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NEW QUESTION: 1
Die Grafik hat ein Problem beim Drucken bestimmter Dateien. Der Drucker druckt nicht das gesamte Bild auf größeren Dateien. Ein Techniker überprüft, ob die Netzwerkgeschwindigkeit des Druckers auf 1 GB eingestellt ist und ob normale Textdateien ohne Probleme gedruckt werden. Welche der folgenden Ursachen ist am wahrscheinlichsten für dieses Problem?
A. Der Drucker benötigt mehr RAM
B. Die Benutzer drucken nicht im Post-Script-Modus
C. Die Druckernetzwerkverbindung ist auf Halbduplex eingestellt
D. Der Druckserver läuft ab
Answer: A
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
システムには、commonという名前でVGSRVボリュームグループに属するローカル論理ボリュームがあり、/ commonディレクトリにマウントされます。サイズの定義は128 MBです。
要件：
データを失うことなく、論理ボリュームを190 MBに拡張します。サイズは、拡張後に160〜160 MBの間で許可されます。
Answer:
Explanation:
see explanation below.
Explanation
lvextend -L 190M /dev/mapper/vgsrv-common resize2fs /dev/mapper/vgsrv-common
NEW QUESTION: 4
A. Option A
B. Option D
C. Option C
D. Option B
Answer: A