rov xgb model

recommend-model-produce/src/main/scala/com/tzld/piaoquan/recommend/model/train_recsys_61_xgb_rov_20241209.scala

@@ -68,7 +68,7 @@ object train_recsys_61_xgb_rov_20241209 {
     val schema = DataTypes.createStructType(fields)
     val trainDataSet: Dataset[Row] = spark.createDataFrame(trainData, schema)
     val vectorAssembler = new VectorAssembler().setInputCols(features).setOutputCol("features")
-    val xgbInput = vectorAssembler.transform(trainDataSet).select("features", "label")
+    val xgbInput = vectorAssembler.transform(trainDataSet).select("features", "label").persist()
     //    val xgbParam = Map("eta" -> 0.01f,
     //      "max_depth" -> 5,
     //      "objective" -> "binary:logistic",