Free CCA175 Questions Attempt

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 15 : 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 activities.

1. In mysql departments table please insert following record. Insert into departments values(9999, '"Data Science"1);

2. Now there is a downstream system which will process dumps of this file. However, system is designed the way that it can process only files if fields are enlcosed in(') single quote and separate of the field should be (-} and line needs to be terminated by : (colon).

3. If data itself contains the " (double quote } than it should be escaped by \.

4. Please import the departments table in a directory called departments_enclosedby and file should be able to process by downstream system.

Problem Scenario 50 : You have been given below code snippet (calculating an average score}, with intermediate output.

type ScoreCollector = (Int, Double)

type PersonScores = (String, (Int, Double))

val initialScores = Array(("Fred", 88.0), ("Fred", 95.0), ("Fred", 91.0), ("Wilma", 93.0), ("Wilma", 95.0), ("Wilma", 98.0))

val wilmaAndFredScores = sc.parallelize(initialScores).cache()

val scores = wilmaAndFredScores.combineByKey(createScoreCombiner, scoreCombiner, scoreMerger)

val averagingFunction = (personScore: PersonScores) => { val (name, (numberScores, totalScore)) = personScore (name, totalScore / numberScores)

}

val averageScores = scores.collectAsMap(}.map(averagingFunction)

Expected output: averageScores: scala.collection.Map[String,Double] = Map(Fred -> 91.33333333333333, Wilma -> 95.33333333333333)

Define all three required function , which are input for combineByKey method, e.g. (createScoreCombiner, scoreCombiner, scoreMerger). And help us producing required results.

Problem Scenario 48 : You have been given below Python code snippet, with intermediate output.

We want to take a list of records about people and then we want to sum up their ages and count them.

So for this example the type in the RDD will be a Dictionary in the format of {name: NAME, age:AGE, gender:GENDER}.

The result type will be a tuple that looks like so (Sum of Ages, Count)

people = []

people.append({'name':'Amit', 'age':45,'gender':'M'})

people.append({'name':'Ganga', 'age':43,'gender':'F'})

people.append({'name':'John', 'age':28,'gender':'M'})

people.append({'name':'Lolita', 'age':33,'gender':'F'})

people.append({'name':'Dont Know', 'age':18,'gender':'T'})

peopleRdd=sc.parallelize(people) //Create an RDD

peopleRdd.aggregate((0,0), seqOp, combOp) //Output of above line : 167, 5)

Now define two operation seqOp and combOp , such that

seqOp : Sum the age of all people as well count them, in each partition. combOp : Combine results from all partitions.