diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala
index 1b59b19d94..ad55367258 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala
@@ -124,6 +124,24 @@ private[sql] abstract class BaseWriterContainer(
     }
   }
 
+  protected def newOutputWriter(path: String): OutputWriter = {
+    try {
+      outputWriterFactory.newInstance(path, dataSchema, taskAttemptContext)
+    } catch {
+      case e: org.apache.hadoop.fs.FileAlreadyExistsException =>
+        if (outputCommitter.isInstanceOf[parquet.DirectParquetOutputCommitter]) {
+          // Spark-11382: DirectParquetOutputCommitter is not idempotent, meaning on retry
+          // attempts, the task will fail because the output file is created from a prior attempt.
+          // This often means the most visible error to the user is misleading. Augment the error
+          // to tell the user to look for the actual error.
+          throw new SparkException("The output file already exists but this could be due to a " +
+            "failure from an earlier attempt. Look through the earlier logs or stage page for " +
+            "the first error.\n  File exists error: " + e)
+        }
+        throw e
+    }
+  }
+
   private def newOutputCommitter(context: TaskAttemptContext): OutputCommitter = {
     val defaultOutputCommitter = outputFormatClass.newInstance().getOutputCommitter(context)
 
@@ -234,7 +252,7 @@ private[sql] class DefaultWriterContainer(
     executorSideSetup(taskContext)
     val configuration = SparkHadoopUtil.get.getConfigurationFromJobContext(taskAttemptContext)
     configuration.set("spark.sql.sources.output.path", outputPath)
-    val writer = outputWriterFactory.newInstance(getWorkPath, dataSchema, taskAttemptContext)
+    val writer = newOutputWriter(getWorkPath)
     writer.initConverter(dataSchema)
 
     var writerClosed = false
@@ -403,7 +421,7 @@ private[sql] class DynamicPartitionWriterContainer(
       val configuration = SparkHadoopUtil.get.getConfigurationFromJobContext(taskAttemptContext)
       configuration.set(
         "spark.sql.sources.output.path", new Path(outputPath, partitionPath).toString)
-      val newWriter = outputWriterFactory.newInstance(path.toString, dataSchema, taskAttemptContext)
+      val newWriter = super.newOutputWriter(path.toString)
       newWriter.initConverter(dataSchema)
       newWriter
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/DirectParquetOutputCommitter.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/DirectParquetOutputCommitter.scala
index 300e8677b3..1a4e99ff10 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/DirectParquetOutputCommitter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/DirectParquetOutputCommitter.scala
@@ -41,7 +41,8 @@ import org.apache.parquet.hadoop.{ParquetFileReader, ParquetFileWriter, ParquetO
  *   no safe way undo a failed appending job (that's why both `abortTask()` and `abortJob()` are
  *   left empty).
  */
-private[parquet] class DirectParquetOutputCommitter(outputPath: Path, context: TaskAttemptContext)
+private[datasources] class DirectParquetOutputCommitter(
+    outputPath: Path, context: TaskAttemptContext)
   extends ParquetOutputCommitter(outputPath, context) {
   val LOG = Log.getLog(classOf[ParquetOutputCommitter])