Zouxxyy commented on code in PR #8300:
URL: https://github.com/apache/paimon/pull/8300#discussion_r3447788853


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paimon-spark/paimon-spark-common/src/main/scala/org/apache/spark/sql/execution/SparkFormatTableFileIndex.scala:
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@@ -0,0 +1,336 @@
+/*
+ * 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.execution
+
+import org.apache.paimon.CoreOptions
+import org.apache.paimon.spark.catalyst.Compatibility
+import org.apache.paimon.spark.util.OptionUtils
+
+import org.apache.hadoop.fs.{FileStatus, Path}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.catalog.ExternalCatalogUtils
+import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, 
BoundReference, Expression, InterpretedPredicate, Literal, Predicate => 
ExprPredicate}
+import org.apache.spark.sql.execution.datasources._
+import org.apache.spark.sql.paimon.shims.SparkShimLoader
+import org.apache.spark.sql.types.{StringType, StructField, StructType}
+import org.apache.spark.sql.util.CaseInsensitiveStringMap
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+
+/** Factory for creating partition-aware file indexes for format tables. */
+object SparkFormatTableFileIndex {
+
+  def createFileIndex(
+      options: CaseInsensitiveStringMap,
+      sparkSession: SparkSession,
+      paths: Seq[String],
+      userSpecifiedSchema: Option[StructType],
+      partitionSchema: StructType): PartitioningAwareFileIndex = {
+
+    def globPaths: Boolean = {
+      val entry = options.get(DataSource.GLOB_PATHS_KEY)
+      Option(entry).forall(_ == "true")
+    }
+
+    val caseSensitiveMap = options.asCaseSensitiveMap.asScala.toMap
+    val hadoopConf = 
sparkSession.sessionState.newHadoopConfWithOptions(caseSensitiveMap)
+    if (
+      SparkShimLoader.shim.hasFileStreamSinkMetadata(
+        paths,
+        hadoopConf,
+        sparkSession.sessionState.conf)
+    ) {
+      SparkShimLoader.shim.createPartitionedMetadataLogFileIndex(
+        sparkSession,
+        new Path(paths.head),
+        options.asScala.toMap,
+        userSpecifiedSchema,
+        partitionSchema = partitionSchema)
+    } else {
+      val rootPathsSpecified = DataSource.checkAndGlobPathIfNecessary(
+        paths,
+        hadoopConf,
+        checkEmptyGlobPath = true,
+        checkFilesExist = true,
+        enableGlobbing = globPaths)
+      val fileStatusCache = FileStatusCache.getOrCreate(sparkSession)
+
+      val lazyPruning =
+        partitionSchema.nonEmpty && 
OptionUtils.readFormatTableLazyPartitionPruning()
+
+      if (lazyPruning) {
+        new LazyPartitionPruningFileIndex(
+          sparkSession,
+          rootPathsSpecified,
+          caseSensitiveMap,
+          userSpecifiedSchema,
+          fileStatusCache,
+          partitionSchema)
+      } else {
+        new EagerPartitionListingFileIndex(
+          sparkSession,
+          rootPathsSpecified,
+          caseSensitiveMap,
+          userSpecifiedSchema,
+          fileStatusCache,
+          partitionSchema)
+      }
+    }
+  }
+
+  // Visible to shim-local PartitionedMetadataLogFileIndex subclasses.
+  private[sql] def alignPartitionSpec(
+      inferred: PartitionSpec,
+      partitionSchema: StructType): PartitionSpec = {
+    if (inferred.partitionColumns.isEmpty && partitionSchema.nonEmpty) {
+      PartitionSpec(partitionSchema, inferred.partitions)
+    } else {
+      inferred
+    }
+  }
+}
+
+/** Eagerly lists all files at construction time, like the default 
[[InMemoryFileIndex]]. */
+class EagerPartitionListingFileIndex(
