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NEW QUESTION: 1

A. Option C
B. Option B
C. Option A
D. Option D
Answer: C

NEW QUESTION: 2
Which of the following features can provide significant benefits in storage savings, performance of analytic workloads, and time to value?
A. Self tuning memory manager
B. auto reorg
C. BLU acceleration
D. pureScale
Answer: C
Explanation:
Explanation/Reference:
Reference: https://www.ibm.com/developerworks/data/library/techarticle/dm-1309db2bluaccel/index.html

NEW QUESTION: 3
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