Updated Jul-2022 CCA175 Exam Practice Test Questions [Q47-Q68]

NO.47 CORRECT TEXT
Problem Scenario 62 : You have been given below code snippet.
val a = sc.parallelize(List(“dogM, “tiger”, “lion”, “cat”, “panther”, “eagle”), 2) val b = a.map(x => (x.length, x)) operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(lnt, String)] = Array((3,xdogx), (5,xtigerx), (4,xlionx), (3,xcatx), (7,xpantherx),
(5,xeaglex))

NO.48 CORRECT TEXT
Problem Scenario 54 : You have been given below code snippet.
val a = sc.parallelize(List(“dog”, “tiger”, “lion”, “cat”, “panther”, “eagle”)) val b = a.map(x => (x.length, x)) operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(lnt, String)] = Array((4,lion), (7,panther), (3,dogcat), (5,tigereagle))

NO.49 CORRECT TEXT
Problem Scenario 9 : 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.
2. Again import departments table same directory (However, directory already exist hence it should not overrride and append the results)
3. Also make sure your results fields are terminated by ‘|’ and lines terminated by ‘n

NO.50 CORRECT TEXT
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.

NO.51 CORRECT TEXT
Problem Scenario 94 : You have to run your Spark application on yarn with each executor
20GB and number of executors should be 50. Please replace XXX, YYY, ZZZ export HADOOP_CONF_DIR=XXX
./bin/spark-submit
-class com.hadoopexam.MyTask
xxx
-deploy-mode cluster # can be client for client mode
YYY
2 22
/path/to/hadoopexam.jar
1 000

NO.52 CORRECT TEXT
Problem Scenario 87 : You have been given below three files
product.csv (Create this file in hdfs)
productID,productCode,name,quantity,price,supplierid
1 001,PEN,Pen Red,5000,1.23,501
1 002,PEN,Pen Blue,8000,1.25,501
1003,PEN,Pen Black,2000,1.25,501
1004,PEC,Pencil 2B,10000,0.48,502
1005,PEC,Pencil 2H,8000,0.49,502
1006,PEC,Pencil HB,0,9999.99,502
2001,PEC,Pencil 3B,500,0.52,501
2002,PEC,Pencil 4B,200,0.62,501
2003,PEC,Pencil 5B,100,0.73,501
2004,PEC,Pencil 6B,500,0.47,502
supplier.csv
supplierid,name,phone
501,ABC Traders,88881111
502,XYZ Company,88882222
503,QQ Corp,88883333
products_suppliers.csv
productID,supplierID
2001,501
2002,501
2003,501
2004,502
2001,503
Now accomplish all the queries given in solution.
Select product, its price , its supplier name where product price is less than 0.6 using
SparkSQL

NO.53 CORRECT TEXT
Problem Scenario 21 : You have been given log generating service as below.
startjogs (It will generate continuous logs)
tailjogs (You can check , what logs are being generated)
stopjogs (It will stop the log service)
Path where logs are generated using above service : /opt/gen_logs/logs/access.log
Now write a flume configuration file named flumel.conf , using that configuration file dumps logs in HDFS file system in a directory called flumel. Flume channel should have following property as well. After every 100 message it should be committed, use non-durable/faster channel and it should be able to hold maximum 1000 events
Solution :
Step 1 : Create flume configuration file, with below configuration for source, sink and channel.
#Define source , sink , channel and agent,
agent1 .sources = source1
agent1 .sinks = sink1
agent1.channels = channel1
# Describe/configure source1
agent1 .sources.source1.type = exec
agent1.sources.source1.command = tail -F /opt/gen logs/logs/access.log
## Describe sinkl
agentl .sinks.sinkl.channel = memory-channel
agentl .sinks.sinkl .type = hdfs
agentl .sinks.sink1.hdfs.path = flumel
agentl .sinks.sinkl.hdfs.fileType = Data Stream
# Now we need to define channell property.
agent1.channels.channel1.type = memory
agent1.channels.channell.capacity = 1000
agent1.channels.channell.transactionCapacity = 100
# Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1
Step 2 : Run below command which will use this configuration file and append data in hdfs.
Start log service using : startjogs
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file
/home/cloudera/flumeconf/flumel.conf-Dflume.root.logger=DEBUG,INFO,console
Wait for few mins and than stop log service.
Stop_logs

