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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def normalRDD(sc, size, numPartitions=None, seed=None):
 """ Generates an RDD comprised of i.i.d. samples from the standard normal distribution. To transform the distribution in the generated RDD from standard normal to some other normal N(mean, sigma^2), use C{RandomRDDs.normal(sc, n, p, seed)\ .map(lambda v: mean + sigma * v)} :param sc: SparkContext used to create the RDD. :param size: Size of the RDD. :param numPartitions: Number of partitions in the RDD (default: `sc.defaultParallelism`). :param seed: Random seed (default: a random long integer). :return: RDD of float comprised of i.i.d. samples ~ N(0.0, 1.0). 1000 True True """

        return callMLlibFunc("normalRDD", sc._jsc, size, numPartitions, seed)