From f75f633b21faaf911f04aeff847f25749b1ecd89 Mon Sep 17 00:00:00 2001 From: Xiangrui Meng Date: Sat, 28 Mar 2015 15:08:05 -0700 Subject: [SPARK-6571][MLLIB] use wrapper in MatrixFactorizationModel.load This fixes `predictAll` after load. jkbradley Author: Xiangrui Meng Closes #5243 from mengxr/SPARK-6571 and squashes the following commits: 82dcaa7 [Xiangrui Meng] use wrapper in MatrixFactorizationModel.load --- python/pyspark/mllib/recommendation.py | 8 ++++++++ 1 file changed, 8 insertions(+) (limited to 'python/pyspark/mllib/recommendation.py') diff --git a/python/pyspark/mllib/recommendation.py b/python/pyspark/mllib/recommendation.py index 1a4527b12c..b094e50856 100644 --- a/python/pyspark/mllib/recommendation.py +++ b/python/pyspark/mllib/recommendation.py @@ -90,6 +90,8 @@ class MatrixFactorizationModel(JavaModelWrapper, JavaSaveable, JavaLoader): >>> sameModel = MatrixFactorizationModel.load(sc, path) >>> sameModel.predict(2,2) 0.43... + >>> sameModel.predictAll(testset).collect() + [Rating(... >>> try: ... os.removedirs(path) ... except OSError: @@ -111,6 +113,12 @@ class MatrixFactorizationModel(JavaModelWrapper, JavaSaveable, JavaLoader): def productFeatures(self): return self.call("getProductFeatures") + @classmethod + def load(cls, sc, path): + model = cls._load_java(sc, path) + wrapper = sc._jvm.MatrixFactorizationModelWrapper(model) + return MatrixFactorizationModel(wrapper) + class ALS(object): -- cgit v1.2.3