NO.54 CORRECT TEXT
Problem Scenario 45 : You have been given 2 files , with the content as given Below
(spark12/technology.txt)
(spark12/salary.txt)
(spark12/technology.txt)
first,last,technology
Amit,Jain,java
Lokesh,kumar,unix
Mithun,kale,spark
Rajni,vekat,hadoop
Rahul,Yadav,scala
(spark12/salary.txt)
first,last,salary
Amit,Jain,100000
Lokesh,kumar,95000
Mithun,kale,150000
Rajni,vekat,154000
Rahul,Yadav,120000
Write a Spark program, which will join the data based on first and last name and save the joined results in following format, first Last.technology.salary

NO.55 CORRECT TEXT
Problem Scenario 61 : 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”,”wolf”,”bear”,”bee”), 3) val d = c.keyBy(_.length) operationl
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(lnt, (String, Option[String]}}] = Array((6,(salmon,Some(salmon))),
(6,(salmon,Some(rabbit))),
(6,(salmon,Some(turkey))), (6,(salmon,Some(salmon))), (6,(salmon,Some(rabbit))),
(6,(salmon,Some(turkey))), (3,(dog,Some(dog))), (3,(dog,Some(cat))),
(3,(dog,Some(dog))), (3,(dog,Some(bee))), (3,(rat,Some(dogg)), (3,(rat,Some(cat)j),
(3,(rat.Some(gnu))). (3,(rat,Some(bee))), (8,(elephant,None)))

NO.56 CORRECT TEXT
Problem Scenario 79 : You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.orders
table=retail_db.order_items
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Columns of products table : (product_id | product categoryid | product_name | product_description | product_prtce | product_image )
Please accomplish following activities.
1 . Copy “retaildb.products” table to hdfs in a directory p93_products
2 . Filter out all the empty prices
3 . Sort all the products based on price in both ascending as well as descending order.
4 . Sort all the products based on price as well as product_id in descending order.
5 . Use the below functions to do data ordering or ranking and fetch top 10 elements top() takeOrdered() sortByKey()

NO.57 CORRECT TEXT
Problem Scenario 75 : You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.orders
table=retail_db.order_items
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
1. Copy “retail_db.order_items” table to hdfs in respective directory p90_order_items .
2. Do the summation of entire revenue in this table using pyspark.
3. Find the maximum and minimum revenue as well.
4. Calculate average revenue
Columns of ordeMtems table : (order_item_id , order_item_order_id ,
order_item_product_id, order_item_quantity,order_item_subtotal,order_
item_subtotal,order_item_product_price)

NO.58 CORRECT TEXT
Problem Scenario 71 :
Write down a Spark script using Python,
In which it read a file “Content.txt” (On hdfs) with following content.
After that split each row as (key, value), where key is first word in line and entire line as value.
Filter out the empty lines.
And save this key value in “problem86” as Sequence file(On hdfs)
Part 2 : Save as sequence file , where key as null and entire line as value. Read back the stored sequence files.
Content.txt
Hello this is ABCTECH.com
This is XYZTECH.com
Apache Spark Training
This is Spark Learning Session
Spark is faster than MapReduce

NO.59 CORRECT TEXT
Problem Scenario 3: 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. Import data from categories table, where category=22 (Data should be stored in categories subset)
2. Import data from categories table, where category>22 (Data should be stored in categories_subset_2)
3. Import data from categories table, where category between 1 and 22 (Data should be stored in categories_subset_3)
4. While importing catagories data change the delimiter to ‘|’ (Data should be stored in categories_subset_S)
5. Importing data from catagories table and restrict the import to category_name,category id columns only with delimiter as ‘|’
6 . Add null values in the table using below SQL statement ALTER TABLE categories modify category_department_id int(11); INSERT INTO categories values
(eO.NULL.’TESTING’);
7. Importing data from catagories table (In categories_subset_17 directory) using ‘|’ delimiter and categoryjd between 1 and 61 and encode null values for both string and non string columns.
8. Import entire schema retail_db in a directory categories_subset_all_tables

