CCA175 Exam Dumps : CCA Spark and Hadoop Developer Exam

Solution :

val z = x.intersection(y)

intersection : Returns the elements in the two RDDs which are the same.

Solution :

Step 1 : Select Maximum, minimum, average , Standard Deviation, and total quantity.

val results = sqlContext.sql('.....SELECT MAX(price) AS MAX , MIN(price) AS MIN , AVG(price) AS Average, STD(price) AS STD, SUM(quantity) AS total_products FROM products......)

results. showQ

Step 2 : Select minimum and maximum price for each product code.

val results = sqlContext.sql(......SELECT code, MAX(price) AS Highest Price', MIN(price) AS Lowest Price'

FROM products GROUP BY code......)

results. showQ

Step 3 : Select Maximum, minimum, average , Standard Deviation, and total quantity for each product code, hwoever make sure Average and Standard deviation will have maximum two decimal values.

val results = sqlContext.sql(......SELECT code, MAX(price), MIN(price),

CAST(AVG(price} AS DECIMAL(7,2)) AS Average', CAST(STD(price) AS DECIMAL(7,2)) AS 'Std Dev\ SUM(quantity) FROM products

GROUP BY code......)

results. showQ

Step 4 : Select all the product code and average price only where product count is more than or equal to 3.

val results = sqlContext.sql(......SELECT code AS Product Code',

COUNTf) AS Count',

CAST(AVG(price) AS DECIMAL(7,2)) AS Average' FROM products GROUP BY code

HAVING Count >=3"M") results. showQ

Step 5 : Select maximum, minimum , average and total of all the products for each code. Also produce the same across all the products.

val results = sqlContext.sql( """SELECT

code,

MAX(price),

MIN(pnce),

CAST(AVG(price) AS DECIMAL(7,2)) AS Average',

SUM(quantity)-

FROM products

GROUP BY code

WITH ROLLUP""" )

results. show()

Solution : pairRDD1.fullOuterJoin(pairRDD2).collect

fullOuterJoin [Pair]

Performs the full outer join between two paired RDDs.

Listing Variants

def fullOuterJoin[W](other: RDD[(K, W)], numPartitions: Int): RDD[(K, (Option[V], OptionfW]))]

def fullOuterJoin[W](other: RDD[(K, W}]}: RDD[(K, (Option[V], OptionfW]))]

def fullOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (Option[V], Option[W]))]