Py4JJavaError：調用 o57.sql 時出錯：org.apache.spark.SparkException：作業中止

Question

我正在嘗試根據以下代碼將 spark dataframe 寫入 hive 表。 但我有一個錯誤。 我檢查了相同的問題帖子（ Py4JJavaError: An error occurred while calling o57.showString. : org.apache.spark.SparkException: ）但我找不到任何解決方案。 您可以找到完整的錯誤。

代碼：

spark_df = spark.createDataFrame(df2)
spark_df.createOrReplaceTempView("steer");
spark.sql("drop table if exists sandbox_nonmotor.steer")
spark.sql("create table sandbox_nonmotor.steer as select * from steer")

錯誤：

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-16-84bf8c9c8f45> in <module>
  2 spark_df.createOrReplaceTempView("steer");
  3 spark.sql("drop table if exists sandbox_nonmotor.steer")
----> 4 spark.sql("create table sandbox_nonmotor.steer as select * from steer")

/opt/cloudera/parcels/SPARK2/lib/spark2/python/pyspark/sql/session.py in sql(self, sqlQuery)
765         [Row(f1=1, f2=u'row1'), Row(f1=2, f2=u'row2'), Row(f1=3, f2=u'row3')]
766         """
--> 767         return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
768 
769     @since(2.0)

/opt/cloudera/parcels/SPARK2/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in             
__call__(self, *args)
1255         answer = self.gateway_client.send_command(command)
1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
1258 
1259         for temp_arg in temp_args:

/opt/cloudera/parcels/SPARK2/lib/spark2/python/pyspark/sql/utils.py in deco(*a, **kw)
 61     def deco(*a, **kw):
 62         try:
---> 63             return f(*a, **kw)
 64         except py4j.protocol.Py4JJavaError as e:
 65             s = e.java_exception.toString()

/opt/cloudera/parcels/SPARK2/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in     
get_return_value(answer, gateway_client, target_id, name)
326                 raise Py4JJavaError(
327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
329             else:
330                 raise Py4JError(

Py4JJavaError: An error occurred while calling o57.sql.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:198)
at org.apache.spark.sql.hive.execution.SaveAsHiveFile$class.saveAsHiveFile(SaveAsHiveFile.scala:86)
at     
org.apache.spark.sql.hive.execution.InsertIntoHiveTable.saveAsHiveFile(InsertIntoHiveTable.scala:66)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.processInsert     
(InsertIntoHiveTable.scala:195)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.run(InsertIntoHiveTable.scala:99)
at org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand.run 
(CreateHiveTableAsSelectCommand.scala:88)
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.executeCollect(commands.scala:115)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3364)
at org.apache.spark.sql.execution.SQLExecution$$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$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3363)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:194)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:79)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:642)
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:497)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
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.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 2:0 was    
155731289 bytes, which exceeds max allowed: spark.rpc.message.maxSize (134217728 bytes). Consider 
increasing spark.rpc.message.maxSize or using broadcast variables for large values.
at org.apache.spark.scheduler.DAGScheduler. 
org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply 
(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply 
(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:167)
... 29 more

Answer 1

您鏈接的帖子有不同的問題，在您的情況下，錯誤消息是：

Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 2:0 was    
155731289 bytes, which exceeds max allowed: spark.rpc.message.maxSize (134217728 bytes). Consider 
increasing spark.rpc.message.maxSize or using broadcast variables for large values.

您應該嘗試設置更大的spark.rpc.message.maxSize ，嘗試類似：

config = SparkConf().set('spark.rpc.message.maxSize', '256')
sc = SparkContext.getOrCreate(conf=config)