我正在开发一个共享的ApacheZeppelin服务器。几乎每天，我都会尝试运行一个命令，并出现以下错误： Job 65 cancelled because SparkContext was shut down 我很想了解更多导致sparkcontext关闭的原因。我的理解是齐柏林飞艇是一个kube应用程序，它向机器发送命令进行处理。
当sparkcontext关闭时，这是否意味着我与spark cluster之间的桥梁关闭了？如果是这样的话，我怎样才能让通往星火团的桥塌下来呢？
在这个例子中，它发生在我试图上传数据到s3的时候。
这是密码

val myfiles = readParquet(
    startDate=ew LocalDate(2020, 4, 1),
    endDate=ew LocalDate(2020, 4, 7)
)

log_events.createOrReplaceTempView("log_events")

val mySQLDF = spark.sql(s"""
    select [6 columns]
    from myfiles 
    join [other table]
    on [join_condition]
"""
)

mySQLDF.write.option("maxRecordsPerFile", 1000000).parquet(path)
// mySQLDF has 3M rows and they're all strings or dates

这是stacktrace错误

org.apache.spark.SparkException: Job aborted.
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:198)
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:159)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
  at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
  at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
  at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
  at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
  at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
  at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
  at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:229)
  at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:566)
  ... 48 elided
Caused by: org.apache.spark.SparkException: Job 44 cancelled because SparkContext was shut down
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:972)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:970)
  at scala.collection.mutable.HashSet.foreach(HashSet.scala:78)
  at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:970)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:2286)
  at org.apache.spark.util.EventLoop.stop(EventLoop.scala:84)
  at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:2193)
  at org.apache.spark.SparkContext$$anonfun$stop$6.apply$mcV$sp(SparkContext.scala:1949)
  at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1340)
  at org.apache.spark.SparkContext.stop(SparkContext.scala:1948)
  at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend$MonitorThread.run(YarnClientSchedulerBackend.scala:121)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:777)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:167)
  ... 70 more