[SPARK-2871] [PySpark] add histgram() API

RDD.histogram(buckets)

        Compute a histogram using the provided buckets. The buckets
        are all open to the right except for the last which is closed.
        e.g. [1,10,20,50] means the buckets are [1,10) [10,20) [20,50],
        which means 1<=x<10, 10<=x<20, 20<=x<=50. And on the input of 1
        and 50 we would have a histogram of 1,0,1.

        If your histogram is evenly spaced (e.g. [0, 10, 20, 30]),
        this can be switched from an O(log n) inseration to O(1) per
        element(where n = # buckets).

        Buckets must be sorted and not contain any duplicates, must be
        at least two elements.

        If `buckets` is a number, it will generates buckets which is
        evenly spaced between the minimum and maximum of the RDD. For
        example, if the min value is 0 and the max is 100, given buckets
        as 2, the resulting buckets will be [0,50) [50,100]. buckets must
        be at least 1 If the RDD contains infinity, NaN throws an exception
        If the elements in RDD do not vary (max == min) always returns
        a single bucket.

        It will return an tuple of buckets and histogram.

        >>> rdd = sc.parallelize(range(51))
        >>> rdd.histogram(2)
        ([0, 25, 50], [25, 26])
        >>> rdd.histogram([0, 5, 25, 50])
        ([0, 5, 25, 50], [5, 20, 26])
        >>> rdd.histogram([0, 15, 30, 45, 60], True)
        ([0, 15, 30, 45, 60], [15, 15, 15, 6])
        >>> rdd = sc.parallelize(["ab", "ac", "b", "bd", "ef"])
        >>> rdd.histogram(("a", "b", "c"))
        (('a', 'b', 'c'), [2, 2])

closes #122, it's duplicated.