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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 logNormalRDD(sc, mean, std, size, numPartitions=None, seed=None):
 """ Generates an RDD comprised of i.i.d. samples from the log normal distribution with the input mean and standard distribution. :param sc: SparkContext used to create the RDD. :param mean: mean for the log Normal distribution :param std: std for the log Normal distribution :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 ~ log N(mean, std). 1000 True True """

        return callMLlibFunc("logNormalRDD", sc._jsc, float(mean), float(std),
                             size, numPartitions, seed)