When I write data throw java.lang.Exception: Batch 'xxxxxxxxxxx' failed with error 'InvalidBatch : Records not found'

[newforesee]

I use the following method to write data to Salesforce. Every time the write is completed, an exception will be thrown but the data seems to be written.

def save2Salesforce(df: DataFrame): Unit = {
    df.write
      .format("com.springml.spark.salesforce")
      .option("username", "myusername")
      .option("password", "mypassword")
      .option("login", "https://test.salesforce.com/")
      .option("upsert", true)
      .option("sfObject", "OrderTemp__c").
      save()
  }

The Exception :

Exception in thread "main" java.lang.Exception: Batch '7512i000004KPxyAAG' failed with error 'InvalidBatch : Records not found'
	at com.springml.salesforce.wave.impl.BulkAPIImpl.isCompleted(BulkAPIImpl.java:93)
	at com.springml.spark.salesforce.SFObjectWriter.writeData(SFObjectWriter.scala:44)
	at com.springml.spark.salesforce.DefaultSource.updateSalesforceObject(DefaultSource.scala:154)
	at com.springml.spark.salesforce.DefaultSource.createRelation(DefaultSource.scala:130)
	at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
	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$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
	at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
	at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
	at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
	at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
	at org.apache.spark.sql.DataFrameWriter$$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)

Will this Exception affect my data? Can it be ignored? If I just ignore whether there is any risk?