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