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NEW QUESTION: 1
CORRECT TEXT
Problem Scenario 59 : You have been given below code snippet.
val x = sc.parallelize(1 to 20)
val y = sc.parallelize(10 to 30) operationl
z.collect
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[lnt] = Array(16,12, 20,13,17,14,18,10,19,15,11)
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
val z = x.intersection(y)
intersection : Returns the elements in the two RDDs which are the same.
NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question
in the series contains a unique solution that might meet the stated goals. Some question sets
might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these
questions will not appear in the review screen.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about
customers in a table. Each record uses a value for CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID.
Proposed Solution: Separate data into customer regions by using horizontal partitioning.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation/Reference:
Explanation:
We should use Horizontal Partitioning through Sharding, not divide through regions.
Note: Horizontal Partitioning - Sharding: Data is partitioned horizontally to distribute rows across a scaled
out data tier. With this approach, the schema is identical on all participating databases. This approach is
also called "sharding". Sharding can be performed and managed using (1) the elastic database tools
libraries or (2) self-sharding. An elastic query is used to query or compile reports across many shards.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview
NEW QUESTION: 3
Sie haben die folgenden Unterabfragen: Unterabfrage1, Unterabfrage2 und Unterabfrage3.
Sie müssen die drei Unterabfragen durch benannte Ergebnismengen oder temporäre Tabellen ersetzen. Folgende Voraussetzungen müssen erfüllt sein:
Welche Ersatztechniken sollten Sie anwenden? Wählen Sie zum Beantworten die entsprechenden Optionen im Antwortbereich aus.
Answer:
Explanation:
Erläuterung
Unterabfrage1: Common Table Expression (CTE)
Ein allgemeiner Tabellenausdruck (CTE) kann als temporäre Ergebnismenge betrachtet werden, die im Ausführungsbereich einer einzelnen SELECT-, INSERT-, UPDATE-, DELETE- oder CREATE VIEW-Anweisung definiert ist. Ein CTE ähnelt einer abgeleiteten Tabelle, da es nicht als Objekt gespeichert wird und nur für die Dauer der Abfrage gültig ist. Im Gegensatz zu einer abgeleiteten Tabelle kann ein CTE selbstreferenzierend sein und in derselben Abfrage mehrfach referenziert werden.
Unterabfrage2: globale temporäre Tabelle
Globale temporäre Tabellen sind für jeden Benutzer und jede Verbindung sichtbar, nachdem sie erstellt wurden. Sie werden gelöscht, wenn alle Benutzer, die auf die Tabelle verweisen, die Verbindung zur SQL Server-Instanz trennen.
Unterabfrage3: lokale temporäre Tabelle
Lokale temporäre Tabellen sind nur für ihre Ersteller während derselben Verbindung zu einer Instanz von SQL Server sichtbar, als die Tabellen zum ersten Mal erstellt wurden oder auf die verwiesen wurde. Lokale temporäre Tabellen werden gelöscht, nachdem der Benutzer die Verbindung zur SQL Server-Instanz getrennt hat.
Verweise:
https://technet.microsoft.com/en-us/library/ms190766(v=sql.105).aspx
https://technet.microsoft.com/en-us/library/ms186986.aspx