[VL][Delta] Add native deletion vector scan foundation

backends-velox/src-delta33/main/scala/org/apache/gluten/backendsapi/velox/VeloxDeltaMetadataUtils.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.
+ */
+package org.apache.gluten.backendsapi.velox
+
+import org.apache.spark.sql.delta.actions.DeletionVectorDescriptor
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+
+import org.apache.hadoop.fs.Path
+
+import java.util.{HashMap => JHashMap, Map => JMap}
+
+object VeloxDeltaMetadataUtils {
+  val DeltaDvStorageType = "delta_dv_storage_type"
+  val DeltaDvPathOrInline = "delta_dv_path_or_inline"
+  val DeltaDvOffset = "delta_dv_offset"
+  val DeltaDvSizeInBytes = "delta_dv_size_in_bytes"
+  val DeltaDvCardinality = "delta_dv_cardinality"
+
+  private val RowIndexFilterIdEncoded = "row_index_filter_id_encoded"
+
+  def normalizeOtherMetadataColumns(
+      partitionColumnCount: Int,
+      file: PartitionedFile,
+      otherConstantMetadataColumnValues: JMap[String, Object]): JMap[String, Object] = {
+    val normalized = new JHashMap[String, Object]()
+    if (otherConstantMetadataColumnValues != null) {
+      normalized.putAll(otherConstantMetadataColumnValues)
+    }
+
+    Option(normalized.get(RowIndexFilterIdEncoded)).map(_.toString).foreach {
+      encodedDescriptor =>
+        val descriptor = DeletionVectorDescriptor.deserializeFromBase64(encodedDescriptor)
+        descriptor.storageType match {
+          case "i" =>
+            normalized.put(DeltaDvStorageType, descriptor.storageType)
+            normalized.put(DeltaDvPathOrInline, descriptor.pathOrInlineDv)
+          case _ =>
+            val absolutePath =
+              descriptor.absolutePath(resolveTablePath(partitionColumnCount, file))
+            normalized.put(DeltaDvStorageType, "p")
+            normalized.put(DeltaDvPathOrInline, absolutePath.toUri.toASCIIString)
+        }
+        descriptor.offset.foreach(offset => normalized.put(DeltaDvOffset, Int.box(offset)))
+        normalized.put(DeltaDvSizeInBytes, Int.box(descriptor.sizeInBytes))
+        normalized.put(DeltaDvCardinality, Long.box(descriptor.cardinality))
+        normalized.remove(RowIndexFilterIdEncoded)
+    }
+
+    normalized
+  }
+
+  private def resolveTablePath(partitionColumnCount: Int, file: PartitionedFile): Path = {
+    var tablePath = new Path(file.filePath.toString).getParent
+    for (_ <- 0 until partitionColumnCount) {
+      tablePath = tablePath.getParent
+    }
+    tablePath
+  }
+}

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)
+  }
+}

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

@@ -0,0 +1,58 @@
+/*
+ * 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.stats
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, V2WriteCommand}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.delta.{DeltaTable, OptimisticTransaction, PreprocessTableWithDVs}
+import org.apache.spark.sql.delta.sources.DeltaSQLConf
+
+/** Shadow Delta's PrepareDeltaScan to inject backend-specific DV preprocessing. */
+class PrepareDeltaScan(protected val spark: SparkSession)
+  extends Rule[LogicalPlan]
+  with PrepareDeltaScanBase
+  with PreprocessTableWithDVs {
+
+  override def apply(plan0: LogicalPlan): LogicalPlan = {
+    var plan = plan0
+
+    val isSubquery = isSubqueryRoot(plan)
+    val isDataSourceV2 = plan.isInstanceOf[V2WriteCommand]
+    if (isSubquery || isDataSourceV2) {
+      return plan
+    }
+
+    val updatedPlan = if (spark.sessionState.conf.getConf(DeltaSQLConf.DELTA_STATS_SKIPPING)) {
+      if (spark.sessionState.conf.getConf(DeltaSQLConf.DELTA_OPTIMIZE_METADATA_QUERY_ENABLED)) {
+        plan = optimizeQueryWithMetadata(plan)
+      }
+      prepareDeltaScan(plan)
+    } else {
+      OptimisticTransaction.getActive.foreach {
+        txn =>
+          val logsInPlan = plan.collect { case DeltaTable(fileIndex) => fileIndex.deltaLog }
+          if (logsInPlan.exists(_.isSameLogAs(txn.deltaLog))) {
+            txn.readWholeTable()
+          }
+      }
+      plan
+    }
+
+    preprocessTablesWithDVs(updatedPlan)
+  }
+}