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NEW QUESTION: 1
Ihr Netzwerk enthält eine Active Directory-Domäne mit dem Namen contoso.com.
Die Domäne enthält einen Computer mit dem Namen Computer1, auf dem Windows 10 ausgeführt wird.
Das Netzwerk verwendet den Adressraum 172.16.0.0/16.
Computer1 verfügt über eine Anwendung mit dem Namen App1.exe, die sich in D: \\ Apps \\ befindet.
App1.exe ist so konfiguriert, dass Verbindungen über TCP-Port 8080 akzeptiert werden.
Sie müssen sicherstellen, dass App1.exe nur Verbindungen akzeptiert, wenn Computer1 mit dem Unternehmensnetzwerk verbunden ist.
Lösung: Sie führen New-NetFirewallRule -DisplayName "Rule1" -Direction Inbound -LocalPort 8080 aus
-Protocol TCP -Action -Profil Domain-Befehl zulassen.
Erfüllt dies das Ziel?
A. Nein
B. Ja
Answer: A

NEW QUESTION: 2
Microsoft AzureでLambdaアーキテクチャを使用してソリューションを開発しています。
テストレイヤーのデータは、次の要件を満たしている必要があります。
データストレージ：
*リポジトリ（またはさまざまな形式の大量の大容量ファイル）として機能します。
*ビッグデータ分析ワークロード用に最適化されたストレージを実装します。
*階層構造を使用してデータを整理できるようにします。
バッチ処理：
*メモリ内の計算処理にはマネージドソリューションを使用します。
* Scala、Python、およびRプログラミング言語をネイティブにサポートします。
*クラスターを自動的にサイズ変更および終了する機能を提供します。
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
Lambdaアーキテクチャを構築するには、正しいテクノロジーを特定する必要があります。
どのテクノロジー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:

Explanation

Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
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
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is

NEW QUESTION: 3
A Solutions Architect has been asked to look at a company's Amazon Redshift cluster, which has quickly become an integral part of its technology and supports key business process. The Solutions Architect is to increase the reliability and availability of the cluster and provide options to ensure that if an issue arises, the cluster can either operate or be restored within four hours.
Which of the following solution options BEST addresses the business need in the most cost- effective manner?
A. Create two identical Amazon Redshift clusters in different regions (one as the primary, one as the secondary). Use Amazon S3 cross-region replication from the primary to secondary). Use Amazon S3 cross-region replication from the primary to secondary region, which triggers an AWS Lambda function to populate the cluster in the secondary region.
B. Use Amazon Kinesis Data Firehose to collect the data ahead of ingestion into Amazon Redshift and create clusters using AWS CloudFormation in another region and stream the data to both clusters.
C. Ensure that the Amazon Redshift cluster has been set up to make use of Auto Scaling groups with the nodes in the cluster spread across multiple Availability Zones.
D. Ensure that the Amazon Redshift cluster creation has been template using AWS CloudFormation so it can easily be launched in another Availability Zone and data populated from the automated Redshift back-ups stored in Amazon S3.
Answer: D
Explanation:
https://aws.amazon.com/redshift/faqs/?nc1=h_ls
Q: What happens to my data warehouse cluster availability and data durability if my data warehouse cluster's Availability Zone (AZ) has an outage?
If your Amazon Redshift data warehouse cluster's Availability Zone becomes unavailable, you will not be able to use your cluster until power and network access to the AZ are restored. Your data warehouse cluster's data is preserved so you can start using your Amazon Redshift data warehouse as soon as the AZ becomes available again. In addition, you can also choose to restore any existing snapshots to a new AZ in the same Region. Amazon Redshift will restore your most frequently accessed data first so you can resume queries as quickly as possible.