Details
Major Description
This code, adapted from the documentation, fails when using a loaded model.
from pyspark.mllib.recommendation import ALS, Rating, MatrixFactorizationModel
r1 = (1, 1, 1.0)
r2 = (1, 2, 2.0)
r3 = (2, 1, 2.0)
ratings = sc.parallelize([r1, r2, r3])
model = ALS.trainImplicit(ratings, 1, seed=10)
print '(2, 2)', model.predict(2, 2)
- 0.43...
testset = sc.parallelize([(1, 2), (1, 1)])
print 'all', model.predictAll(testset).collect() - [Rating(user=1, product=1, rating=1.0...), Rating(user=1, product=2, rating=1.9...)]
import os, tempfile
path = tempfile.mkdtemp()
model.save(sc, path)
sameModel = MatrixFactorizationModel.load(sc, path)
print '(2, 2)', sameModel.predict(2,2)
sameModel.predictAll(testset).collect()
This gives
(2, 2) 0.443547642944
all [Rating(user=1, product=1, rating=1.1538351103381217), Rating(user=1, product=2, rating=0.7153473708381739)]
(2, 2) 0.443547642944
---------------------------------------------------------------------------
Py4JError Traceback (most recent call last)
<ipython-input-18-af6612bed9d0> in <module>()
19 sameModel = MatrixFactorizationModel.load(sc, path)
20 print '(2, 2)', sameModel.predict(2,2)
---> 21 sameModel.predictAll(testset).collect()
22
/home/ubuntu/spark/python/pyspark/mllib/recommendation.pyc in predictAll(self, user_product)
104 assert len(first) == 2, "user_product should be RDD of (user, product)"
105 user_product = user_product.map(lambda (u, p): (int(u), int(p)))
--> 106 return self.call("predict", user_product)
107
108 def userFeatures(self):
/home/ubuntu/spark/python/pyspark/mllib/common.pyc in call(self, name, *a)
134 def call(self, name, *a):
135 """Call method of java_model"""
--> 136 return callJavaFunc(self._sc, getattr(self._java_model, name), *a)
137
138
/home/ubuntu/spark/python/pyspark/mllib/common.pyc in callJavaFunc(sc, func, *args)
111 """ Call Java Function """
112 args = [_py2java(sc, a) for a in args]
--> 113 return _java2py(sc, func(*args))
114
115
/home/ubuntu/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in _call_(self, *args)
536 answer = self.gateway_client.send_command(command)
537 return_value = get_return_value(answer, self.gateway_client,
--> 538 self.target_id, self.name)
539
540 for temp_arg in temp_args:
/home/ubuntu/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
302 raise Py4JError(
303 'An error occurred while calling
. Trace:\n
{3}\n'.
--> 304 format(target_id, '.', name, value))
305 else:
306 raise Py4JError(
Py4JError: An error occurred while calling o450.predict. Trace:
py4j.Py4JException: Method predict([class org.apache.spark.api.java.JavaRDD]) does not exist
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:333)
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:342)
at py4j.Gateway.invoke(Gateway.java:252)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:744)
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