Cloudera CCA Spark and Hadoop Developer Exam CCA175 Dumps in PDF

Free Cloudera CCA175 Real Questions (page: 19)

Problem Scenario 51 : You have been given below code snippet.
val a = sc.parallelize(List(1, 2, 1, 3), 1)
val b = a.map((_, "b"))
val c = a.map((_, "c"))
Operation_xyz
Write a correct code snippet for Operationxyz which will produce below output.
Output:
Array[(lnt, (lterable[String], lterable[String]))] = Array(
(2, (ArrayBuffer(b), ArrayBuffer(c))),
(3, (ArrayBuffer(b), ArrayBuffer(c))),
(1, (ArrayBuffer(b, b), ArrayBuffer(c, c)))
)

  1. See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :
b.cogroup(c).collect
cogroup [Pair], groupWith [Pair]
A very powerful set of functions that allow grouping up to 3 key-value RDDs together using their keys.
Another example
val x = sc.parallelize(List((1, "apple"), (2, "banana"), (3, "orange"), (4, "kiwi")), 2) val y = sc.parallelize(List((5, "computer"), (1, "laptop"), (1, "desktop"), (4, "iPad")), 2)
x.cogroup(y).collect
Array[(lnt, (lterable[String], lterable[String]))] = Array( (4, (ArrayBuffer(kiwi), ArrayBuffer(iPad))),
(2, (ArrayBuffer(banana), ArrayBuffer())),
(3, (ArrayBuffer(orange), ArrayBuffer())),
(1 , (ArrayBuffer(apple), ArrayBuffer(laptop, desktop))), (5, {ArrayBuffer(), ArrayBuffer(computer))))



Problem Scenario 24 : You have been given below comma separated employee information.
Data Set:
name, salary, sex, age
alok, 100000, male, 29
jatin, 105000, male, 32
yogesh, 134000, male, 39
ragini, 112000, female, 35
jyotsana, 129000, female, 39
valmiki, 123000, male, 29
Requirements:
Use the netcat service on port 44444, and nc above data line by line. Please do the following activities.

1. Create a flume conf file using fastest channel, which write data in hive warehouse
directory, in a table called flumemaleemployee (Create hive table as well tor given data).
2. While importing, make sure only male employee data is stored.

  1. See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Step 1: Create hive table for flumeemployee.'
CREATE TABLE flumemaleemployee
(
name string,
salary int,
sex string,
age int
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ', ';
Step 2: Create flume configuration file, with below configuration for source, sink and channel and save it in flume4.conf.
#Define source , sink, channel and agent.
agent1 .sources = source1
agent1 .sinks = sink1
agent1 .channels = channel1
# Describe/configure source1
agent1 .sources.source1.type = netcat
agent1 .sources.source1.bind = 127.0.0.1
agent1.sources.sourcel.port = 44444
#Define interceptors
agent1.sources.source1.interceptors=il
agent1 .sources.source1.interceptors.i1.type=regex_filter agent1 .sources.source1.interceptors.i1.regex=female agent1 .sources.source1.interceptors.i1.excludeEvents=true
## Describe sink1
agent1 .sinks, sinkl.channel = memory-channel
agent1.sinks.sink1.type = hdfs
agent1 .sinks, sinkl. hdfs. path = /user/hive/warehouse/flumemaleemployee hdfs-agent.sinks.hdfs-write.hdfs.writeFormat=Text
agentl .sinks.sink1.hdfs.fileType = Data Stream
# Now we need to define channel1 property.
agent1.channels.channel1.type = memory
agent1.channels.channell.capacity = 1000
agent1.channels.channel1.transactionCapacity = 100
# Bind the source and sink to the channel
agent1 .sources.source1.channels = channel1
agent1 .sinks.sink1.channel = channel1
Step 3: Run below command which will use this configuration file and append data in hdfs.

Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flume4.conf --name agentl
Step 4: Open another terminal and use the netcat service, nc localhost 44444
Step 5: Enter data line by line.
alok, 100000, male, 29
jatin, 105000, male, 32
yogesh, 134000, male, 39
ragini, 112000, female, 35
jyotsana, 129000, female, 39
valmiki.123000.male.29
Step 6: Open hue and check the data is available in hive table or not.
Step 7: Stop flume service by pressing ctrl+c
Step 8: Calculate average salary on hive table using below query. You can use either hive command line tool or hue. select avg(salary) from flumeemployee;



Problem Scenario 27 : You need to implement near real time solutions for collecting information when submitted in file with below information.
Data
echo "IBM, 100, 20160104" >> /tmp/spooldir/bb/.bb.txt
echo "IBM, 103, 20160105" >> /tmp/spooldir/bb/.bb.txt
mv /tmp/spooldir/bb/.bb.txt /tmp/spooldir/bb/bb.txt
After few mins
echo "IBM, 100.2, 20160104" >> /tmp/spooldir/dr/.dr.txt
echo "IBM, 103.1, 20160105" >> /tmp/spooldir/dr/.dr.txt
mv /tmp/spooldir/dr/.dr.txt /tmp/spooldir/dr/dr.txt
Requirements:
You have been given below directory location (if not available than create it) /tmp/spooldir . You have a finacial subscription for getting stock prices from BloomBerg as well as
Reuters and using ftp you download every hour new files from their respective ftp site in directories /tmp/spooldir/bb and /tmp/spooldir/dr respectively.
As soon as file committed in this directory that needs to be available in hdfs in /tmp/flume/finance location in a single directory.
Write a flume configuration file named flume7.conf and use it to load data in hdfs with following additional properties .

