RandomForest in Pyspark (version 1.4.1)

[SK <sk...@gmail.com>]

Hi,

I tried to develop a RandomForest model for my data in PySpark as follows:

       rf_model = RandomForest.trainClassifier(train_idf, 2, {},
numTrees=15, seed=144)
       print "RF: Num trees = %d, Num nodes = %d\n" %(rf_model.numTrees(),
rf_model.totalNumNodes())

       pred_label = test_idf.map(lambda p:
(float(rf_model.predict(p.features)), p.label))
       print pred_label.take(5)  ##--------> exception

I am  getting the following error at the highlighted statement.
      
         Exception: It appears that you are attempting to reference
SparkContext from a broadcast variable, action, or   transforamtion.
SparkContext can only be used on the driver, not in code that it run on
workers. For more information, see SPARK-5063.

 I have used the same set of statements for linear models
(LogisticRegresssion and SVM) in PySpark and was able to get the predictions
abd print them.  I am not sure why I am getting the above exception. I am
not using the SparkContenxt directly in any of the above statements. I would
appreciate your help. 

thanks







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