I'm following some online tutorial written in Python and trying to convert
a Spark SQL table object to an RDD in Scala.
The Spark SQL just loads a simple table from a CSV file. The tutorial says
to convert the table to an RDD.
The Python is
products_rdd = sqlContext.table("products").map(lambda row:
(float(row[0]),float(row[1]),float(row[2]),float(row[3]),
float(row[4]),float(row[5]),float(row[6]),float(row[7]),float(row[8]),float(row[9]),float(row[10]),float(row[11])))
The Scala is *not*
val productsRdd = sqlContext.table("products").map( row => (
row(0).toFloat,row(1).toFloat,row(2).toFloat,row(3).toFloat,
row(4).toFloat,row(5).toFloat,row(6).toFloat,row(7).toFloat,row(8).toFloat,
row(9).toFloat,row(10).toFloat,row(11).toFloat
))
I know this, because Spark says that for each of the row(x).toFloat calls,
"error: value toFloat is not a member of Any"
Does anyone know the proper syntax for this?
Thank you