+    sparkSession: SparkSession,
+    rootPathsSpecified: Seq[Path],
+    parameters: Map[String, String],
+    userSpecifiedSchema: Option[StructType],
+    fileStatusCache: FileStatusCache,
+    override val partitionSchema: StructType)
+  extends InMemoryFileIndex(
+    sparkSession,
+    rootPathsSpecified,
+    parameters,
+    userSpecifiedSchema,
+    fileStatusCache) {
+
+  override def partitionSpec(): PartitionSpec =
+    SparkFormatTableFileIndex.alignPartitionSpec(super.partitionSpec(), 
partitionSchema)
+}
+
+/**
+ * A [[PartitioningAwareFileIndex]] that prunes partition directories 
level-by-level using partition
+ * filters, similar to [[CatalogFileIndex]] but discovers partitions from the 
filesystem instead of
+ * the metastore.
+ */
+class LazyPartitionPruningFileIndex(
+    sparkSession: SparkSession,
+    tableLocations: Seq[Path],
+    parameters: Map[String, String],
+    userSpecifiedSchema: Option[StructType],
+    fileStatusCache: FileStatusCache,
+    _partitionSchema: StructType)
+  extends PartitioningAwareFileIndex(sparkSession, parameters, 
userSpecifiedSchema, fileStatusCache)
+  with Logging {
+
+  override val rootPaths: Seq[Path] = tableLocations
+
+  override def partitionSchema: StructType = _partitionSchema
+
+  override def equals(other: Any): Boolean = other match {
+    case o: LazyPartitionPruningFileIndex => rootPaths.toSet == 
o.rootPaths.toSet
+    case _ => false
+  }
+
+  override def hashCode(): Int = rootPaths.toSet.hashCode()
+
+  @volatile private var _fullIndex: InMemoryFileIndex = _
+
+  private def fullIndex: InMemoryFileIndex = {
+    if (_fullIndex == null) {
+      synchronized {
+        if (_fullIndex == null) {
+          _fullIndex = new InMemoryFileIndex(
+            sparkSession,
+            tableLocations,
+            parameters,
+            userSpecifiedSchema,
+            fileStatusCache)
+        }
+      }
+    }
+    _fullIndex
+  }
+
+  override def refresh(): Unit = {
+    fileStatusCache.invalidateAll()
+    synchronized { _fullIndex = null }
+  }
+
+  // Required by PartitioningAwareFileIndex but never accessed — all callers 
are overridden.
+  override protected def leafFiles: mutable.LinkedHashMap[Path, FileStatus] =
+    throw new IllegalStateException()
+  override protected def leafDirToChildrenFiles: Map[Path, Array[FileStatus]] =
+    throw new IllegalStateException()
+
+  override def partitionSpec(): PartitionSpec =
+    PartitionSpec(_partitionSchema, Seq.empty)
+
+  override def sizeInBytes: Long = fullIndex.sizeInBytes

Review Comment:
   The 600 files discovered comes from `sizeInBytes` triggered by 
`DataSourceV2ScanRelation.computeStats()` during planning, not from 
`listFiles`. With the `_fullIndex != null` check, filtered `listFiles` reuses 
`fullIndex` for in-memory `prunePartitions` — zero additional FS calls and zero 
additional `FILES_DISCOVERED`. Without it, `discoverPartitions` would create a 
`prunedIndex` whose paths miss `FileStatusCache` (keyed by root path, not 
sub-paths), adding more to the metric (verified: 16 vs 15 in a 5×3 table).
   
   To answer your two questions: (1) `FileScan.estimateStatistics()` calls 
`fileIndex.sizeInBytes` which has no partition filter parameter — to properly 
fix this we'd need to change Spark's `FileScan` to pass partition filters when 
computing stats, which is beyond this PR. (2) Keeping filtered `listFiles` lazy 
after stats are requested would actually be worse — it adds redundant FS calls 
and increases `FILES_DISCOVERED` due to `FileStatusCache` key mismatch.



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