JingsongLi commented on code in PR #8300:
URL: https://github.com/apache/paimon/pull/8300#discussion_r3447754961


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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:
   Spark also asks the scan for statistics while planning some queries. For 
file scans, `estimateStatistics()` calls `fileIndex.sizeInBytes`, so this 
initializes `fullIndex` by recursively listing the whole table before 
`listFiles` can apply the partition filters. I reproduced this on the latest 
head with a 20x30 partitioned format table: `SELECT * FROM t JOIN d ON t.p1 = 
d.p1 WHERE t.p1 = 1` discovers 600 files instead of the expected 30 because 
planning touches `sizeInBytes`, and then `_fullIndex != null` makes the 
filtered read use the eager index too. Could we avoid constructing `fullIndex` 
for lazy-path stats, or keep filtered `listFiles` lazy even after stats are 
requested?



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