import pyspark.sql as spark_sql
from pyspark.sql import SparkSession
spark = SparkSession.builder \
.appName("Simple PySpark DataFrame Example") \
.master("local") \
.getOrCreate()
# 创建一个简单的 DataFrame
data = [("James", 30), ("Anna", 23), ("Robert", 45)]
columns = ["Name", "Age"]
df = spark.createDataFrame(data, columns)
以上代码均无报错，但是运行df.show时报错
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
Cell In[15], line 1
----> 1 df.show()
File c:\ProgramData\anaconda3\envs\lwy\lib\site-packages\pyspark\sql\dataframe.py:959, in DataFrame.show(self, n, truncate, vertical)
953 raise PySparkTypeError(
954 error_class="NOT_BOOL",
955 message_parameters={"arg_name": "vertical", "arg_type": type(vertical).__name__},
956 )
958 if isinstance(truncate, bool) and truncate:
--> 959 print(self._jdf.showString(n, 20, vertical))
960 else:
961 try:
File c:\ProgramData\anaconda3\envs\lwy\lib\site-packages\py4j\java_gateway.py:1362, in JavaMember.__call__(self, *args)
1356 command = proto.CALL_COMMAND_NAME +\
1357 self.command_header +\
1358 args_command +\
1359 proto.END_COMMAND_PART
1361 answer = self.gateway_client.send_command(command)
-> 1362 return_value = get_return_value(
1363 answer, self.gateway_client, self.target_id, self.name)
1365 for temp_arg in temp_args:
1366 if hasattr(temp_arg, "_detach"):
File c:\ProgramData\anaconda3\envs\lwy\lib\site-packages\pyspark\errors\exceptions\captured.py:179, in capture_sql_exception.<locals>.deco(*a, **kw)
177 def deco(*a: Any, **kw: Any) -> Any:
178 try:
--> 179 return f(*a, **kw)
180 except Py4JJavaError as e:
181 converted = convert_exception(e.java_exception)
File c:\ProgramData\anaconda3\envs\lwy\lib\site-packages\py4j\protocol.py:327, in get_return_value(answer, gateway_client, target_id, name)
325 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
326 if answer[1] == REFERENCE_TYPE:
--> 327 raise Py4JJavaError(
328 "An error occurred while calling {0}{1}{2}.\n".
329 format(target_id, ".", name), value)
330 else:
331 raise Py4JError(
332 "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
333 format(target_id, ".", name, value))
Py4JJavaError: An error occurred while calling o88.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2) (BF-202401010010 executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:203)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:109)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:124)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:174)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:67)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
at org.apache.spark.scheduler.Task.run(Task.scala:141)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:190)
... 32 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2844)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2780)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2779)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2779)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1242)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1242)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1242)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3048)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2982)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2971)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:984)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2398)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2419)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2438)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:530)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:483)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:61)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:4344)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:3326)
at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:4334)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:546)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:4332)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:201)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:108)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:66)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:4332)
at org.apache.spark.sql.Dataset.head(Dataset.scala:3326)
at org.apache.spark.sql.Dataset.take(Dataset.scala:3549)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:280)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:315)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:203)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:109)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:124)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:174)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:67)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
at org.apache.spark.scheduler.Task.run(Task.scala:141)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:190)
... 32 more
