diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ListingFileCatalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ListingFileCatalog.scala
index 7d2854aaad..d96cf1bf07 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ListingFileCatalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ListingFileCatalog.scala
@@ -20,7 +20,7 @@ package org.apache.spark.sql.execution.datasources
 import scala.collection.mutable
 import scala.util.Try
 
-import org.apache.hadoop.fs.{FileStatus, LocatedFileStatus, Path}
+import org.apache.hadoop.fs.{FileStatus, Path}
 import org.apache.hadoop.mapred.{FileInputFormat, JobConf}
 
 import org.apache.spark.sql.SparkSession
@@ -83,8 +83,9 @@ class ListingFileCatalog(
       val statuses: Seq[FileStatus] = paths.flatMap { path =>
         val fs = path.getFileSystem(hadoopConf)
         logInfo(s"Listing $path on driver")
-        Try(HadoopFsRelation.listLeafFiles(fs, fs.getFileStatus(path), pathFilter)).
-          getOrElse(Array.empty)
+        Try {
+          HadoopFsRelation.listLeafFiles(fs, fs.getFileStatus(path), pathFilter)
+        }.getOrElse(Array.empty[FileStatus])
       }
       mutable.LinkedHashSet(statuses: _*)
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileCatalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileCatalog.scala
index 406d2e8e81..811e96c99a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileCatalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileCatalog.scala
@@ -50,14 +50,14 @@ abstract class PartitioningAwareFileCatalog(
 
   override def listFiles(filters: Seq[Expression]): Seq[Partition] = {
     val selectedPartitions = if (partitionSpec().partitionColumns.isEmpty) {
-      Partition(InternalRow.empty, allFiles().filterNot(_.getPath.getName startsWith "_")) :: Nil
+      Partition(InternalRow.empty, allFiles().filter(f => isDataPath(f.getPath))) :: Nil
     } else {
       prunePartitions(filters, partitionSpec()).map {
         case PartitionDirectory(values, path) =>
           val files: Seq[FileStatus] = leafDirToChildrenFiles.get(path) match {
             case Some(existingDir) =>
               // Directory has children files in it, return them
-              existingDir.filterNot(_.getPath.getName.startsWith("_"))
+              existingDir.filter(f => isDataPath(f.getPath))
 
             case None =>
               // Directory does not exist, or has no children files
@@ -96,7 +96,11 @@ abstract class PartitioningAwareFileCatalog(
 
   protected def inferPartitioning(): PartitionSpec = {
     // We use leaf dirs containing data files to discover the schema.
-    val leafDirs = leafDirToChildrenFiles.keys.toSeq
+    val leafDirs = leafDirToChildrenFiles.filter { case (_, files) =>
+      // SPARK-15895: Metadata files (e.g. Parquet summary files) and temporary files should not be
+      // counted as data files, so that they shouldn't participate partition discovery.
+      files.exists(f => isDataPath(f.getPath))
+    }.keys.toSeq
     partitionSchema match {
       case Some(userProvidedSchema) if userProvidedSchema.nonEmpty =>
         val spec = PartitioningUtils.parsePartitions(
@@ -197,4 +201,9 @@ abstract class PartitioningAwareFileCatalog(
           if (leafFiles.contains(qualifiedPath)) qualifiedPath.getParent else qualifiedPath }.toSet
     }
   }
+
+  private def isDataPath(path: Path): Boolean = {
+    val name = path.getName
+    !(name.startsWith("_") || name.startsWith("."))
+  }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetPartitionDiscoverySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetPartitionDiscoverySuite.scala
index e19345529e..133ffedf12 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetPartitionDiscoverySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetPartitionDiscoverySuite.scala
@@ -25,11 +25,13 @@ import scala.collection.mutable.ArrayBuffer
 
 import com.google.common.io.Files
 import org.apache.hadoop.fs.Path
+import org.apache.parquet.hadoop.ParquetOutputFormat
 
 import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions.Literal
 import org.apache.spark.sql.execution.datasources.{HadoopFsRelation, LogicalRelation, PartitionDirectory => Partition, PartitioningUtils, PartitionSpec}
+import org.apache.spark.sql.functions._
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSQLContext
 import org.apache.spark.sql.types._
@@ -890,4 +892,46 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest with Sha
       }
     }
   }
+
+  test("SPARK-15895 summary files in non-leaf partition directories") {
+    withTempPath { dir =>
+      val path = dir.getCanonicalPath
+
+      withSQLConf(ParquetOutputFormat.ENABLE_JOB_SUMMARY -> "true") {
+        spark.range(3).write.parquet(s"$path/p0=0/p1=0")
+      }
+
+      val p0 = new File(path, "p0=0")
+      val p1 = new File(p0, "p1=0")
+
+      // Builds the following directory layout by:
+      //
+      //  1. copying Parquet summary files we just wrote into `p0=0`, and
+      //  2. touching a dot-file `.dummy` under `p0=0`.
+      //
+      // <base>
+      // +- p0=0
+      //    |- _metadata
+      //    |- _common_metadata
+      //    |- .dummy
+      //    +- p1=0
+      //       |- _metadata
+      //       |- _common_metadata
+      //       |- part-00000.parquet
+      //       |- part-00001.parquet
+      //       +- ...
+      //
+      // The summary files and the dot-file under `p0=0` should not fail partition discovery.
+
+      Files.copy(new File(p1, "_metadata"), new File(p0, "_metadata"))
+      Files.copy(new File(p1, "_common_metadata"), new File(p0, "_common_metadata"))
+      Files.touch(new File(p0, ".dummy"))
+
+      checkAnswer(spark.read.parquet(s"$path"), Seq(
+        Row(0, 0, 0),
+        Row(1, 0, 0),
+        Row(2, 0, 0)
+      ))
+    }
+  }
 }