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NEW QUESTION: 1
Contoso、Ltd。という名前の会社には、contoso.comという名前のドメインを使用するMicrosoft ExchangeOnlineサブスクリプションがあります。
Contosoは、A.DatumCorporationという名前のパートナー企業と協力しています。 A.Datumには、adatum.comという名前のドメインを使用するExchange Server2016組織があります。
ContosoのユーザーがA.Datumのユーザーと空き時間情報を共有できるようにする必要があります。
あなたはそれぞれの会社のために何をすべきですか？回答するには、回答領域で適切なオプションを選択します。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

References:
https://docs.microsoft.com/en-us/exchange/sharing/organization-relationships/organization-relationships

NEW QUESTION: 2
会社のデータエンジニアリングソリューションを開発します。
プロジェクトには、メモリ内のバッチデータ処理ソリューションが必要です。
Microsoft Azureでデータをバッチ処理するためにHDInsightクラスターをプロビジョニングする必要があります。
PowerShellセグメントをどのように完成させ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

Box 1: New-AzStorageContainer
# Example: Create a blob container. This holds the default data store for the cluster.
New-AzStorageContainer `
-Name $clusterName `
-Context $defaultStorageContext
$sparkConfig = New-Object "System.Collections.Generic.Dictionary``2[System.String,System.String]"
$sparkConfig.Add("spark", "2.3")
Box 2: Spark
Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications than disk-based applications, such as Hadoop, which shares data through Hadoop distributed file system (HDFS).
Box 3: New-AzureRMHDInsightCluster
# Create the HDInsight cluster. Example:
New-AzHDInsightCluster `
-ResourceGroupName $resourceGroupName `
-ClusterName $clusterName `
-Location $location `
-ClusterSizeInNodes $clusterSizeInNodes `
-ClusterType $"Spark" `
-OSType "Linux" `
Box 4: Spark
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-jupyter-spark-sql-use-powershell
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-overview

NEW QUESTION: 3
Locating datacenters close to target markets is the result of which of the following strategic initiatives?
A. Geography
B. Geoproximity
C. Geodiversity
D. Localization
Answer: B
Explanation:
Azure allows specification of geographical regions or affinity groups. Geographical regions are related to the
data centers, like North Central US, South Central US, Anywhere US, East Asia, North Europe, and so on.
The list of options will grow as more data centers are added.
Instead of selecting a region, it is possible to specify an affinity group. Affinity groups are hints to Azure
that essentially state that everything within the group should be as close in proximity as Azure will allow.
That usually means keeping items within the same data center, which besides having the benefit of geo-
location, can sometimes offer performance improvements for communication.
References: http://greglevenhagen.com/azure-geographical-location-restriction/