[SPARK-6827] [MLLIB] Wrap FPGrowthModel.freqItemsets and make it cons…

…istent with Java API

Make PySpark ```FPGrowthModel.freqItemsets``` consistent with Java/Scala API like ```MatrixFactorizationModel.userFeatures```
It return a RDD with each tuple is composed of an array and a long value.
I think it's difficult to implement namedtuples to wrap the output because items of freqItemsets can be any type with arbitrary length which is tedious to impelement corresponding SerDe function.

Author: Yanbo Liang <[email protected]>

Closes #5614 from yanboliang/spark-6827 and squashes the following commits:

da8c404 [Yanbo Liang] use namedtuple
5532e78 [Yanbo Liang] Wrap FPGrowthModel.freqItemsets and make it consistent with Java API

python/pyspark/mllib/fpm.py

@@ -15,6 +15,10 @@
 # limitations under the License.
 #
 
+import numpy
+from numpy import array
+from collections import namedtuple
+
 from pyspark import SparkContext
 from pyspark.rdd import ignore_unicode_prefix
 from pyspark.mllib.common import JavaModelWrapper, callMLlibFunc, inherit_doc
@@ -36,14 +40,14 @@ class FPGrowthModel(JavaModelWrapper):
     >>> rdd = sc.parallelize(data, 2)
     >>> model = FPGrowth.train(rdd, 0.6, 2)
     >>> sorted(model.freqItemsets().collect())
-    [([u'a'], 4), ([u'c'], 3), ([u'c', u'a'], 3)]
+    [FreqItemset(items=[u'a'], freq=4), FreqItemset(items=[u'c'], freq=3), ...
     """
 
     def freqItemsets(self):
         """
-        Get the frequent itemsets of this model
+        Returns the frequent itemsets of this model.
         """
-        return self.call("getFreqItemsets")
+        return self.call("getFreqItemsets").map(lambda x: (FPGrowth.FreqItemset(x[0], x[1])))
 
 
 class FPGrowth(object):
@@ -67,6 +71,11 @@ def train(cls, data, minSupport=0.3, numPartitions=-1):
         model = callMLlibFunc("trainFPGrowthModel", data, float(minSupport), int(numPartitions))
         return FPGrowthModel(model)
 
+    class FreqItemset(namedtuple("FreqItemset", ["items", "freq"])):
+        """
+        Represents an (items, freq) tuple.
+        """
+
 
 def _test():
     import doctest