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NEW QUESTION: 1
Welche davon liegt NICHT in der Verantwortung des Anwendungsmanagements?
A. Entscheiden, ob eine Anwendung gekauft oder erstellt werden soll
B. Sicherstellen, dass die richtigen Fähigkeiten zur Verwaltung der Infrastruktur verfügbar sind
C. Anleitung für den IT-Betrieb zur optimalen Verwaltung der Anwendung
D. Unterstützung bei der Gestaltung der Anwendung
Answer: B
NEW QUESTION: 2
Hinweis: Diese Frage ist Teil einer Reihe von Fragen, die dasselbe Szenario darstellen. Jede Frage in der Reihe enthält eine eindeutige Lösung, mit der die angegebenen Ziele erreicht werden können. Einige Fragensätze haben möglicherweise mehr als eine richtige Lösung, während andere möglicherweise keine richtige Lösung haben.
Nachdem Sie eine Frage in diesem Abschnitt beantwortet haben, können Sie NICHT mehr darauf zurückkommen. Infolgedessen werden diese Fragen nicht im Überprüfungsbildschirm angezeigt.
Sie müssen sicherstellen, dass die SecurityPin-Sicherheitsanforderungen erfüllt sind.
Lösung: Aktivieren Sie Immer verschlüsselt für die SecurityPin-Spalte mithilfe eines in Azure Key Vault enthaltenen Zertifikats und gewähren Sie dem WebAppldentity-Dienstprinzipal Zugriff auf das Zertifikat.
Entspricht die Lösung dem Ziel?
A. Ja
B. Nein
Answer: A
Explanation:
Erläuterung
Szenario: Der SecurityPin des Benutzers muss so gespeichert werden, dass beim Zugriff auf die Datenbank keine SecurityPins angezeigt werden können. Die Webanwendung ist das einzige System, das Zugriff auf SecurityPins haben sollte.
NEW QUESTION: 3
CORRECT TEXT
Problem Scenario 31 : You have given following two files
1 . Content.txt: Contain a huge text file containing space separated words.
2 . Remove.txt: Ignore/filter all the words given in this file (Comma Separated).
Write a Spark program which reads the Content.txt file and load as an RDD, remove all the words from a broadcast variables (which is loaded as an RDD of words from Remove.txt).
And count the occurrence of the each word and save it as a text file in HDFS.
Content.txt
Hello this is ABCTech.com
This is TechABY.com
Apache Spark Training
This is Spark Learning Session
Spark is faster than MapReduce
Remove.txt
Hello, is, this, the
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create all three files in hdfs in directory called spark2 (We will do using Hue).
However, you can first create in local filesystem and then upload it to hdfs
Step 2 : Load the Content.txt file
val content = sc.textFile("spark2/Content.txt") //Load the text file
Step 3 : Load the Remove.txt file
val remove = sc.textFile("spark2/Remove.txt") //Load the text file
Step 4 : Create an RDD from remove, However, there is a possibility each word could have trailing spaces, remove those whitespaces as well. We have used two functions here flatMap, map and trim.
val removeRDD= remove.flatMap(x=> x.splitf',") ).map(word=>word.trim)//Create an array of words
Step 5 : Broadcast the variable, which you want to ignore
val bRemove = sc.broadcast(removeRDD.collect().toList) // It should be array of Strings
Step 6 : Split the content RDD, so we can have Array of String. val words = content.flatMap(line => line.split(" "))
Step 7 : Filter the RDD, so it can have only content which are not present in "Broadcast
Variable". val filtered = words.filter{case (word) => !bRemove.value.contains(word)}
Step 8 : Create a PairRDD, so we can have (word,1) tuple or PairRDD. val pairRDD = filtered.map(word => (word,1))
Step 9 : Nowdo the word count on PairRDD. val wordCount = pairRDD.reduceByKey(_ + _)
Step 10 : Save the output as a Text file.
wordCount.saveAsTextFile("spark2/result.txt")
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