dwsmith1983 commented on code in PR #5365:
URL: https://github.com/apache/datafusion-comet/pull/5365#discussion_r4081142447


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contrib/delta-spark/src/main/scala/org/apache/comet/contrib/delta/CometDeltaNativeScan.scala:
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@@ -0,0 +1,583 @@
+/*
+ * 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.comet.contrib.delta
+
+import scala.jdk.CollectionConverters._
+
+import org.apache.hadoop.fs.Path
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.catalyst.expressions.Literal
+import org.apache.spark.sql.comet.{CometScanExec, DeltaPlanDataInjector}
+import org.apache.spark.sql.delta.DeltaParquetFileFormat
+import org.apache.spark.sql.delta.RowIndexFilterType
+import org.apache.spark.sql.delta.actions.DeletionVectorDescriptor
+import org.apache.spark.sql.execution.{FileSourceScanExec, ScalarSubquery => 
ExecScalarSubquery}
+import org.apache.spark.sql.execution.datasources.{FilePartition, 
PartitionedFile}
+import org.apache.spark.sql.types.{ByteType, LongType, MetadataBuilder, 
StructField, StructType}
+
+import org.apache.comet.objectstore.NativeConfig
+import org.apache.comet.serde.OperatorOuterClass
+import org.apache.comet.serde.OperatorOuterClass.Operator
+import org.apache.comet.serde.QueryPlanSerde.{exprToProto, serializeDataType}
+import org.apache.comet.serde.operator.{literalToProto, partition2Proto, 
schema2Proto, CometNativeScan}
+import org.apache.comet.shims.ShimFileFormat
+
+/**
+ * Serde for the native Delta scan. Two shapes:
+ *   - Plain reads reuse core's `NativeScanCommon` builder wholesale.
+ *   - Deletion-vector reads: Delta's planner appends 
`__delta_internal_is_row_deleted` (tinyint)
+ *     and Spark's row-index temp column (bigint) to the read schema and 
filters on is_row_deleted
+ *     above the scan. The native reader applies the DV as a row selection, so 
both internal
+ *     columns are emitted as per-file constants (0), the parquet read schema 
is stripped to the
+ *     real data columns, and the DV descriptor ships per file for native to 
fetch and decode.
+ */
+object CometDeltaNativeScan
+    extends Logging
+    with org.apache.spark.sql.catalyst.expressions.PredicateHelper {
+
+  val IsRowDeletedColumn: String = 
DeltaParquetFileFormat.IS_ROW_DELETED_COLUMN_NAME
+  val RowIndexColumn: String = ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME
+
+  private[delta] val internalColumnNames: Set[String] = 
Set(IsRowDeletedColumn, RowIndexColumn)
+
+  // Prefix for the internal columns' slots in the partition schema, mirroring 
core's
+  // _comet_metadata_ prefix rationale: DataFusion matches partition columns 
by name.
+  // [[allocateUniqueInternalFields]] additionally suffixes on collision with 
a real column.
+  private val deltaConstFieldPrefix = "_comet_delta_"
+
+  def isDvShape(scanExec: FileSourceScanExec): Boolean =
+    scanExec.requiredSchema.exists(f => internalColumnNames.contains(f.name))
+
+  private def deltaFormat(scanExec: FileSourceScanExec): 
DeltaParquetFileFormat =
+    scanExec.relation.fileFormat.asInstanceOf[DeltaParquetFileFormat]
+
+  private def columnMappingMode(scanExec: FileSourceScanExec): String =
+    deltaFormat(scanExec).metadata.columnMappingMode.name
+
+  /**
+   * Under column mapping, parquet files store physical column names (stable 
UUIDs / ids), so the
+   * schemas passed to the native parquet reader must be physical. Positions 
and structure are
+   * preserved, so output binding and projection are unaffected. The scan's 
internal DV columns
+   * are not part of the table schema and must be stripped before calling this.
+   *
+   * `private[delta]` (not `private`): [[DeltaScanSupport.declineReason]]'s 
non-ASCII
+   * case-insensitive name gate reuses this exact conversion to compute the 
names native sees
+   * under column mapping, rather than re-deriving physical names with 
separate logic.
+   */
+  private[delta] def toPhysical(scanExec: FileSourceScanExec, schema: 
StructType): StructType = {

Review Comment:
   > Could `toPhysical` delegate to 
`DeltaParquetFileFormat.prepareSchemaForRead` instead of duplicating 
`createPhysicalSchema` and name-mode field-ID stripping?
   
   Tracked in #5949, together with keeping the physical read schemas apart from 
the logical output types in `common.fields`.



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