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.