[VL][Delta] Add JVM Delta DV scan handoff

backends-velox/src-delta33/main/scala/org/apache/gluten/backendsapi/velox/VeloxDeltaMetadataUtils.scala

@@ -0,0 +1,157 @@
+/*
+ * 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.backendsapi.velox
+
+import org.apache.gluten.backendsapi.velox.VeloxIteratorApi.unescapePathName
+import org.apache.gluten.sql.shims.SparkShimLoader
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.delta.actions.DeletionVectorDescriptor
+import org.apache.spark.sql.delta.deletionvectors.{RoaringBitmapArrayFormat, StoredBitmap}
+import org.apache.spark.sql.delta.storage.dv.HadoopFileSystemDVStore
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+
+import org.apache.hadoop.fs.Path
+
+import java.util.{ArrayList => JArrayList, HashMap => JHashMap, List => JList, Map => JMap}
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+import scala.util.control.NonFatal
+
+object VeloxDeltaMetadataUtils {
+  val DeltaDvCardinality = "delta_dv_cardinality"
+  val DeltaDvPayloadIndex = "delta_dv_payload_index"
+
+  private val RowIndexFilterIdEncoded = "row_index_filter_id_encoded"
+  private val RowIndexFilterType = "row_index_filter_type"
+  private val RowIndexFilterTypeIfContained = "IF_CONTAINED"
+
+  final class NormalizedSplitMetadata(
+      val otherMetadataColumns: JList[JMap[String, Object]],
+      val deletionVectorPayloads: Array[Array[Byte]])
+    extends Serializable
+
+  private def decodeDescriptor(
+      normalizedMetadata: JMap[String, Object]): Option[DeletionVectorDescriptor] = {
+    Option(normalizedMetadata.get(RowIndexFilterIdEncoded))
+      .map(_.toString)
+      .filter(_.nonEmpty)
+      .flatMap(encoded => Try(DeletionVectorDescriptor.deserializeFromBase64(encoded)).toOption)
+  }
+
+  private def serializePayload(
+      dvStore: HadoopFileSystemDVStore,
+      tablePath: Path,
+      descriptor: DeletionVectorDescriptor): Array[Byte] = {
+    if (tablePath == null) {
+      throw new IllegalStateException(
+        "Unable to resolve Delta table path while materializing deletion vector payload")
+    }
+    StoredBitmap
+      .create(descriptor, tablePath)
+      .load(dvStore)
+      .serializeAsByteArray(RoaringBitmapArrayFormat.Portable)
+  }
+
+  private def normalizeMetadataWithDescriptor(
+      metadata: JMap[String, Object],
+      descriptor: DeletionVectorDescriptor): JMap[String, Object] = {
+    val normalized = new JHashMap[String, Object]()
+    if (metadata != null) {
+      normalized.putAll(metadata)
+    }
+    normalized.put(DeltaDvCardinality, Long.box(descriptor.cardinality))
+    normalized.remove(RowIndexFilterIdEncoded)
+    if (!normalized.containsKey(RowIndexFilterType)) {
+      normalized.put(RowIndexFilterType, RowIndexFilterTypeIfContained)
+    }
+    normalized
+  }
+
+  def normalizeSplitMetadata(
+      partitionColumnCount: Int,
+      files: JList[PartitionedFile]): NormalizedSplitMetadata = {
+    val dvStore = new HadoopFileSystemDVStore(activeSpark.sessionState.newHadoopConf())
+    val normalizedMetadataColumns = new JArrayList[JMap[String, Object]](files.size())
+    val deletionVectorPayloads = scala.collection.mutable.ArrayBuffer.empty[Array[Byte]]
+
+    files.asScala.foreach {
+      file =>
+        val otherMetadata =
+          SparkShimLoader.getSparkShims.getOtherConstantMetadataColumnValues(file)
+        val metadataWithDecodedPayload = new JHashMap[String, Object]()
