[SPARK-57659][SQL] Make SchemaPruning idempotent after variant pushdown

sql/core/src/main/scala/org/apache/spark/sql/execution/SparkOptimizer.scala

@@ -53,7 +53,10 @@ class SparkOptimizer(
       V2ScanPartitioningAndOrdering,
       V2Writes,
       PruneFileSourcePartitions,
-      PushVariantIntoScan)
+      PushVariantIntoScan,
+      // Variant pushdown can make a reconstruction projection unnecessary. Prune again so this
+      // Once batch reaches the same plan on its first application as it would on a second one.
+      SchemaPruning)
 
   override def preCBORules: Seq[Rule[LogicalPlan]] =
     Seq(OptimizeMetadataOnlyDeleteFromTable)

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaPruningSuite.scala

@@ -24,6 +24,7 @@ import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
 import org.apache.spark.sql.execution.datasources.SchemaPruningSuite
 import org.apache.spark.sql.execution.datasources.v2.BatchScanExec
 import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan
+import org.apache.spark.sql.functions.{col, udf}
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.tags.ExtendedSQLTest
 
@@ -42,6 +43,23 @@ class ParquetV1SchemaPruningSuite extends ParquetSchemaPruningSuite {
     super
       .sparkConf
       .set(SQLConf.USE_V1_SOURCE_LIST, "parquet")
+
+  test("SPARK-57659: SchemaPruning is idempotent with metadata and a filtered variant") {
+    withTempPath { path =>
+      spark.range(10)
+        .selectExpr("parse_json(cast(id as string)) as v")
+        .write.parquet(path.getCanonicalPath)
+
+      val alwaysTrue = udf(() => true).asNondeterministic()
+      val query = spark.read.parquet(path.getCanonicalPath)
+        .where("v::int = 3")
+        .select(col("_metadata.file_path"))
+        .filter(alwaysTrue())
+        .distinct()
+
+      assert(query.collect().nonEmpty)
+    }
+  }
 }
 
 @ExtendedSQLTest