I am writing a Spark Scala UDF and facing "java.lang.UnsupportedOperationException: Schema for type Any is not supported"
import org.apache.spark.sql.expressions.UserDefinedFunction
import org.apache.spark.sql.functions.udf
val aBP = udf((bG: String, pS: String, bP: String, iOne: String, iTwo: String) => {
if (bG != "I") {"NA"}
else if (pS == "D")
{if (iTwo != null) iOne else "NA"}
else if (pS == "U")
{if (bP != null) bP else "NA"}
})
This is throwing error "java.lang.UnsupportedOperationException: Schema for type Any is not supported"
As disussed in this link your udf should return:
So if you add another else to your code, the compilation will succeed.
val aBP = udf((bG: String, pS: String, bP: String, iOne: String, iTwo: String) => {
if (bG != "I") {"NA"}
else if (pS == "D") {
if (iTwo != null)
iOne
else "NA"
} else if (pS == "U") {
if (bP != null)
bP
else
"NA"
} else {
""
}
})
You could also redistribute your code using pattern matching:
val aBP = udf [String, String, String, String, String, String] {
case (bG: String, _, _, _, _) if bG != "I" => "NA"
case (_, pS: String, _, iOne: String, iTwo: String) if pS == "D" && iTwo.isEmpty => iOne
case (_, pS: String, _, _, _) if pS == "D" => "NA"
case (_, pS: String, bP: String, _, _) if pS == "U" && bP.isEmpty => bP
case (_, pS: String, _, _, _) if pS == "U" => "NA"
case _ => ""
}
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