+        if (otherMetadata != null) {
+          metadataWithDecodedPayload.putAll(otherMetadata)
+        }
+
+        val descriptor = decodeDescriptor(metadataWithDecodedPayload)
+
+        descriptor match {
+          case Some(descriptor) =>
+            val normalized = normalizeMetadataWithDescriptor(metadataWithDecodedPayload, descriptor)
+            val payloadTablePath = resolveTablePath(partitionColumnCount, file)
+            val serializedPayload = serializePayload(dvStore, payloadTablePath, descriptor)
+            normalized.put(DeltaDvPayloadIndex, Int.box(deletionVectorPayloads.length))
+            deletionVectorPayloads += serializedPayload
+            normalizedMetadataColumns.add(normalized)
+          case None =>
+            normalizedMetadataColumns.add(metadataWithDecodedPayload)
+        }
+    }
+
+    new NormalizedSplitMetadata(normalizedMetadataColumns, deletionVectorPayloads.toArray)
+  }
+
+  private def activeSpark: SparkSession = {
+    SparkSession.getActiveSession
+      .orElse(SparkSession.getDefaultSession)
+      .getOrElse {
+        throw new IllegalStateException(
+          "Active SparkSession is required to materialize Delta deletion vectors")
+      }
+  }
+
+  private def resolveTablePath(partitionColumnCount: Int, file: PartitionedFile): Path = {
+    val fileParent = new Path(unescapePathName(file.filePath.toString)).getParent
+    var tablePath = fileParent
+    for (_ <- 0 until partitionColumnCount) {
+      tablePath = tablePath.getParent
+    }
+    val spark = activeSpark
+    if (tablePath != null && isDeltaTablePath(spark, tablePath)) {
+      return tablePath
+    }
+
+    // Spark can report a partition column count that does not map 1:1 to path depth for
+    // prepared Delta scans. Find the nearest ancestor of the file path that has _delta_log.
+    var candidate = fileParent
+    while (candidate != null && !isDeltaTablePath(spark, candidate)) {
+      candidate = candidate.getParent
+    }
+    if (candidate != null) candidate else tablePath
+  }
+
+  private def isDeltaTablePath(spark: SparkSession, tablePath: Path): Boolean = {
+    val deltaLogPath = new Path(tablePath, "_delta_log")
+    try {
+      deltaLogPath.getFileSystem(spark.sessionState.newHadoopConf()).exists(deltaLogPath)
+    } catch {
+      case NonFatal(_) => false
+    }
+  }
+}

backends-velox/src-delta33/main/scala/org/apache/spark/sql/delta/PreprocessTableWithDVs.scala

@@ -0,0 +1,228 @@
+/*
+ * 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.spark.sql.delta
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, EqualTo, Literal}
+import org.apache.spark.sql.catalyst.expressions.Literal.TrueLiteral
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.delta.DeltaParquetFileFormat._
+import org.apache.spark.sql.delta.commands.DeletionVectorUtils.deletionVectorsReadable
+import org.apache.spark.sql.delta.files.{TahoeFileIndex, TahoeLogFileIndex}
+import org.apache.spark.sql.delta.sources.DeltaSQLConf
+import org.apache.spark.sql.execution.datasources.FileFormat.METADATA_NAME
+import org.apache.spark.sql.execution.datasources.HadoopFsRelation
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.types.StructType
+
+/**
+ * Rewrites Delta scans over DV-enabled tables to request the backend-specific skip-row metadata
+ * column only when the snapshot actually contains DVs.
