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NEW QUESTION: 1
Lisa has already created the IBM Connections 4.0 databases. Which statement is true about populating the Profiles database?
A. The populate_from_dn_file.[bat/sh] automatically invokes collect_dns.[bat/sh]. There is no need to manually run collect_dns.[bat/sh].
B. The collect_dns.[bat/sh] is really not required for Profiles database population. It is a troubleshooting tool used when errors are encountered during population.
C. The collect_dns.[bat/sh] process collects the DNS host names of all the LDAP directory servers and passes this information on to the populate_from_dn_file.[bat/sh] for Profiles database population.
D. The collect_dns.[bat/sh] process collects all the distinguished names from the source LDAP server into the collect.dns file and the populate_from_dn_file.[bat/sh] populates the Profiles database.
Answer: D
NEW QUESTION: 2
エンジニアは、セッションサービスを実行しているCisco ISEノードにパケットを送信するようにNADがすでに設定されていることを発見しました。どのプローブプロファイルに最も単純な設定が必要ですか。
A. RADIUS
B. NMAP
C. SPAN
D. HTTP
E. DHCP
Answer: A
NEW QUESTION: 3
Microsoft Azureで新しいLambdaアーキテクチャを設計しています。
リアルタイム処理レイヤーは、次の要件を満たしている必要があります。
摂取：
1秒あたり数百万のイベントを受信する
完全に管理されたPlatform-as-a-Service（PaaS）ソリューションとして機能する
Azure Functionsと統合する
ストリーム処理：
ジョブごとに処理する
Azureサービスとのシームレスな接続を提供する
SQLベースのクエリ言語を使用する
分析データストア：
マネージドサービスとして機能する
ドキュメントストアを使用する
保管中のデータ暗号化を提供する
最小限の労力でLambdaアーキテクチャを構築するには、正しいテクノロジーを特定する必要があります。どのテクノロジーを使用す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:
ボックス1：Azure Event Hubs
ストリーミングアーキテクチャのこの部分は、多くの場合、ストリームバッファリングと呼ばれます。オプションには、Azure Event Hubs、Azure IoT Hub、Kafkaが含まれます。
不正解：HDInsight Kafkaではありません
Azure Functionsを実行するには、トリガーを定義する必要があります。サポートされているトリガータイプのセットは限られていますが、Kafkaはそれらの1つではありません。
ボックス2：Azure Stream Analytics
Azure Stream Analyticsは、無制限のストリームで動作する永続的に実行されるSQLクエリに基づくマネージドストリーム処理サービスを提供します。
HDInsightクラスターでは、StormやSpark StreamingなどのオープンソースApacheストリーミングテクノロジーを使用することもできます。
ボックス3：Azure SQL Data Warehouse
Azure SQL Data Warehouseは、大規模なクラウドベースのデータウェアハウジング向けのマネージドサービスを提供します。 HDInsightは、Interactive Hive、HBase、およびSpark SQLをサポートしています。これらは、分析用のデータの提供にも使用できます。
参照：
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/