add app

helloworld/src/main/scala/com/salesforce/hw/OpTitanicSimple.scala

@@ -58,7 +58,7 @@ import org.apache.spark.sql.SparkSession
  */
 case class IDTextClassification
 (
- id: Int,
+ id: Option[Int],
  eng_sentences: Option[String],
  eng_paragraphs: Option[String],
  news_data: Option[String],
@@ -79,13 +79,19 @@ case class IDTextClassification
  faker_ipv6: Option[String]
 )
 
-object IdDetectTest {
+object OpTitanicSimple {
 
  /**
  * Run this from the command line with
  * ./gradlew sparkSubmit -Dmain=com.salesforce.op.filters.IdDetectTest -Dargs=/full/path/to/csv/file
  */
- def main(): Unit = {
+ def main(args: Array[String]): Unit = {
+ if (args.isEmpty) {
+ println("You need to pass in the CSV file path as an argument")
+ sys.exit(1)
+ }
+ val csvFilePath = args(0)
+ println(s"Using user-supplied CSV file path: $csvFilePath")
 
  // Set up a SparkSession as normal
  implicit val spark = SparkSession.builder.config(new SparkConf()).getOrCreate()
@@ -115,6 +121,7 @@ object IdDetectTest {
  .extract(_.variable_nb_sentences.toText).asPredictor
  val faker_ipv4 = FeatureBuilder.Text[IDTextClassification].extract(_.faker_ipv4.toText).asPredictor
  val faker_ipv6 = FeatureBuilder.Text[IDTextClassification].extract(_.faker_ipv6.toText).asPredictor
+ val id = FeatureBuilder.Integral[IDTextClassification].extract(_.id.toIntegral).asResponse
 
  val IDFeatures = Seq(
  eng_sentences, eng_paragraphs, news_data, tox_data,
@@ -126,11 +133,11 @@ object IdDetectTest {
 
  def thresHoldRFF(mTK: Int): Seq[String] = {
  val dataReader = DataReaders.Simple.csvCase[IDTextClassification](
- path = Option("~/Downloads/3kData.csv"),
+ path = Option(csvFilePath),
  key = _.id.toString)
  val workflow = new OpWorkflow()
  .withRawFeatureFilter(Some(dataReader), None, minTopk = mTK)
- .setResultFeatures(IDFeatures)
+ .setResultFeatures(id, IDFeatures)
  .setReader(dataReader)
 
  // Fit the workflow to the data