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doc-exports/docs/mrs/component-operation-guide/mrs_01_2059.html
Yang, Tong 6182f91ba8 MRS component operation guide_normal 2.0.38.SP20 version 
Reviewed-by: Hasko, Vladimir <vladimir.hasko@t-systems.com>
Co-authored-by: Yang, Tong <yangtong2@huawei.com>
Co-committed-by: Yang, Tong <yangtong2@huawei.com>
2022-12-09 14:55:21 +00:00

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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.