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NEW QUESTION: 1
CORRECT TEXT
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
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create all three files in hdfs in directory called sparkl (We will do using Hue}.
However, you can first create in local filesystem and then
Step 2 : Load EmployeeManager.csv file from hdfs and create PairRDDs
val manager = sc.textFile("spark1/EmployeeManager.csv")
val managerPairRDD = manager.map(x=> (x.split(",")(0),x.split(",")(1)))
Step 3 : Load EmployeeName.csv file from hdfs and create PairRDDs
val name = sc.textFile("spark1/EmployeeName.csv")
val namePairRDD = name.map(x=> (x.split(",")(0),x.split('\")(1)))
Step 4 : Load EmployeeSalary.csv file from hdfs and create PairRDDs
val salary = sc.textFile("spark1/EmployeeSalary.csv")
val salaryPairRDD = salary.map(x=> (x.split(",")(0),x.split(",")(1)))
Step 4 : Join all pairRDDS
val joined = namePairRDD.join(salaryPairRDD}.join(managerPairRDD}
Step 5 : Now sort the joined results, val joinedData = joined.sortByKey()
Step 6 : Now generate comma separated data.
val finalData = joinedData.map(v=> (v._1, v._2._1._1, v._2._1._2, v._2._2))
Step 7 : Save this output in hdfs as text file.
finalData.saveAsTextFile("spark1/result.txt")
NEW QUESTION: 2
A company is running a multi-tier ecommerce web application In the AWS Cloud. The application runs on Amazon EC2 Instances with an Amazon RDS MySQL Mutt>AZ DB instance.
Amazon RDS is configured with the latest generation instance with 2,000 GB of storage in an Amazon EBS General Purpose SSD (gp2) volume.
The database performance impacts the application during periods of high demand.
After analyzing the logs in Amazon CloudWatch Logs, a database administrator finds that the application performance always degrades when the number of read and write IOPS is higher than
6.000
What should a solutions architect do to improve the application performance?
A. Replace the 2,000 GB gp2 volume with two 1,000 GBgp2 volumes.
B. Increase the number of IOPS on the gp2 volume
C. Replace the volume with a Magnetic volume
D. Replace the volume with a Provisioned IOPS (PIOPS) volume.
Answer: D
NEW QUESTION: 3
In a stateful inspection firewall, data packets are captured by an inspection engine that is operating at the:
A. Network or Transport Layer.
B. Inspection Layer.
C. Application Layer.
D. Data Link Layer.
Answer: A
Explanation:
Most stateful packet inspection firewalls work at the network or transport layers. For the TCP/IP protcol, this allows the firewall to make decisions both on IP addresses, protocols and TCP/UDP port numbers
Application layer is incorrect. This is too high in the OSI stack for this type of firewall.
Inspection layer is incorrect. There is no such layer in the OSI stack.
"Data link layer" is incorrect. This is too low in the OSI stack for this type of firewall.
References:
CBK, p. 466
AIO3, pp. 485 - 486
NEW QUESTION: 4
In authentication, which of the following represents something you have?
A. Token
B. Fingerprint
C. PIN
D. Password
Answer: A