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

RDD.countApproxDistinct(relativeSD=0.05):

        :: Experimental ::
        Return approximate number of distinct elements in the RDD.

        The algorithm used is based on streamlib's implementation of
        "HyperLogLog in Practice: Algorithmic Engineering of a State
        of The Art Cardinality Estimation Algorithm", available
        <a href="http://dx.doi.org/10.1145/2452376.2452456">here</a>.

        This support all the types of objects, which is supported by
        Pyrolite, nearly all builtin types.

        @param relativeSD Relative accuracy. Smaller values create
                           counters that require more space.
                           It must be greater than 0.000017.

        >>> n = sc.parallelize(range(1000)).map(str).countApproxDistinct()
        >>> 950 < n < 1050
        True
        >>> n = sc.parallelize([i % 20 for i in range(1000)]).countApproxDistinct()
        >>> 18 < n < 22
        True
hash() in Python could be negative, but portable_hash() of tuple() are positive, we should make the hash of them share the same range.

hash % sys.maxint should be better than abs(hash), so for small range of [-N, N], we will not have hash collision for them.