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NEW QUESTION: 1
Scenario: Multiple virtual servers are configured in a NetScaler Gateway implementation.
Corporate policy requires that an administrator restrict the number of users who can log on through each virtual server.
What could the administrator specify to meet the needs of this scenario?
A. Max Users in a session policy
B. Allowed users to logon in the Access Gateway Global Settings
C. Max Connections on the virtual server
D. Max Users on the virtual server
Answer: D

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
When integrating with external systems, one concern is managing how the connection information may vary as the application migrates from Development through Production. This problem is solved by using which of the following PRPC techniques? (Choose One)
A. Circumstanced Data Transform rules
B. Dynamic Class Referencing
C. Global Resource Settings
D. Declare Pages
Answer: C

NEW QUESTION: 4
Thenamespacevalue in the header of the incoming directive for an Amazon Alexa smart home skill specifies the:
A. endpoint specified in the message
B. context of the message
C. control message for the directive
D. capability interface of the message
Answer: C