我试图从 spark 中的镶木地板文件中读取，与另一个 rdd 进行联合，然后将结果写入我读取的同一个文件中（基本上是覆盖），这会引发以下错误：
couldnt write parquet to file: An error occurred while calling o102.parquet.
: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
TungstenExchange hashpartitioning(billID#42,200), None
+- Union
:- Scan ParquetRelation[units#35,price#36,priceSold#37,orderingTime#38,itemID#39,storeID#40,customerID#41,billID#42,sourceRef#43] InputPaths: hdfs://master-wat:8020/user/root/dataFile/parquet/general/NPM61LKK1C/Billbody
+- Project [units#22,price#23,priceSold#24,orderingTime#25,itemID#26,storeID#27,customerID#28,billID#29,2 AS sourceRef#30]
+- Scan ExistingRDD[units#22,price#23,priceSold#24,orderingTime#25,itemID#26,storeID#27,customerID#28,billID#29]
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49)
at org.apache.spark.sql.execution.Exchange.doExecute(Exchange.scala:247)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at org.apache.spark.sql.execution.Sort.doExecute(Sort.scala:64)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at org.apache.spark.sql.execution.Window.doExecute(Window.scala:245)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at org.apache.spark.sql.execution.Filter.doExecute(basicOperators.scala:70)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130) …