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NEW QUESTION: 1
A. Option A
B. Option C
C. Option D
D. Option B
Answer: A
NEW QUESTION: 2
You are evaluating whether to use a standard or an enhanced service level agreement (SLA).
You need to identify a characteristic of a standard SLA.
What should you identify?
A. The SLA can be paused-
B. The status can be tracked directly from the case form .
C. The failure time is tracked .
D. Actions can be triggered based on specific success catena .
Answer: C
NEW QUESTION: 3
ハードウェア障害時のリカバリ時間を短縮するため、サーバ管理者は互換性のあるハードウェアが使用可能な限り、完全なOSとサービス/アプリケーションのリカバリを可能にするバックアップ方法を実装する必要があります。 この要件を満たすバックアップタイプはどれですか？
A. フル
B. 増分
C. ベアメタル
D. スナップショット
Answer: C
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")