这是我的代码：
df.write
.mode(SaveMode.Overwrite)
.parquet("d:/filename/sample.parquet")
创建0KB镶木地板文件。
请帮忙。可能是什么错误？ 我在IntelliJ IDEA上编写了这段代码，并面临编写数据框拼花的问题。
我需要我的数据帧是镶木地板格式，但它给我0Kb镶木地板文件。它空了
这是我的错误：
ERROR Utils: Aborting task
ExitCodeException exitCode=-1073741515:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:575)
at org.apache.hadoop.util.Shell.run(Shell.java:478)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:766)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:859)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:842)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:661)
at org.apache.hadoop.fs.ChecksumFileSystem$1.apply(ChecksumFileSystem.java:501)
at org.apache.hadoop.fs.ChecksumFileSystem$FsOperation.run(ChecksumFileSystem.java:482)
at org.apache.hadoop.fs.ChecksumFileSystem.setPermission(ChecksumFileSystem.java:498)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:467)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:433)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStream(CodecStreams.scala:81)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStreamWriter(CodecStreams.scala:92)
at org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.<init>(CSVFileFormat.scala:135)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:77)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.newOutputWriter(FileFormatWriter.scala:305)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:314)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:258)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:256)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1375)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:191)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:190)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)