将dataframe写入oracle时列标识符无效

ORA-00904：“XXXX”：无效标识符

不要使用

XXXX

列，因为它不存在于代码所涉及的表中

很难提出其他建议，因为您发布了很多几乎毫无用处的信息表说明以及您编写的代码将更有帮助

同时，自己检查一下

Caused by: java.sql.SQLException: ORA-00904: "XXXX": invalid identifier

    at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:445)
    at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:396)
    at oracle.jdbc.driver.T4C8Oall.processError(T4C8Oall.java:879)
    at oracle.jdbc.driver.T4CTTIfun.receive(T4CTTIfun.java:450)
    at oracle.jdbc.driver.T4CTTIfun.doRPC(T4CTTIfun.java:192)
    at oracle.jdbc.driver.T4C8Oall.doOALL(T4C8Oall.java:531)
    at oracle.jdbc.driver.T4CPreparedStatement.doOall8(T4CPreparedStatement.java:207)
    at oracle.jdbc.driver.T4CPreparedStatement.executeForRows(T4CPreparedStatement.java:1037)
    at oracle.jdbc.driver.OraclePreparedStatement.executeForRowsWithTimeout(OraclePreparedStatement.java:10084)
    at oracle.jdbc.driver.OraclePreparedStatement.executeBatch(OraclePreparedStatement.java:10190)
    ... 14 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1965)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:926)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:924)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
    at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:924)
    at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply$mcV$sp(Dataset.scala:2320)
    at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2320)
    at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2320)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
    at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2788)
    at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2319)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:670)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:77)
    at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:518)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:215)