You can create a UDF which will invoke your java lib
def calculateExpense: UserDefinedFunction = udf((pexpense: String,
cexpense: String) => new MyJava().calculateExpense(pexpense.toDouble,
cexpense.toDouble))
On Tue, Aug 29, 2017 at 6:53 AM, purna pradeep <purna2prad...@gmail.com>
wrote:
> I have data in a DataFrame with below columns
>
> 1)Fileformat is csv
> 2)All below column datatypes are String
>
> employeeid,pexpense,cexpense
>
> Now I need to create a new DataFrame which has new column called
> `expense`, which is calculated based on columns `pexpense`, `cexpense`.
>
> The tricky part is the calculation algorithm is not an **UDF** function
> which I created, but it's an external function that needs to be imported
> from a Java library which takes primitive types as arguments - in this case
> `pexpense`, `cexpense` - to calculate the value required for new column.
>
> The external function signature
>
> public class MyJava
>
> {
>
> public Double calculateExpense(Double pexpense, Double cexpense) {
> // calculation
> }
>
> }
>
> So how can I invoke that external function to create a new calculated
> column. Can I register that external function as UDF in my Spark
> application?
>
> Stackoverflow reference
>
> https://stackoverflow.com/questions/45928007/use-withcolumn-with-external-
> function
>
>
>
>
>
>
