Spark-csv into labeled points with null values

[Saif.A.Ellafi]

Hello all,

I am learning scala spark and going through some applications with data I have. 
Please allow me to put a couple questions:

spark-csv: The data I have, ain't malformed, but there are empty values in some 
rows, properly comma-sepparated and not catched by "DROPMALFORMED" mode
These values are taken into account as null values. My final mission is to 
create a LabeledPoint vector for MLLIB, so my steps are:
a.      load csv
b.      cast column types to have a proper DataFrame schema
c.      apply map() to create a LabeledPoint with denseVector. Using map( Row 
=> Row.getDouble(col_index) )

To this point:
res173: org.apache.spark.mllib.regression.LabeledPoint = 
(-1.530132691E9,[162.89431,13.55811,18.3346818,-1.6653182])

As running the following code:

      val model = new LogisticRegressionWithLBFGS().
          setNumClasses(2).
          setValidateData(true).
          run(data_map)

      java.lang.RuntimeException: Failed to check null bit for primitive double 
value.

Debugging this, I am pretty sure this is because rows that look like 
-2.593849123898,392.293891,,,,

Any suggestions to get round this?

Saif