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NEW QUESTION: 1
暖房、換気、および空調（HVAC）システムは、暖かい空気を____________に押し込むことにより、データセンターを冷却します。
A. 床下プレナム
B. サーバーインレット
C. 外の世界
D. HVACインテーク
Answer: C
NEW QUESTION: 2
A system administrator has deployed a Linux server based on an Anaconda process with all packages and custom configurations necessary to install a web server role.
Which of the following could be used to install more Linux servers with the same characteristics?
A. /etc/sysconfig/anaconda/cfg
B. /root/anaconda.auto
C. /root/anaconda-ks.cfg
D. /etc/sysconfig/installation.cfg
Answer: C
Explanation:
Reference:
https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/6/html/installation_guide/sn-automating-installation
NEW QUESTION: 3
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: 4
Answer:
Explanation:
Explanation
Box 1: retention
There are two ways to delete Storage Analytics data: by manually making deletion requests or by setting a data retention policy. Manual requests to delete Storage Analytics data are billable, but delete requests resulting from a retention policy are not billable.
To avoid unnecessary charges, set a retention policy for logging and metrics.
Note: By default, Storage Analytics will not delete any logging or metrics data. Blobs and table entities will continue to be written until the shared 20TB limit is reached. Once the 20TB limit is reached, Storage Analytics will stop writing new data and will not resume until free space is available.
Box 2: 365
You can configure two data retention policies: one for logging and one for metrics. When enabled for both, Storage Analytics will delete logs and table entries older than the specified number of days. The maximum retention period is 365 days (1 year).
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/Setting-a-Storage-Analytics-Data-Retention-Policy
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