I think the problem is because you are calling "model2 =
ALSModel.load("/models/als")" instead of "model2 =
*model*.load("/models/als")".
See my working sample below.
>>> model.save('/models/als.test')
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further
details.
>>> model2 = model.load('/models/als.test')
>>> model
ALS_4324a1082d889dd1f0e4
>>> model2
ALS_4324a1082d889dd1f0e4
Thank You,
Irving Duran
On Sat, Jul 29, 2017 at 2:57 PM, Cristian Garcia <cgarcia....@gmail.com>
wrote:
> This code is not working:
>
> ================
> from pyspark.ml.evaluation import RegressionEvaluator
> from pyspark.ml.recommendation import ALS, ALSModel
> from pyspark.sql import Row
>
> als = ALS(maxIter=10, regParam=0.01, userCol="user_id",
> itemCol="movie_id", ratingCol="rating")
> model = als.fit(training)
>
> model.save("/models/als")
>
> model2 = ALSModel.load("/models/als") # <-- error here
> =================
>
>
>
> Gives rise to this error:
> =================
>
> ---------------------------------------------------------------------------Py4JJavaError
> Traceback (most recent call
> last)<ipython-input-24-c0454f47bb1d> in <module>()----> 1 m2 =
> ALSModel.load("/models/als")
> /usr/local/spark/python/pyspark/ml/util.py in load(cls, path) 251 def
> load(cls, path): 252 """Reads an ML instance from the input path,
> a shortcut of `read().load(path)`."""--> 253 return
> cls.read().load(path) 254 255
> /usr/local/spark/python/pyspark/ml/util.py in load(self, path) 192
> if not isinstance(path, basestring): 193 raise TypeError("path
> should be a basestring, got type %s" % type(path))--> 194 java_obj =
> self._jread.load(path) 195 if not hasattr(self._clazz,
> "_from_java"): 196 raise NotImplementedError("This Java ML
> type cannot be loaded into Python currently: %r"
> /usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in
> __call__(self, *args) 1131 answer =
> self.gateway_client.send_command(command) 1132 return_value =
> get_return_value(-> 1133 answer, self.gateway_client,
> self.target_id, self.name) 1134 1135 for temp_arg in temp_args:
> /usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw) 61 def
> deco(*a, **kw): 62 try:---> 63 return f(*a, **kw)
> 64 except py4j.protocol.Py4JJavaError as e: 65 s =
> e.java_exception.toString()
> /usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in
> get_return_value(answer, gateway_client, target_id, name) 317
> raise Py4JJavaError( 318 "An error occurred while
> calling {0}{1}{2}.\n".--> 319 format(target_id, ".",
> name), value) 320 else: 321 raise Py4JError(
> Py4JJavaError: An error occurred while calling o337.load.
> : java.lang.UnsupportedOperationException: empty collection
> at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1370)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> at org.apache.spark.rdd.RDD.first(RDD.scala:1367)
> at
> org.apache.spark.ml.util.DefaultParamsReader$.loadMetadata(ReadWrite.scala:379)
> at
> org.apache.spark.ml.recommendation.ALSModel$ALSModelReader.load(ALS.scala:317)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:280)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:214)
> at java.lang.Thread.run(Thread.java:748)
>
> =================
>
