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NEW QUESTION: 1
Shawn is the project manager of the WHT Project for his company. In this project Shawn's team reports that they have found a way to complete the project work for less cost than
what was originally planned. The project team presents a new software that will help to automate the project work. While the software and the associated training costs $25,000 it will save the project nearly $65,000 in total costs. Shawn agrees to the software and changes to the project management plan accordingly. What type of risk response has been used in this instance?
A. Enhancing
B. Accepting
C. Avoidance
D. Exploiting
Answer: D

NEW QUESTION: 2
An architect wants to create a composite blueprint with nested components but cannot see the needed component in the blueprints list of the design canvas.
What is a possible reason for this issue?
A. The nested blueprint does not have the _deploymentName custom property set.
B. The nested blueprint is an XaaS blueprint.
C. The nested blueprint is not published.
D. The nested blueprint is not part of an entitlement.
Answer: A

NEW QUESTION: 3
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")