Cloudera CCA175 - CCA Spark and Hadoop Developer Exam
Problem Scenario 8 : You have been given following mysql database details as well as other info.
Please accomplish following.
1. Import joined result of orders and order_items table join on orders.order_id = order_items.order_item_order_id.
2. Also make sure each tables file is partitioned in 2 files e.g. part-00000, part-00002
3. Also make sure you use orderid columns for sqoop to use for boundary conditions.
Problem Scenario 5 : You have been given following mysql database details.
user=retail_dba
password=cloudera
database=retail_db
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
1. List all the tables using sqoop command from retail_db
2. Write simple sqoop eval command to check whether you have permission to read database tables or not.
3. Import all the tables as avro files in /user/hive/warehouse/retail cca174.db
4. Import departments table as a text file in /user/cloudera/departments.
Problem Scenario 11 : You have been given following mysql database details as well as other info.
user=retail_dba
password=cloudera
database=retail_db
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following.
1. Import departments table in a directory called departments.
2. Once import is done, please insert following 5 records in departments mysql table.
Insert into departments(10, physics);
Insert into departments(11, Chemistry);
Insert into departments(12, Maths);
Insert into departments(13, Science);
Insert into departments(14, Engineering);
3. Now import only new inserted records and append to existring directory . which has been created in first step.
Problem Scenario 73 : You have been given data in json format as below.
{"first_name":"Ankit", "last_name":"Jain"}
{"first_name":"Amir", "last_name":"Khan"}
{"first_name":"Rajesh", "last_name":"Khanna"}
{"first_name":"Priynka", "last_name":"Chopra"}
{"first_name":"Kareena", "last_name":"Kapoor"}
{"first_name":"Lokesh", "last_name":"Yadav"}
Do the following activity
1. create employee.json file locally.
2. Load this file on hdfs
3. Register this data as a temp table in Spark using Python.
4. Write select query and print this data.
5. Now save back this selected data in json format.
Problem Scenario 30 : You have been given three csv files in hdfs as below.
EmployeeName.csv with the field (id, name)
EmployeeManager.csv (id, manager Name)
EmployeeSalary.csv (id, Salary)
Using Spark and its API you have to generate a joined output as below and save as a text tile (Separated by comma) for final distribution and output must be sorted by id.
ld,name,salary,managerName
EmployeeManager.csv
E01,Vishnu
E02,Satyam
E03,Shiv
E04,Sundar
E05,John
E06,Pallavi
E07,Tanvir
E08,Shekhar
E09,Vinod
E10,Jitendra
EmployeeName.csv
E01,Lokesh
E02,Bhupesh
E03,Amit
E04,Ratan
E05,Dinesh
E06,Pavan
E07,Tejas
E08,Sheela
E09,Kumar
E10,Venkat
EmployeeSalary.csv
E01,50000
E02,50000
E03,45000
E04,45000
E05,50000
E06,45000
E07,50000
E08,10000
E09,10000
E10,10000
Problem Scenario 81 : You have been given MySQL DB with following details. You have been given following product.csv file
product.csv
productID,productCode,name,quantity,price
1001,PEN,Pen Red,5000,1.23
1002,PEN,Pen Blue,8000,1.25
1003,PEN,Pen Black,2000,1.25
1004,PEC,Pencil 2B,10000,0.48
1005,PEC,Pencil 2H,8000,0.49
1006,PEC,Pencil HB,0,9999.99
Now accomplish following activities.
1. Create a Hive ORC table using SparkSql
2. Load this data in Hive table.
3. Create a Hive parquet table using SparkSQL and load data in it.
Problem Scenario 41 : You have been given below code snippet.
val aul = sc.parallelize(List (("a" , Array(1,2)), ("b" , Array(1,2))))
val au2 = sc.parallelize(List (("a" , Array(3)), ("b" , Array(2))))
Apply the Spark method, which will generate below output.
Array[(String, Array[lnt])] = Array((a,Array(1, 2)), (b,Array(1, 2)), (a(Array(3)), (b,Array(2)))
Problem Scenario 46 : You have been given belwo list in scala (name,sex,cost) for each work done.
List( ("Deeapak" , "male", 4000), ("Deepak" , "male", 2000), ("Deepika" , "female", 2000),("Deepak" , "female", 2000), ("Deepak" , "male", 1000) , ("Neeta" , "female", 2000))
Now write a Spark program to load this list as an RDD and do the sum of cost for combination of name and sex (as key)
Problem Scenario 20 : You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.categories
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
1. Write a Sqoop Job which will import "retaildb.categories" table to hdfs, in a directory name "categories_targetJob".
Problem Scenario 91 : You have been given data in json format as below.
{"first_name":"Ankit", "last_name":"Jain"}
{"first_name":"Amir", "last_name":"Khan"}
{"first_name":"Rajesh", "last_name":"Khanna"}
{"first_name":"Priynka", "last_name":"Chopra"}
{"first_name":"Kareena", "last_name":"Kapoor"}
{"first_name":"Lokesh", "last_name":"Yadav"}
Do the following activity
1. create employee.json tile locally.
2. Load this tile on hdfs
3. Register this data as a temp table in Spark using Python.
4. Write select query and print this data.
5. Now save back this selected data in json format.
