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NEW QUESTION: 1
A. Option A
B. Option B
C. Option C
D. Option D
Answer: B
NEW QUESTION: 2
You plan to use Power Automate to perform data-management tasks when users interact with sales opportunities in Dynamics 365.
You need to identify the three types of events that can generate a trigger for the tasks.
Which three types of events should you identify? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. when a record is updated
B. when a record is displayed in a view
C. when a record is deleted
D. when a record is read
E. when a record is created
Answer: A,C,E
Explanation:
Explanation
Triggers like When a record is created, When a record is updated, and When a record is deleted initiate your flow within a few minutes of the event occurring. In rare cases, your flow can take up to 2 hours to trigger.
Reference:
https://docs.microsoft.com/en-us/power-automate/connection-dynamics365
NEW QUESTION: 3
A BSR candidate message is seen with a higher priority than the existing BSR. Which of the following describes the action that occurs?
A. There is a BSR configuration parameter that determines whether or not there is a BSR election in this case.
B. The higher priority router becomes the BSR immediately.
C. The higher priority router becomes the BSR only after the existing BSR fails.
D. The higher priority router becomes the BSR after the bootstrap message wait interval.
Answer: B
NEW QUESTION: 4
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
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create 2 files first using Hue in hdfs.
Step 2 : Load all file as an RDD
val technology = sc.textFile(Msparkl2/technology.txt").map(e => e.splitf',")) val salary = sc.textFile("spark12/salary.txt").map(e => e.split("."))
Step 3 : Now create Key.value pair of data and join them.
val joined = technology.map(e=>((e(0),e(1)),e(2))).join(salary.map(e=>((e(0),e(1)),e(2))))
Step 4 : Save the results in a text file as below.
joined.repartition(1).saveAsTextFile("spark12/multiColumn Joined.txt")