我听说Java中有一个小故障，当您尝试在Windows 11中运行Spark功能时会导致错误。这就是我想运行的：
home_sales_df.write.partitionBy('date_built').parquet('p_home_sales',mode='overwrite')
这就是我得到的错误。给菜鸟的建议？谢谢你，谢谢
"name": "Py4JJavaError", "message": "An error occurred while calling o105.parquet.\n: java.lang.UnsatisfiedLinkError: 'boolean org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(java.lang.String, int)'\r\n\tat org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)\r\n\tat org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:793)\r\n\tat org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:1249)\r\n\tat org.apache.hadoop.fs.FileUtil.list(FileUtil.java:1454)\r\n\tat org.apache.hadoop.fs.RawLocalFileSystem.listStatus(RawLocalFileSystem.java:601)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)\r\n\tat org.apache.hadoop.fs.ChecksumFileSystem.listStatus(ChecksumFileSystem.java:761)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.getAllCommittedTaskPaths(FileOutputCommitter.java:334)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:404)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJob(FileOutputCommitter.java:377)\r\n\tat org.apache.parquet.hadoop.ParquetOutputCommitter.commitJob(ParquetOutputCommitter.java:48)\r\n\tat org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.commitJob(HadoopMapReduceCommitProtocol.scala:192)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$writeAndCommit$3(FileFormatWriter.scala:275)\r\n\tat scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)\r\n\tat org.apache.spark.util.Utils$.timeTakenMs(Utils.scala:640)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:275)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:304)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:190)\r\n\tat org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:190)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)\r\n\tat org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)\r\n\tat org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)\r\n\tat org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)\r\n\tat org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)\r\n\tat org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)\r\n\tat org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:133)\r\n\tat org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:856)\r\n\tat org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:387)\r\n\tat org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:360)\r\n\tat org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)\r\n\tat org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:789)\r\n\tat java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:75)\r\n\tat java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:52)\r\n\tat java.base/java.lang.reflect.Method.invoke(Method.java:578)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)\r\n\tat py4j.ClientServerConnection.run(ClientServerConnection.java:106)\r\n\tat java.base/java.lang.Thread.run(Thread.java:1623)\r\n", "stack": "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mPy4JJavaError\u001b[0m Traceback (most recent call last)\n\u001b[1;32mc:\\Users\\Adam\\spark-challenge\\Home_Sales.ipynb Cell 12\u001b[0m line \u001b[0;36m2\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/Adam/spark-challenge/Home_Sales.ipynb#X14sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39m# 10. Partition by the \"date_built\" field on the formatted parquet home sales data \u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/Adam/spark-challenge/Home_Sales.ipynb#X14sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m home_sales_df\u001b[39m.\u001b[39;49mwrite\u001b[39m.\u001b[39;49mpartitionBy(\u001b[39m'\u001b[39;49m\u001b[39mdate_built\u001b[39;49m\u001b[39m'\u001b[39;49m)\u001b[39m.\u001b[39;49mparquet(\u001b[39m'\u001b[39;49m\u001b[39mp_home_sales\u001b[39;49m\u001b[39m'\u001b[39;49m,mode\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39moverwrite\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\nFile \u001b[1;32m~\\spark-3.4.1-bin-hadoop3\\python\\pyspark\\sql\\readwriter.py:1656\u001b[0m, in \u001b[0;36mDataFrameWriter.parquet\u001b[1;34m(self, path, mode, partitionBy, compression)\u001b[0m\n\u001b[0;32m 1654\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpartitionBy(partitionBy)\n\u001b[0;32m 1655\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_set_opts(compression\u001b[39m=\u001b[39mcompression)\n\u001b[1;32m-> 1656\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_jwrite\u001b[39m.\u001b[39;49mparquet(path)\n\nFile \u001b[1;32m~\\spark-3.4.1-bin-hadoop3\\python\\lib\\py4j-0.10.9.7-src.zip\\py4j\\java_gateway.py:1322\u001b[0m, in \u001b[0;36mJavaMember.__call__\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m 1316\u001b[0m command \u001b[39m=\u001b[39m proto\u001b[39m.\u001b[39mCALL_COMMAND_NAME \u001b[39m+\u001b[39m\\\n\u001b[0;32m 1317\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcommand_header \u001b[39m+\u001b[39m\\\n\u001b[0;32m 1318\u001b[0m args_command \u001b[39m+\u001b[39m\\\n\u001b[0;32m 1319\u001b[0m proto\u001b[39m.\u001b[39mEND_COMMAND_PART\n\u001b[0;32m 1321\u001b[0m answer \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgateway_client\u001b[39m.\u001b[39msend_command(command)\n\u001b[1;32m-> 1322\u001b[0m return_value \u001b[39m=\u001b[39m get_return_value(\n\u001b[0;32m 1323\u001b[0m answer, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mgateway_client, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtarget_id, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mname)\n\u001b[0;32m 1325\u001b[0m \u001b[39mfor\u001b[39;00m temp_arg \u001b[39min\u001b[39;00m temp_args:\n\u001b[0;32m 1326\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mhasattr\u001b[39m(temp_arg, \u001b[39m\"\u001b[39m\u001b[39m_detach\u001b[39m\u001b[39m\"\u001b[39m):\n\nFile \u001b[1;32m~\\spark-3.4.1-bin-hadoop3\\python\\pyspark\\errors\\exceptions\\captured.py:169\u001b[0m, in \u001b[0;36mcapture_sql_exception.