add pyspark rformula save/load

Author: yinxusen

python/pyspark/ml/feature.py

@@ -2360,7 +2360,7 @@ def explainedVariance(self):
 
 
 @inherit_doc
-class RFormula(JavaEstimator, HasFeaturesCol, HasLabelCol):
+class RFormula(JavaEstimator, HasFeaturesCol, HasLabelCol, MLReadable, MLWritable):
     """
     .. note:: Experimental
 
@@ -2385,7 +2385,31 @@ class RFormula(JavaEstimator, HasFeaturesCol, HasLabelCol):
     |0.0|0.0|  a|[0.0,1.0]|  0.0|
     +---+---+---+---------+-----+
     ...
-    >>> rf.fit(df, {rf.formula: "y ~ . - s"}).transform(df).show()
+    >>> model = rf.fit(df, {rf.formula: "y ~ . - s"})
+    >>> model.transform(df).show()
+    +---+---+---+--------+-----+
+    |  y|  x|  s|features|label|
+    +---+---+---+--------+-----+
+    |1.0|1.0|  a|   [1.0]|  1.0|
+    |0.0|2.0|  b|   [2.0]|  0.0|
+    |0.0|0.0|  a|   [0.0]|  0.0|
+    +---+---+---+--------+-----+
+    ...
+    >>> rFormulaPath = temp_path + "/rFormula"
+    >>> rf.save(rFormulaPath)
+    >>> loadedRF = RFormula.load(rFormulaPath)
+    >>> loadedRF.getFormula() == rf.getFormula()
+    True
+    >>> loadedRF.getFeaturesCol() == rf.getFeaturesCol()
+    True
+    >>> loadedRF.getLabelCol() == rf.getLabelCol()
+    True
+    >>> modelPath = temp_path + "/rFormula-model"
+    >>> model.save(modelPath)
+    >>> loadedModel = RFormulaModel.load(modelPath)
+    >>> loadedModel.uid == model.uid
+    True
+    >>> loadedModel.transform(df).show()
     +---+---+---+--------+-----+
     |  y|  x|  s|features|label|
     +---+---+---+--------+-----+
@@ -2439,7 +2463,7 @@ def _create_model(self, java_model):
         return RFormulaModel(java_model)
 
 
-class RFormulaModel(JavaModel):
+class RFormulaModel(JavaModel, MLReadable, MLWritable):
     """
     .. note:: Experimental