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NEW QUESTION: 1
プロジェクト内にApp Engineアプリケーションを含むGoogle Cloud Platformプロジェクトを作成しました。最初に、アプリケーションをus-centralリージョンから提供されるように構成しました。次に、asia-northeast1リージョンからアプリケーションを提供したいとします。あなたは何をするべきか？
A. 既存のApp Engineアプリケーションのリージョンプロパティ設定をus-centralからasia-northeast1に変更します。
B. 既存のGCPプロジェクトに2つ目のApp Engineアプリケーションを作成し、アプリケーションを提供するリージョンとしてasia-northeast1を指定します。
C. 既存のGCPプロジェクトのデフォルトのリージョンプロパティ設定をasia-northeast1に変更します。
D. 新しいGCPプロジェクトを作成し、この新しいプロジェクト内にApp Engineアプリケーションを作成します。アプリケーションを提供するリージョンとしてasia-northeast1を指定します。
Answer: B

NEW QUESTION: 2

A. lpd
B. lpr
C. lpp
D. lpq
Answer: B

NEW QUESTION: 3
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")