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NEW QUESTION: 1
What is the minimum memory in gigabyte (GB) required for a QRadar All-in-One Virtual 3199 appliance?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Reference:
https://www.ibm.com/support/knowledgecenter/en/SS42VS_7.3.1/com.ibm.qradar.doc/ c_qradar_ha_vrt_ap_reqs.html

NEW QUESTION: 2
CORRECT TEXT
Problem Scenario 42 : You have been given a file (sparklO/sales.txt), with the content as given in below.
spark10/sales.txt
Department,Designation,costToCompany,State
Sales,Trainee,12000,UP
Sales,Lead,32000,AP
Sales,Lead,32000,LA
Sales,Lead,32000,TN
Sales,Lead,32000,AP
Sales,Lead,32000,TN
Sales,Lead,32000,LA
Sales,Lead,32000,LA
Marketing,Associate,18000,TN
Marketing,Associate,18000,TN
HR,Manager,58000,TN
And want to produce the output as a csv with group by Department,Designation,State with additional columns with sum(costToCompany) and TotalEmployeeCountt
Should get result like
Dept,Desg,state,empCount,totalCost
Sales,Lead,AP,2,64000
Sales.Lead.LA.3.96000
Sales,Lead,TN,2,64000
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
step 1 : Create a file first using Hue in hdfs.
Step 2 : Load tile as an RDD
val rawlines = sc.textFile("spark10/sales.txt")
Step 3 : Create a case class, which can represent its column fileds. case class
Employee(dep: String, des: String, cost: Double, state: String)
Step 4 : Split the data and create RDD of all Employee objects.
val employees = rawlines.map(_.split(",")).map(row=>Employee(row(0), row{1), row{2).toDouble, row{3)))
Step 5 : Create a row as we needed. All group by fields as a key and value as a count for each employee as well as its cost, val keyVals = employees.map( em => ((em.dep, em.des, em.state), (1 , em.cost)))
Step 6 : Group by all the records using reduceByKey method as we want summation as well. For number of employees and their total cost, val results = keyVals.reduceByKey{
(a,b) => (a._1 + b._1, a._2 + b._2)} // (a.count + b.count, a.cost + b.cost)}
Step 7 : Save the results in a text file as below.
results.repartition(1).saveAsTextFile("spark10/group.txt")

NEW QUESTION: 3
HOTSPOT


Answer:
Explanation:

NEW QUESTION: 4
DRAG DROP
Place the appropriate token next to each graphic

Answer:
Explanation:

Explanation:

Reference:http://en.wikipedia.org/wiki/List_of_video_connectors