cloud-fan commented on code in PR #39408:
URL: https://github.com/apache/spark/pull/39408#discussion_r1069071458


##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala:
##########
@@ -677,4 +677,90 @@ class FileMetadataStructSuite extends QueryTest with 
SharedSparkSession {
     assert(analyzedStruct.fields.forall(!_.nullable), 
analyzedStruct.fields.mkString(", "))
     assert(executedStruct.fields.forall(!_.nullable), 
executedStruct.fields.mkString(", "))
   }
+
+  test("SPARK-41896: Filter on row_index and a stored column at the same 
time") {
+    withTempPath { dir =>
+      val storedIdName = "stored_id"
+      val storedIdUpperLimitExclusive = 520
+      val rowIndexLowerLimitInclusive = 10
+
+      spark.range(start = 500, end = 600)
+        .toDF(storedIdName)
+        .write
+        .format("parquet")
+        .save(dir.getAbsolutePath)
+
+      // Select stored_id 510 to 519 via a stored_id and row_index filter.
+      val collectedRows = spark.read.load(dir.getAbsolutePath)
+        .select(storedIdName, METADATA_ROW_INDEX)
+        .where(col(storedIdName).lt(lit(storedIdUpperLimitExclusive)))
+        .where(col(METADATA_ROW_INDEX).geq(lit(rowIndexLowerLimitInclusive)))
+        .collect()
+
+      assert(collectedRows.length === 10)
+      assert(collectedRows.forall(_.getLong(0) < storedIdUpperLimitExclusive))
+      assert(collectedRows.forall(_.getLong(1) >= rowIndexLowerLimitInclusive))
+    }
+  }
+
+  test("SPARK-41896: Filter on constant and generated metadata attributes at 
the same time") {
+    withTempPath { dir =>
+      val idColumnName = "id"
+      val partitionColumnName = "partition"
+      val numFiles = 4
+      val totalNumRows = 40
+
+      spark.range(end = totalNumRows)
+        .toDF(idColumnName)
+        .withColumn(partitionColumnName, col(idColumnName).mod(lit(numFiles)))
+        .write
+        .partitionBy(partitionColumnName)
+        .format("parquet")
+        .save(dir.getAbsolutePath)
+
+      // Get one file path.
+      val randomTableFilePath = spark.read.load(dir.getAbsolutePath)
+        .select(METADATA_FILE_PATH).collect().head.getString(0)
+
+      val halfTheNumberOfRowsPerFile = totalNumRows / (numFiles * 2)
+      val collectedRows = spark.read.load(dir.getAbsolutePath)
+        .where(col(METADATA_FILE_PATH).equalTo(lit(randomTableFilePath)))
+        .where(col(METADATA_ROW_INDEX).leq(lit(halfTheNumberOfRowsPerFile)))
+        .collect()
+
+      // The query will match half the rows in one of the files.
+      assert(collectedRows.length === halfTheNumberOfRowsPerFile)
+    }
+  }
+
+  test("SPARK-41896: Filter by a function that takes the metadata struct as 
argument") {
+    withTempPath { dir =>
+      val idColumnName = "id"
+      val numFiles = 4
+      spark.range(end = numFiles)
+        .toDF(idColumnName)
+        .withColumn("partition", col(idColumnName))
+        .write
+        .format("parquet")
+        .partitionBy("partition")
+        .save(dir.getAbsolutePath)
+
+      // Select path and partition value for a random file.
+      val testFileData = spark.read.load(dir.getAbsolutePath)
+        .select(idColumnName, METADATA_FILE_PATH).collect().head
+      val testFilePartition = testFileData.getLong(0)
+      val testFilePath = testFileData.getString(1)
+
+      // Create and use a filter using the file path.
+      spark.udf.register("isTestFile",

Review Comment:
   wrap it with `withUserDefinedFunction` to clean up the function at the end



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