NO.60 CORRECT TEXT
Problem Scenario 43 : You have been given following code snippet.
val grouped = sc.parallelize(Seq(((1,”twoM), List((3,4), (5,6)))))
val flattened = grouped.flatMap {A =>
groupValues.map { value => B }
}
You need to generate following output.
Hence replace A and B
Array((1,two,3,4),(1,two,5,6))

NO.61 CORRECT TEXT
Problem Scenario 1:
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 . Connect MySQL DB and check the content of the tables.
2 . Copy “retaildb.categories” table to hdfs, without specifying directory name.
3 . Copy “retaildb.categories” table to hdfs, in a directory name “categories_target”.
4 . Copy “retaildb.categories” table to hdfs, in a warehouse directory name
“categories_warehouse”.

NO.62 CORRECT TEXT
Problem Scenario 58 : You have been given below code snippet.
val a = sc.parallelize(List(“dog”, “tiger”, “lion”, “cat”, “spider”, “eagle”), 2) val b = a.keyBy(_.length) operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(lnt, Seq[String])] = Array((4,ArrayBuffer(lion)), (6,ArrayBuffer(spider)),
(3,ArrayBuffer(dog, cat)), (5,ArrayBuffer(tiger, eagle}}}

NO.63 CORRECT TEXT
Problem Scenario 18 : 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
Now accomplish following activities.
1. Create mysql table as below.
mysql –user=retail_dba -password=cloudera
use retail_db
CREATE TABLE IF NOT EXISTS departments_hive02(id int, department_name
varchar(45), avg_salary int);
show tables;
2. Now export data from hive table departments_hive01 in departments_hive02. While exporting, please note following. wherever there is a empty string it should be loaded as a null value in mysql.
wherever there is -999 value for int field, it should be created as null value.

NO.64 CORRECT TEXT
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.

NO.65 CORRECT TEXT
Problem Scenario 31 : You have given following two files
1 . Content.txt: Contain a huge text file containing space separated words.
2 . Remove.txt: Ignore/filter all the words given in this file (Comma Separated).
Write a Spark program which reads the Content.txt file and load as an RDD, remove all the words from a broadcast variables (which is loaded as an RDD of words from Remove.txt).
And count the occurrence of the each word and save it as a text file in HDFS.
Content.txt
Hello this is ABCTech.com
This is TechABY.com
Apache Spark Training
This is Spark Learning Session
Spark is faster than MapReduce
Remove.txt
Hello, is, this, the

NO.66 CORRECT TEXT
Problem Scenario 55 : You have been given below code snippet.
val pairRDDI = sc.parallelize(List( (“cat”,2), (“cat”, 5), (“book”, 4),(“cat”, 12))) val pairRDD2 = sc.parallelize(List( (“cat”,2), (“cup”, 5), (“mouse”, 4),(“cat”, 12))) operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(String, (Option[lnt], Option[lnt]))] = Array((book,(Some(4},None)),
(mouse,(None,Some(4))), (cup,(None,Some(5))), (cat,(Some(2),Some(2)),
(cat,(Some(2),Some(12))), (cat,(Some(5),Some(2))), (cat,(Some(5),Some(12))),
(cat,(Some(12),Some(2))), (cat,(Some(12),Some(12)))J

NO.67 CORRECT TEXT
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)))

NO.68 CORRECT TEXT
Problem Scenario 67 : You have been given below code snippet.
lines = sc.parallelize([‘lts fun to have fun,’,’but you have to know how.’])
M = lines.map( lambda x: x.replace(‘,7 ‘).replace(‘.’,’ ‘J.replaceC-V ‘).lower()) r2 = r1.flatMap(lambda x: x.split()) r3 = r2.map(lambda x: (x, 1)) operation1
r5 = r4.map(lambda x:(x[1],x[0]))
r6 = r5.sortByKey(ascending=False)
r6.take(20)
Write a correct code snippet for operationl which will produce desired output, shown below.
[(2, ‘fun’), (2, ‘to’), (2, ‘have’), (1, its’), (1, ‘know1), (1, ‘how1), (1, ‘you’), (1, ‘but’)]