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NEW QUESTION: 1
Company X has a primary and a backup Cisco Unified Communications Manager instance.
The administrator had to do maintenance on the primary node and did a shutdown, which resulted in a failover to the backup node.
What happens when the primary node comes back online?
A. The primary node becomes the backup node.
B. Nothing, the endpoints only failover when the node they lose connection to their registered node.
C. The backup node must be shut down first to allow the endpoints to realize that the primary node is online again.
D. Endpoints detect that the primary is back and reregisters automatically.
Answer: D
NEW QUESTION: 2
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
企業は、Azure Data Lake Gen 1ストレージを使用して、消費者の行動に関連するビッグデータを保存します。
ロギングを実装する必要があります。
解決策：Azure Data Late Storage診断を構成して、ストレージアカウントにログとメトリックを保存します。
ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
From the Azure Storage account that contains log data, open the Azure Storage account blade associated with Data Lake Storage Gen1 for logging, and then click Blobs. The Blob service blade lists two containers.
References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-diagnostic-logs
NEW QUESTION: 3
You need to develop a pipeline for processing dat
a. The pipeline must meet the following requirements.
* Scale up and down resources for cost reduction.
* Use an in-memory data processing engine to speed up ETL and machine learning operations.
* Use streaming capabilities.
* Provide the ability to code in SQL, Python, Scala, and R.
* Integrate workspace collaboration with Git.
What should you use?
A. HDInsight Hadoop Cluster
B. HDInsight Spark Cluster
C. Azure Stream Analytics
D. Azure SQL Data Warehouse
Answer: B
Explanation:
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
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.
Languages: R, Python, Java, Scala, SQL
You can create an HDInsight Spark cluster using an Azure Resource Manager template. The template can be found in GitHub.
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing