengths = mutable.ListBuffer.empty[JLong] + val partitionColumns = mutable.ListBuffer.empty[JMap[String, String]] + partition.splits.foreach { + split => + val rawFilesOpt = split.convertToRawFiles() + if (rawFilesOpt.isPresent) { + val partitionRow = split.asInstanceOf[DataSplit].partition() + val partitionCols = partitionComputer.generatePartValues(partitionRow) + val rawFiles = rawFilesOpt.get().asScala + paths ++= rawFiles.map(_.path()) + starts ++= rawFiles.map(file => JLong.valueOf(file.offset())) + lengths ++= rawFiles.map(file => JLong.valueOf(file.length())) + partitionColumns ++= mutable.ArrayBuffer.fill(rawFiles.size)(partitionCols) + } else { + throw new GlutenNotSupportException( + "Cannot get raw files from paimon SparkInputPartition.") + } + } + val preferredLoc = + SoftAffinity.getFilePartitionLocations(paths.toArray, partition.preferredLocations()) + PaimonLocalFilesBuilder.makePaimonLocalFiles( + index, + paths.asJava, + starts.asJava, + lengths.asJava, + partitionColumns.asJava, + fileFormat, + preferredLoc.toList.asJava, + new JHashMap[String, String]() + ) + case _ => + throw new GlutenNotSupportException("Only support paimon SparkInputPartition.") + } + } + } + + override def doCanonicalize(): PaimonScanTransformer = { + this.copy( + output = output.map(QueryPlan.normalizeExpressions(_, output)), + runtimeFilters = QueryPlan.normalizePredicates( + runtimeFilters.filterNot(_ == DynamicPruningExpression(Literal.TrueLiteral)), + output) + ) + } + + override protected[this] def supportsBatchScan(scan: Scan): Boolean = + PaimonScanTransformer.supportsBatchScan(scan) +} + +object PaimonScanTransformer { + def apply(batchScan: BatchScanExec): PaimonScanTransformer = { + new PaimonScanTransformer( + batchScan.output, + batchScan.scan, + batchScan.runtimeFilters, + table = SparkShimLoader.getSparkShims.getBatchScanExecTable(batchScan), + keyGroupedPartitioning = SparkShimLoader.getSparkShims.getKeyGroupedPartitioning(batchScan), + commonPartitionValues = SparkShimLoader.getSparkShims.getCommonPartitionValues(batchScan) + ) + } + + private def getRowDataPartitionComputer(scan: Scan): InternalRowPartitionComputer = { + scan match { + case paimonScan: PaimonScan => + val table = paimonScan.table.asInstanceOf[FileStoreTable] + // use __HIVE_DEFAULT_PARTITION__ because velox using this + new InternalRowPartitionComputer( + ExternalCatalogUtils.DEFAULT_PARTITION_NAME, + table.schema().logicalPartitionType(), + table.partitionKeys.asScala.toArray, + false + ) + case _ => + throw new GlutenNotSupportException("Only support PaimonScan.") + } + } + + def supportsBatchScan(scan: Scan): Boolean = { + scan.getClass.getName == "org.apache.paimon.spark.PaimonScan" Review Comment: nit: Are we able to do `scan.isInstanceOf` here? -- This is an automated message from the Apache Git Service. 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