dynamic Dimensions

data/import_eventserver.py

@@ -18,9 +18,7 @@ def import_events(client, file):
       entity_type="user",
       entity_id=str(count), # use the count num as user ID
       properties= {
-        "attr0" : int(attr[0]),
-        "attr1" : int(attr[1]),
-        "attr2" : int(attr[2]),
+        "attrs" : [int(attr[0]),int(attr[1]),int(attr[2]) ],
         "plan" : int(plan)
       }
     )

src/main/scala/DataSource.scala

@@ -30,17 +30,15 @@ class DataSource(val dsp: DataSourceParams)
       appName = dsp.appName,
       entityType = "user",
       // only keep entities with these required properties defined
-      required = Some(List("plan", "attr0", "attr1", "attr2")))(sc)
+      required = Some(List("plan", "attrs")))(sc)
       // aggregateProperties() returns RDD pair of
       // entity ID and its aggregated properties
       .map { case (entityId, properties) =>
         try {
           LabeledPoint(properties.get[Double]("plan"),
-            Vectors.dense(Array(
-              properties.get[Double]("attr0"),
-              properties.get[Double]("attr1"),
-              properties.get[Double]("attr2")
-            ))
+            Vectors.dense(
+              properties.get[Array[Double]]("attrs")
+            )
           )
         } catch {
           case e: Exception => {
@@ -68,17 +66,15 @@ class DataSource(val dsp: DataSourceParams)
       appName = dsp.appName,
       entityType = "user",
       // only keep entities with these required properties defined
-      required = Some(List("plan", "attr0", "attr1", "attr2")))(sc)
+      required = Some(List("plan", "attrs")))(sc)
       // aggregateProperties() returns RDD pair of
       // entity ID and its aggregated properties
       .map { case (entityId, properties) =>
         try {
           LabeledPoint(properties.get[Double]("plan"),
-            Vectors.dense(Array(
-              properties.get[Double]("attr0"),
-              properties.get[Double]("attr1"),
-              properties.get[Double]("attr2")
-            ))
+            Vectors.dense(
+              properties.get[Array[Double]]("attrs")
+            )
           )
         } catch {
           case e: Exception => {

src/main/scala/Engine.scala

@@ -3,11 +3,13 @@ package org.template.classification
 import io.prediction.controller.EngineFactory
 import io.prediction.controller.Engine
 
-class Query(
-  val attr0 : Double,
-  val attr1 : Double,
-  val attr2 : Double
-) extends Serializable
+class Query extends Serializable{
+  var attrs: Seq[Double] = null
+  def this(attrs: Double*) {
+    this()
+    this.attrs = attrs
+  }
+}
 
 class PredictedResult(
   val label: Double

src/main/scala/NaiveBayesAlgorithm.scala

@@ -32,7 +32,7 @@ class NaiveBayesAlgorithm(val ap: AlgorithmParams)
 
   def predict(model: NaiveBayesModel, query: Query): PredictedResult = {
     val label = model.predict(Vectors.dense(
-      Array(query.attr0, query.attr1, query.attr2)
+      Array(query.attrs: _*)
     ))
     new PredictedResult(label)
   }