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NEW QUESTION: 1
デバイスが指定された場所から200メートル以上移動したときにユーザーに警告するリアルタイム監視アプリを作成する予定です。
計画したアプリのデータを処理するには、Azure Stream Analyticsジョブを設計する必要があります。 このソリューションでは、開発するコードの量と使用するテクノロジーの数を最小限に抑える必要があります。
Stream Analyticsジョブには何を含める必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Input type: Stream
You can process real-time IoT data streams with Azure Stream Analytics.
Input source: Azure IoT Hub
In a real-world scenario, you could have hundreds of these sensors generating events as a stream. Ideally, a gateway device would run code to push these events to Azure Event Hubs or Azure IoT Hubs.
Function: Geospatial
With built-in geospatial functions, you can use Azure Stream Analytics to build applications for scenarios such as fleet management, ride sharing, connected cars, and asset tracking.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios

NEW QUESTION: 2
You create a materialized reference dimension between a dimension named Regions and a measure group named Orders.
You use a table named Customers as a bridge as shown in the exhibit. (Click the Exhibit button.)

You need to ensure that data is updated to reflect any changes in the relationship. The solution must NOT require that the entire cube be reprocessed.
What should you reprocess?
A. The Customers dimension
B. The Orders partition
C. The Sales partition
D. The Regions dimension
Answer: A

NEW QUESTION: 3
DNSの「盲点」と見なされるステートメントは次のうちどれですか？
A. ルートレベルのDNSサーバーがDDos攻撃を受けている場合、DNSブラインドスポットが作成されます。
B. DNSブラインドスポットは、発信要求のCX DNSレコードを変更できないこととして定義されます。
C. DNSブラインドスポットは、UDPポート53のDoSポートスキャンの直接的な結果です。
D. 盲点とは、セキュリティ上の目的でDNSアクティビティを適切に監視できないことです。
E. ブラインドスポットは、DNS BINDサーバーへの適切なソフトウェアパッチの不適切または不足が原因です。
Answer: D

NEW QUESTION: 4


Test.java


A. Option C
B. Option E
C. Option B
D. Option D
E. Option A
Answer: B