Problem $2$: Working with a Numerical RDD

In the first code cell for this problem, we will create a randomly generated RDD and will then calculate some

descriptive statistics for this RDD$.$

Complete the following steps in a single code cell:

$1.$ Use the following line of code to create an RDD containing $1\mathrm{.}2$ million elements randomly selected

from the interval $[0,1]$: random$\_$rdd $=$ RandomRDDs.uniformRDD$($sc$,$ size$=1200000,$

seed$=1)$

$2.$ Use built$-$in RDD methods to calculate the sum, mean, standard deviation, minimum, and maximum

of the values stored in random$\_$rdd$.$ Display the results in the format shown below, replacing the

xxxx strings with the appropriate values. Add spacing to ensure that the numerical values are leftaligned.

Sum: xxxx

Mean: xxxx

Std Dev: xxxx

Minimum: xxxx

Maximum: xxxx

In the second cell in Problem $2,$ we will explore how the RDD we created has been partitioned.

Complete the following steps in a single code cell:

$1.$ Use the getNumPartitions$()$ RDD method to determine the number of partitions used for

random$\_$rdd$.$

$2.$ Use glom$()$ and map$()$ along with the built$-$in Python function len$()$ to create a list that contains

the number of elements contained within each of the partitions of random$\_$rdd$.$ Try to complete this

task with a single line of code by chaining together RDD transformations, followed by collect$().$

$3.$ Print the results in the format shown below, replace the xxxx strings with the appropriate values.

Number of Partitions: xxxx

Size of Partitions:

$[$xxxx$,$ xxxx$,$ xxxx$,$ xxxx$]$