+ */
+trait PreprocessTableWithDVs extends SubqueryTransformerHelper {
+  def preprocessTablesWithDVs(plan: LogicalPlan): LogicalPlan = {
+    transformWithSubqueries(plan) { case ScanWithDeletionVectors(dvScan) => dvScan }
+  }
+}
+
+object ScanWithDeletionVectors {
+  def unapply(a: LogicalRelation): Option[LogicalPlan] = a match {
+    case scan @ LogicalRelation(
+          relation @ HadoopFsRelation(
+            index: TahoeFileIndex,
+            _,
+            _,
+            _,
+            format: DeltaParquetFileFormat,
+            _),
+          _,
+          _,
+          _) =>
+      dvEnabledScanFor(scan, relation, format, index)
+    case scan @ LogicalRelation(
+          relation @ HadoopFsRelation(
+            index: TahoeFileIndex,
+            _,
+            _,
+            _,
+            format: GlutenDeltaParquetFileFormat,
+            _),
+          _,
+          _,
+          _) =>
+      dvEnabledScanFor(scan, relation, format, index)
+    case _ => None
+  }
+
+  def dvEnabledScanFor(
+      scan: LogicalRelation,
+      hadoopRelation: HadoopFsRelation,
+      fileFormat: DeltaParquetFileFormat,
+      index: TahoeFileIndex): Option[LogicalPlan] = {
+    if (!deletionVectorsReadable(index.protocol, index.metadata)) {
+      return None
+    }
+
+    require(
+      !index.isInstanceOf[TahoeLogFileIndex],
+      "Cannot work with a non-pinned table snapshot of the TahoeFileIndex")
+
+    if (fileFormat.hasTablePath) {
+      return None
+    }
+
+    val filesWithDVs = index
+      .matchingFiles(partitionFilters = Seq(TrueLiteral), dataFilters = Seq(TrueLiteral))
+      .filter(_.deletionVector != null)
+    if (filesWithDVs.isEmpty) {
+      return None
+    }
+
+    val planOutput = scan.output
+    val spark = SparkSession.getActiveSession.get
+    val newScan = createScanWithSkipRowColumn(spark, scan, fileFormat, index, hadoopRelation)
+    val rowIndexFilter = createRowIndexFilterNode(newScan)
+    Some(Project(planOutput, rowIndexFilter))
+  }
+
+  def dvEnabledScanFor(
+      scan: LogicalRelation,
+      hadoopRelation: HadoopFsRelation,
+      fileFormat: GlutenDeltaParquetFileFormat,
+      index: TahoeFileIndex): Option[LogicalPlan] = {
+    if (!deletionVectorsReadable(index.protocol, index.metadata)) {
+      return None
+    }
+
+    require(
+      !index.isInstanceOf[TahoeLogFileIndex],
+      "Cannot work with a non-pinned table snapshot of the TahoeFileIndex")
+
+    if (fileFormat.hasTablePath) {
+      return None
+    }
+
+    val filesWithDVs = index
+      .matchingFiles(partitionFilters = Seq(TrueLiteral), dataFilters = Seq(TrueLiteral))
+      .filter(_.deletionVector != null)
+    if (filesWithDVs.isEmpty) {
+      return None
+    }
+
+    val planOutput = scan.output
+    val spark = SparkSession.getActiveSession.get
+    val newScan = createScanWithSkipRowColumn(spark, scan, fileFormat, index, hadoopRelation)
+    val rowIndexFilter = createRowIndexFilterNode(newScan)
+    Some(Project(planOutput, rowIndexFilter))
+  }
+
+  private def addRowIndexIfMissing(attribute: AttributeReference): AttributeReference = {
+    require(attribute.name == METADATA_NAME)
+
+    val dataType = attribute.dataType.asInstanceOf[StructType]
+    if (dataType.fieldNames.contains(ParquetFileFormat.ROW_INDEX)) {
+      return attribute
+    }
+
+    val newDatatype = dataType.add(ParquetFileFormat.ROW_INDEX_FIELD)