<locals>.deco\u001b[1;34m(*a, **kw)\u001b[0m\n\u001b[0;32m 167\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdeco\u001b[39m(\u001b[39m*\u001b[39ma: Any, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkw: Any) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Any:\n\u001b[0;32m 168\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 169\u001b[0m \u001b[39mreturn\u001b[39;00m f(\u001b[39m*\u001b[39ma, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkw)\n\u001b[0;32m 170\u001b[0m \u001b[39mexcept\u001b[39;00m Py4JJavaError \u001b[39mas\u001b[39;00m e:\n\u001b[0;32m 171\u001b[0m converted \u001b[39m=\u001b[39m convert_exception(e\u001b[39m.\u001b[39mjava_exception)\n\nFile \u001b[1;32m~\\spark-3.4.1-bin-hadoop3\\python\\lib\\py4j-0.10.9.7-src.zip\\py4j\\protocol.py:326\u001b[0m, in \u001b[0;36mget_return_value\u001b[1;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[0;32m 324\u001b[0m value \u001b[39m=\u001b[39m OUTPUT_CONVERTER[\u001b[39mtype\u001b[39m](answer[\u001b[39m2\u001b[39m:], gateway_client)\n\u001b[0;32m 325\u001b[0m \u001b[39mif\u001b[39;00m answer[\u001b[39m1\u001b[39m] \u001b[39m==\u001b[39m REFERENCE_TYPE:\n\u001b[1;32m--> 326\u001b[0m \u001b[39mraise\u001b[39;00m Py4JJavaError(\n\u001b[0;32m 327\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mAn error occurred while calling \u001b[39m\u001b[39m{0}\u001b[39;00m\u001b[39m{1}\u001b[39;00m\u001b[39m{2}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\n\u001b[0;32m 328\u001b[0m \u001b[39mformat\u001b[39m(target_id, \u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, name), value)\n\u001b[0;32m 329\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m 330\u001b[0m \u001b[39mraise\u001b[39;00m Py4JError(\n\u001b[0;32m 331\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mAn error occurred while calling \u001b[39m\u001b[39m{0}\u001b[39;00m\u001b[39m{1}\u001b[39;00m\u001b[39m{2}\u001b[39;00m\u001b[39m. Trace:\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m{3}\u001b[39;00m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\n\u001b[0;32m 332\u001b[0m \u001b[39mformat\u001b[39m(target_id, \u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, name, value))\n\n\u001b[1;31mPy4JJavaError\u001b[0m: An error occurred while calling o105.parquet.\n: java.lang.UnsatisfiedLinkError: 'boolean org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(java.lang.String, int)'\r\n\tat org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)\r\n\tat org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:793)\r\n\tat org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:1249)\r\n\tat org.apache.hadoop.fs.FileUtil.list(FileUtil.java:1454)\r\n\tat org.apache.hadoop.fs.RawLocalFileSystem.listStatus(RawLocalFileSystem.java:601)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)\r\n\tat org.apache.hadoop.fs.ChecksumFileSystem.listStatus(ChecksumFileSystem.java:761)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)\r\n\tat org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.getAllCommittedTaskPaths(FileOutputCommitter.java:334)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:404)\r\n\tat org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJob(FileOutputCommitter.java:377)\r\n\tat org.apache.parquet.hadoop.ParquetOutputCommitter.commitJob(ParquetOutputCommitter.java:48)\r\n\tat org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.commitJob(HadoopMapReduceCommitProtocol.scala:192)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$writeAndCommit$3(FileFormatWriter.scala:275)\r\n\tat scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)\r\n\tat org.apache.spark.util.Utils$.timeTakenMs(Utils.scala:640)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:275)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:304)\r\n\tat org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:190)\r\n\tat org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:190)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)\r\n\tat org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)\r\n\tat org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)\r\n\tat org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)\r\n\tat org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)\r\n\tat org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)\r\n\tat org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)\r\n\tat org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)\r\n\tat org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)\r\n\tat org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)\r\n\tat org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:133)\r\n\tat org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:856)\r\n\tat org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:387)\r\n\tat org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:360)\r\n\tat org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)\r\n\tat org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:789)\r\n\tat java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:75)\r\n\tat java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:52)\r\n\tat java.base/java.lang.reflect.Method.invoke(Method.java:578)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)\r\n\tat py4j.ClientServerConnection.run(ClientServerConnection.java:106)\r\n\tat java.base/java.lang.Thread.run(Thread.java:1623)\r\n"
我试过调整环境变量。还有：
import os os.environ 'PYSPARK_PYTHON'] = r'C：\Users\Adam\anaconda3\python.exe '