1. Spool /tmp/spooldir/bb and /tmp/spooldir/dr
2. File prefix in hdfs sholuld be events
3. File suffix should be .log
4. If file is not commited and in use than it should have _ as prefix.
5. Data should be written as text to hdfs

  1. See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :
Step 1: Create directory mkdir /tmp/spooldir/bb mkdir /tmp/spooldir/dr
Step 2: Create flume configuration file, with below configuration for
agent1.sources = source1 source2
agent1 .sinks = sink1
agent1.channels = channel1
agent1 .sources.source1.channels = channel1
agentl .sources.source2.channels = channell agent1 .sinks.sinkl.channel = channell agent1 .sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir/bb
agent1 .sources.source2.type = spooldir
agent1 .sources.source2.spoolDir = /tmp/spooldir/dr
agent1 .sinks.sink1.type = hdfs
agent1 .sinks.sink1.hdfs.path = /tmp/flume/finance
agent1-sinks.sink1.hdfs.filePrefix = events
agent1.sinks.sink1.hdfs.fileSuffix = .log
agent1 .sinks.sink1.hdfs.inUsePrefix = _
agent1 .sinks.sink1.hdfs.fileType = Data Stream
agent1.channels.channel1.type = file
Step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/fIumeconf/fIume7.conf --name agent1
Step 5: Open another terminal and create a file in /tmp/spooldir/ echo "IBM, 100, 20160104" » /tmp/spooldir/bb/.bb.txt
echo "IBM, 103, 20160105" » /tmp/spooldir/bb/.bb.txt mv /tmp/spooldir/bb/.bb.txt /tmp/spooldir/bb/bb.txt
After few mins
echo "IBM, 100.2, 20160104" » /tmp/spooldir/dr/.dr.txt echo "IBM, 103.1, 20160105" »/tmp/spooldir/dr/.dr.txt mv /tmp/spooldir/dr/.dr.txt /tmp/spooldir/dr/dr.txt



Problem Scenario 60 : You have been given below code snippet.
val a = sc.parallelize(List("dog", "salmon", "salmon", "rat", "elephant"}, 3}
val b = a.keyBy(_.length)
val c = sc.parallelize(List("dog", "cat", "gnu", "salmon", "rabbit", "turkey", "woif", "bear", "bee"), 3)
val d = c.keyBy(_.length)
operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(lnt, (String, String))] = Array((6, (salmon, salmon)), (6, (salmon, rabbit)), (6, (salmon, turkey)), (6, (salmon, salmon)), (6, (salmon, rabbit)),
(6, (salmon, turkey)), (3, (dog, dog)), (3, (dog, cat)), (3, (dog, gnu)), (3, (dog, bee)), (3, (rat, dog)), (3, (rat, cat)), (3, (rat, gnu)), (3, (rat, bee)))

  1. See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

solution:
b.join(d).collect
join [Pair]: Performs an inner join using two key-value RDDs. Please note that the keys must be generally comparable to make this work. keyBy : Constructs two-component tuples (key-value pairs) by applying a function on each data item. The result of the function becomes the data item becomes the key and the original value of the newly created tuples.



Problem Scenario 90 : You have been given below two files
course.txt
id, course
1, Hadoop
2, Spark
3, HBase
fee.txt
id, fee
2, 3900
3, 4200
4, 2900
Accomplish the following activities.

1. Select all the courses and their fees , whether fee is listed or not.
2. Select all the available fees and respective course. If course does not exists still list the
fee
3. Select all the courses and their fees , whether fee is listed or not. However, ignore
records having fee as null.

  1. See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :

Step 1:
hdfs dfs -mkdir sparksql4
hdfs dfs -put course.txt sparksql4/
hdfs dfs -put fee.txt sparksql4/
Step 2: Now in spark shell
// load the data into a new RDD
val course = sc.textFile("sparksql4/course.txt")
val fee = sc.textFile("sparksql4/fee.txt")
// Return the first element in this RDD
course.fi rst()
fee.fi rst()
//define the schema using a case class case class Course(id: Integer, name: String) case class Fee(id: Integer, fee: Integer)
// create an RDD of Product objects
val courseRDD = course.map(_.split(", ")).map(c => Course(c(0).tolnt, c(1))) val feeRDD =fee.map(_.split(", ")).map(c => Fee(c(0}.tolnt, c(1}.tolnt)) courseRDD.first()
courseRDD.count(}
feeRDD.first()
feeRDD.countQ
// change RDD of Product objects to a DataFrame val courseDF = courseRDD.toDF(} val feeDF = feeRDD.toDF{)
// register the DataFrame as a temp table courseDF. registerTempTable("course") feeDF.
registerTempTablef'fee")
// Select data from table
val results = sqlContext.sql(......SELECT' FROM course """ ) results. showQ
val results = sqlContext.sql(......SELECT' FROM fee......) results. showQ
val results = sqlContext.sql(......SELECT * FROM course LEFT JOIN fee ON course.id = fee.id......)
results-showQ
val results ="sqlContext.sql(......SELECT * FROM course RIGHT JOIN fee ON course.id = fee.id "MM )
results. showQ
val results = sqlContext.sql(......SELECT' FROM course LEFT JOIN fee ON course.id = fee.id where fee.id IS NULL"
results. show()