+    attribute.copy(dataType = newDatatype)(
+      exprId = attribute.exprId,
+      qualifier = attribute.qualifier)
+  }
+
+  private def createScanWithSkipRowColumn(
+      spark: SparkSession,
+      inputScan: LogicalRelation,
+      fileFormat: DeltaParquetFileFormat,
+      tahoeFileIndex: TahoeFileIndex,
+      hadoopFsRelation: HadoopFsRelation): LogicalRelation = {
+    val useMetadataRowIndex =
+      spark.sessionState.conf.getConf(DeltaSQLConf.DELETION_VECTORS_USE_METADATA_ROW_INDEX)
+
+    val skipRowField = IS_ROW_DELETED_STRUCT_FIELD
+    val scanOutputWithMetadata = if (useMetadataRowIndex) {
+      if (inputScan.output.map(_.name).contains(METADATA_NAME)) {
+        inputScan.output.collect {
+          case a: AttributeReference if a.name == METADATA_NAME => addRowIndexIfMissing(a)
+          case o => o
+        }
+      } else {
+        inputScan.output :+ fileFormat.createFileMetadataCol()
+      }
+    } else {
+      inputScan.output
+    }
+
+    val newScanOutput =
+      scanOutputWithMetadata :+ AttributeReference(skipRowField.name, skipRowField.dataType)()
+    val newDataSchema = hadoopFsRelation.dataSchema.add(skipRowField)
+    val newFileFormat = fileFormat.copyWithDVInfo(
+      tablePath = tahoeFileIndex.path.toString,
+      optimizationsEnabled = useMetadataRowIndex)
+
+    val newRelation = hadoopFsRelation.copy(fileFormat = newFileFormat, dataSchema = newDataSchema)(
+      hadoopFsRelation.sparkSession)
+
+    inputScan.copy(relation = newRelation, output = newScanOutput)
+  }
+
+  private def createScanWithSkipRowColumn(
+      spark: SparkSession,
+      inputScan: LogicalRelation,
+      fileFormat: GlutenDeltaParquetFileFormat,
+      tahoeFileIndex: TahoeFileIndex,
+      hadoopFsRelation: HadoopFsRelation): LogicalRelation = {
+    val useMetadataRowIndex =
+      spark.sessionState.conf.getConf(DeltaSQLConf.DELETION_VECTORS_USE_METADATA_ROW_INDEX)
+
+    val skipRowField = GlutenDeltaParquetFileFormat.IS_ROW_DELETED_STRUCT_FIELD
+    val scanOutputWithMetadata = if (useMetadataRowIndex) {
+      if (inputScan.output.map(_.name).contains(METADATA_NAME)) {
+        inputScan.output.collect {
+          case a: AttributeReference if a.name == METADATA_NAME => addRowIndexIfMissing(a)
+          case o => o
+        }
+      } else {
+        inputScan.output :+ fileFormat.createFileMetadataCol()
+      }
+    } else {
+      inputScan.output
+    }
+
+    val newScanOutput =
+      scanOutputWithMetadata :+ AttributeReference(skipRowField.name, skipRowField.dataType)()
+    val newDataSchema = hadoopFsRelation.dataSchema.add(skipRowField)
+    val newFileFormat = fileFormat.copyWithDVInfo(
+      tablePath = tahoeFileIndex.path.toString,
+      optimizationsEnabled = useMetadataRowIndex)
+
+    val newRelation = hadoopFsRelation.copy(fileFormat = newFileFormat, dataSchema = newDataSchema)(
+      hadoopFsRelation.sparkSession)
+
+    inputScan.copy(relation = newRelation, output = newScanOutput)
+  }
+
+  private def createRowIndexFilterNode(newScan: LogicalRelation): Filter = {
+    val skipRowColumnRefs = newScan.output.filter(_.name == IS_ROW_DELETED_COLUMN_NAME)
+    require(
+      skipRowColumnRefs.size == 1,
+      s"Expected only one column with name=$IS_ROW_DELETED_COLUMN_NAME")
+    val skipRowColumnRef = skipRowColumnRefs.head
+    Filter(EqualTo(skipRowColumnRef, Literal(RowIndexFilter.KEEP_ROW_VALUE)), newScan)
+  }
+}