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NEW QUESTION: 1
HOTSPOT
You administer Windows 10 Enterprise computers in your company network, including a computer named Wst1. Wst1 is configured with multiple shared printer queues.
Wst1 indicates hardware errors. You decide to migrate the printer queues from Wst1 to a new computer named Client1.
You export the printers on Wst1 to a file. You need to import printers from the file to Client1.
From the Print Management console, which Print Management node should you select? To answer, select the appropriate node in the answer area.
Answer:
Explanation:
Explanation:
We have exported the printers on Wst1 to a file. To import printers from the file to Client1, we use the Printer Migration Wizard.
Right-click Print Management, and then click Migrate Printers to open the Printer Migration Wizard. Select Import printer queues and printer drivers from a file, and select the export file. Then complete the wizard.
References: http://blogs.technet.com/b/canitpro/archive/2013/06/17/step-by-step-install- use-and-remove-windows-server-migration-tools.aspx
NEW QUESTION: 2
You develop data engineering solutions for a company.
A project requires an in-memory batch data processing solution.
You need to provision an HDInsight cluster for batch processing of data on Microsoft Azure.
How should you complete the PowerShell segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
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
会社の75,000人の従業員に関するデータがあります。 データには、次の表に示すプロパティが含まれます。
Azure Cosmos DBコンテナーに従業員データを保存する必要があります。 データに対するほとんどのクエリは、Current DepartmentプロパティとEmployee Surnameプロパティでフィルタリングされます。
コンテナにはどのパーティションキーとアイテムID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:
Partition key: Current Department
Item ID: Employee ID
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/designing-a-scalable-partitioning-strategy-for-azure-tab