PySpark join two RDD results in an empty RDD - apache-spark

Question

I'm a Spark newbie trying to edit and apply this movie recommendation tutorial(https://databricks-training.s3.amazonaws.com/movie-recommendation-with-mllib.html) on my dataset .But it keeps throwing This error :
ValueError: Can not reduce() empty RDD
This is the function that computes the Root Mean Squared Error of the model :
def computeRmse(model, data, n):
"""
Compute RMSE (Root Mean Squared Error).
"""
predictions = model.predictAll(data.map(lambda x: (x[0], x[1])))
print predictions.count()
print predictions.first()
print "predictions above"
print data.count()
print data.first()
print "validation data above"
predictionsAndRatings = predictions.map(lambda x: ((x[0], x[1]), x[2])) \
#LINE56
.join(data.map(lambda line: line.split(‘,’) ).map(lambda x: ((x[0], x[1]), x[2]))) \
.values()
print predictionsAndRatings.count()
print "predictions And Ratings above"
#LINE63
return sqrt(predictionsAndRatings.map(lambda x: (x[0] - x[1]) ** 2).reduce(add) / float(n))
model = ALS.train(training, rank, numIter, lambda). data is the validation data set.
training and validation set originally from a ratings.txt file in the format of : userID,productID,rating,ratingopID
These are parts of the output :
879
...
Rating(user=0, product=656, rating=4.122132631144641)
predictions above
...
1164
...
(u'640085', u'1590', u'5')
validation data above
...
16/08/26 12:47:18 INFO DAGScheduler: Registering RDD 259 (join at /path/myapp/MyappALS.py:56)
16/08/26 12:47:18 INFO DAGScheduler: Got job 20 (count at /path/myapp/MyappALS.py:59) with 12 output partitions
16/08/26 12:47:18 INFO DAGScheduler: Final stage: ResultStage 238 (count at /path/myapp/MyappALS.py:59)
16/08/26 12:47:18 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 237)
16/08/26 12:47:18 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 237)
16/08/26 12:47:18 INFO DAGScheduler: Submitting ShuffleMapStage 237 (PairwiseRDD[259] at join at /path/myapp/MyappALS.py:56), which has no missing parents
....
0
predictions And Ratings above
...
Traceback (most recent call last):
File "/path/myapp/MyappALS.py", line 130, in <module>
validationRmse = computeRmse(model, validation, numValidation)
File "/path/myapp/MyappALS.py", line 63, in computeRmse
return sqrt(predictionsAndRatings.map(lambda x: (x[0] - x[1]) ** 2).reduce(add) / float(n))
File "/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 805, in reduce
ValueError: Can not reduce() empty RDD
So from the count() i'm sure the initial RDD are not empty .
Than the INFO log Registering RDD 259 (join at /path/myapp/MyappALS.py:56) does it mean that the join job is launched ?
Is there something wrong i'm missing ?
Thank you .

Answer 1

That error disappeared when i added int() to :
predictionsAndRatings = predictions.map(lambda x: ((x[0], x[1]), x[2])) \
.join(data.map(lambda x: ((int(x[0]), int(x[1])), int(x[2])))) \
.values()
we think its because pediction is outputed from the method predictAll which gives tupple ,but the other data that was parsed manually by the algorithm