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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 logNormalVectorRDD(sc, mean, std, numRows, numCols, numPartitions=None, seed=None):
 """ Generates an RDD comprised of vectors containing i.i.d. samples drawn from the log normal distribution. :param sc: SparkContext used to create the RDD. :param mean: Mean of the log normal distribution :param std: Standard Deviation of the log normal distribution :param numRows: Number of Vectors in the RDD. :param numCols: Number of elements in each Vector. :param numPartitions: Number of partitions in the RDD (default: `sc.defaultParallelism`). :param seed: Random seed (default: a random long integer). :return: RDD of Vector with vectors containing i.i.d. samples ~ log `N(mean, std)`. (100, 100) True True """

        return callMLlibFunc("logNormalVectorRDD", sc._jsc, float(mean), float(std),
                             numRows, numCols, numPartitions, seed)