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NEW QUESTION: 1
Which of the following is not a component of "The HANA - Optimized data store"?
Please choose the correct answer.
Response:
A. SID creation optimized
B. Active table
C. Activation Queue
D. Change log
Answer: A

NEW QUESTION: 2
DRAG DROP


Answer:
Explanation:

Explanation:
Box 1: Create a multi-factor authentication provider with the Per Enabled User usage model.
Box 2: Enable multi-factor authentication for all user accounts.
Box 3: Instruct users to use a mobile phone to complete the registration process.
Adding Multi-Factor Authentication to Azure Active Directory (for Office 365 users) Step 1: First we create the usage model of the MFA provider.
We should use PerEnabled User which is used for Office 365.
Note:
* Per Authentication - purchasing model that charges per authentication. Typically used for scenarios that use the Azure Multi-Factor Authentication in an application.
* Per Enabled User - purchasing model that charges per enabled user. Typically used for scenarios such as Office 365.
Step 2: Enable Multi-Factor Authentication for all your user accounts.
You need to enable multi-factor authentication on your Office 365 users.
Step 3: Have a user sign-in and complete the registration process.
The users can use their mobile phones to complete the auto-enrollment process.
Details: After being enrolled for multi-factor authentication, the next time a user signs in, they see a message asking them to set up their second authentication factor. Using the enrollment process the users will be able to specify your preferred method of verification.
The following methods exist: Mobile Phone Call, Mobile Phone Text Message, Office Phone Call, or Mobile App.
References:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/multi-factor- authentication/multi-factor-authentication-get-started-auth-provider.md

NEW QUESTION: 3

A. Option E
B. Option A
C. Option B
D. Option C
E. Option D
Answer: B,D

NEW QUESTION: 4
CORRECT TEXT
Problem Scenario 34 : You have given a file named spark6/user.csv.
Data is given below:
user.csv
id,topic,hits
Rahul,scala,120
Nikita,spark,80
Mithun,spark,1
myself,cca175,180
Now write a Spark code in scala which will remove the header part and create RDD of values as below, for all rows. And also if id is myself" than filter out row.
Map(id -> om, topic -> scala, hits -> 120)
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create file in hdfs (We will do using Hue). However, you can first create in local filesystem and then upload it to hdfs.
Step 2 : Load user.csv file from hdfs and create PairRDDs val csv =
sc.textFile("spark6/user.csv")
Step 3 : split and clean data
val headerAndRows = csv.map(line => line.split(",").map(_.trim))
Step 4 : Get header row
val header = headerAndRows.first
Step 5 : Filter out header (We need to check if the first val matches the first header name) val data = headerAndRows.filter(_(0) != header(O))
Step 6 : Splits to map (header/value pairs)
val maps = data.map(splits => header.zip(splits).toMap)
step 7: Filter out the user "myself
val result = maps.filter(map => mapf'id") != "myself")
Step 8 : Save the output as a Text file. result.saveAsTextFile("spark6/result.txt")