Why Does Spark2x Fail to Export a Table with the Same Field Name?

Question

The following code fails to be executed on spark-shell of Spark2x:

val acctId = List(("49562", "Amal", "Derry"), ("00000", "Fred", "Xanadu"))
val rddLeft = sc.makeRDD(acctId)
val dfLeft = rddLeft.toDF("Id", "Name", "City")
//dfLeft.show
val acctCustId = List(("Amal", "49562", "CO"), ("Dave", "99999", "ZZ"))
val rddRight = sc.makeRDD(acctCustId)
val dfRight = rddRight.toDF("Name", "CustId", "State")
//dfRight.show
val dfJoin = dfLeft.join(dfRight, dfLeft("Id") === dfRight("CustId"), "outer")
dfJoin.show
dfJoin.repartition(1).write.format("com.databricks.spark.csv").option("delimiter", "\t").option("header", "true").option("treatEmptyValuesAsNulls", "true").option("nullValue", "").save("/tmp/outputDir") 

Answer

In Spark2x, the duplicate field name of the join statement is checked. You need to modify the code to ensure that no duplicate field exists in the saved data.