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NEW QUESTION: 1
Contoso.comという名前のAzure Active Directory（Azure AD）テナントとAzureサービス（AKS）クラスターAKS1があります。
Contoso.comのアカウントを使用してAKS1にアクセスできないことがわかりました。Contoso.comのアカウントを使用してAKS1にアクセスできることを確認する必要があります。このソリューションでは、管理作業を最小限に抑える必要があります。
最初に何をすべきですか？
A. AzureからAKS1を再作成します
B. Azure ADから、ユーザー設定を構成します
C. AKS1から、Kubermetesのバージョンをアップグレードします。
D. Azure ADから、Azure AD Premiumを実装します。
Answer: A
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/aks/azure-ad-integration-cli

NEW QUESTION: 2
Which statement is true about a SnapMirror destination Vserver?
A. It must have a read-only Vserver root volume.
B. It must be created with the same language type as the source Vserver.
C. It must have a different storage efficiency policy than the source Vserver.
D. It must be in the same cluster as the source Vserver.
Answer: B

NEW QUESTION: 3
You have a Skype for Business Server 2015 infrastructure that is configured for audio/video conferencing and
Enterprise Voice.
Users report that they cannot connect to audio conferences from a branch office. The branch office is secured and has
limited connectivity to other offices.
The users can connect to audio conferences from other offices.
You need to configure the port range used by Skype for Business clients for audio conferencing.
Which Skype for Business Management shell cmdlet should you run?
A. Set-CsConferencingConfiguration
B. Set-CsNetworkConfiguration
C. Set-CsMediaConfiguration
D. Set-CsExternalAccessPolicy
Answer: A
Explanation:
http://technet.microsoft.com/en-us/library/gg412969.aspx

NEW QUESTION: 4
What are the two advantages of using Hive over MapReduce? (Choose two.)
A. Hive allows for sophisticated analytics on large data sets.
B. Hive simplifies Hadoop for new users.
C. Hive does not require MapReduce to run in order to analyze data.
D. Hive is a free tool; Hadoop requires a license.
E. Hive is much faster than MapReduce because it accesses data directly.
Answer: A,B
Explanation:
E: A comparison of the performance of the Hadoop/Pig implementation of MapReduce with
Hadoop/Hive.
Both Hive and Pig are platforms optimized for analyzing large data sets and are built on top of Hadoop. Hive is a platform that provides a declarative SQLlike language whereas Pig requires users to write a procedural language called PigLatin.
Writing MapReduce jobs in Java can be difficult, Hive and Pig has been developed and works as platforms on top of Hadoop. Hive and Pig allows users easy access to data compared to implementing their own MapReduce in Hadoop.