Share your comments for Cloudera CCA175 exam with other users:

B
Berihun
7/13/2023 7:29:00 AM

all questions are so important and covers all ccna modules

N
nspk
1/19/2024 12:53:00 AM

q 44. ans:- b (goto setup > order settings > select enable optional price books for orders) reference link --> https://resources.docs.salesforce.com/latest/latest/en-us/sfdc/pdf/sfom_impl_b2b_b2b2c.pdf(decide whether you want to enable the optional price books feature. if so, select enable optional price books for orders. you can use orders in salesforce while managing price books in an external platform. if you’re using d2c commerce, you must select enable optional price books for orders.)

M
Muhammad Rawish Siddiqui
12/2/2023 5:28:00 AM

"cost of replacing data if it were lost" is also correct.

A
Anonymous
7/14/2023 3:17:00 AM

pls upload the questions

M
Mukesh
7/10/2023 4:14:00 PM

good questions

E
Elie Abou Chrouch
12/11/2023 3:38:00 AM

question 182 - correct answer is d. ethernet frame length is 64 - 1518b. length of user data containing is that frame: 46 - 1500b.

D
Damien
9/23/2023 8:37:00 AM

i need this exam pls

N
Nani
9/10/2023 12:02:00 PM

its required for me, please make it enable to access. thanks

E
ethiopia
8/2/2023 2:18:00 AM

seems good..

W
whoAreWeReally
12/19/2023 8:29:00 PM

took the test last week, i did have about 15 - 20 word for word from this site on the test. (only was able to cram 600 of the questions from this site so maybe more were there i didnt review) had 4 labs, bgp, lacp, vrf with tunnels and actually had to skip a lab due to time. lots of automation syntax questions.

V
vs
9/2/2023 12:19:00 PM

no comments

J
john adenu
11/14/2023 11:02:00 AM

nice questions bring out the best in you.

O
Osman
11/21/2023 2:27:00 PM

really helpful

E
Edward
9/13/2023 5:27:00 PM

question #50 and question #81 are exactly the same questions, azure site recovery provides________for virtual machines. the first says that it is fault tolerance is the answer and second says disater recovery. from my research, it says it should be disaster recovery. can anybody explain to me why? thank you

M
Monti
5/24/2023 11:14:00 PM

iam thankful for these exam dumps questions, i would not have passed without this exam dumps.

A
Anon
10/25/2023 10:48:00 PM

some of the answers seem to be inaccurate. q10 for example shouldnt it be an m custom column?

P
PeterPan
10/18/2023 10:22:00 AM

are the question real or fake?

C
CW
7/11/2023 3:19:00 PM

thank you for providing such assistance.

M
Mn8300
11/9/2023 8:53:00 AM

nice questions

N
Nico
4/23/2023 11:41:00 PM

my 3rd purcahse from this site. these exam dumps are helpful. very helpful.

C
Chere
9/15/2023 4:21:00 AM

found it good

T
Thembelani
5/30/2023 2:47:00 AM

excellent material

V
vinesh phale
9/11/2023 2:51:00 AM

very helpfull

B
Bhagiii
11/4/2023 7:04:00 AM

well explained.

R
Rahul
8/8/2023 9:40:00 PM

i need the pdf, please.

C
CW
7/11/2023 2:51:00 PM

a good source for exam preparation

A
Anchal
10/23/2023 4:01:00 PM

nice questions

J
J Nunes
9/29/2023 8:19:00 AM

i need ielts general training audio guide questions

A
Ananya
9/14/2023 5:16:00 AM

please make this content available

S
Swathi
6/4/2023 2:18:00 PM

content is good

L
Leo
7/29/2023 8:45:00 AM

latest dumps please

L
Laolu
2/15/2023 11:04:00 PM

aside from pdf the test engine software is helpful. the interface is user-friendly and intuitive, making it easy to navigate and find the questions.

Z
Zaynik
9/17/2023 5:36:00 AM

questions and options are correct, but the answers are wrong sometimes. so please check twice or refer some other platform for the right answer

M
Massam
6/11/2022 5:55:00 PM

90% of questions was there but i failed the exam, i marked the answers as per the guide but looks like they are not accurate , if not i would have passed the exam given that i saw about 45 of 50 questions from dump

AI Tutor 👋 I’m here to help!