CCA175 Exam Dumps : CCA Spark and Hadoop Developer Exam

Solution :

Step 1 : Create hive table as said.

hive

show tables;

create table departments_hive(department_id int, department_name string);

Step 2 : The important here is, when we create a table without delimiter fields. Then default delimiter for hive is ^A (\001). Hence, while importing data we have to provide proper delimiter.

sqoop import \

-connect jdbc:mysql://quickstart:3306/retail_db \

~username=retail_dba \

-password=cloudera \

--table departments \

--hive-home /user/hive/warehouse \

-hive-import \

-hive-overwrite \

--hive-table departments_hive \

--fields-terminated-by '\001'

Step 3 : Check-the data in directory.

hdfs dfs -Is /user/hive/warehouse/departments_hive

hdfs dfs -cat/user/hive/warehouse/departmentshive/part'

Check data in hive table.

Select * from departments_hive;

Solution :

Step 1 : Create 2 files first using Hue in hdfs.

Step 2 : Load all file as an RDD

val technology = sc.textFile(Msparkl2/technology.txt").map(e => e.splitf',"))

val salary = sc.textFile("spark12/salary.txt").map(e => e.split("."))

Step 3 : Now create Key.value pair of data and join them.

val joined = technology.map(e=>((e(0),e(1)),e(2))).join(salary.map(e=>((e(0),e(1)),e(2))))

Step 4 : Save the results in a text file as below.

joined.repartition(1).saveAsTextFile("spark12/multiColumn Joined.txt")

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()