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Exam Code: Associate-Developer-Apache-Spark-3.5 Dumps

Questions and Answers: 104

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NEW QUESTION: 1
注:この質問は、同じまたは類似の回答の選択肢を使用する一連の質問の一部です。 回答の選択肢は、シリーズの複数の質問に対して正しいかもしれません。 各質問は、このシリーズの他の質問とは独立しています。 質問で提供される情報と詳細は、その質問にのみ適用されます。
Windows Server 2016を実行するServer1という名前のHyper-Vホストと、Cluster1という名前の2ノードスケールアウトファイルサーバークラスタがあります。
VM1という名前の仮想マシンがServer1上で実行されます。
VM1上のストレージをCluster1に移行する必要があります。
どのツールを使用しますか?
A. the Failover Cluster Manager snap-in
B. the Hyper-V Manager snap-in
C. the Computer Management snap-in
D. the configurehyperv.exe command
E. the Disk Management snap-in
F. the Server Manager app
G. the cluster.exe command
H. the clussvc.exe command
Answer: B

NEW QUESTION: 2
Which storage would you use if your big data workload requires shared access and an NFS based interface?
A. Storage Software Cloud Appliance
B. Block Volume
C. Object Storage
D. File Storage
E. Archive Storage
Answer: D
Explanation:
Explanation
References: https://docs.cloud.oracle.com/iaas/Content/File/Concepts/filestorageoverview.htm The File Storage service is designed to meet the needs of applications and users that need an enterprise file system across a wide range of use cases, including the following:
General Purpose File Storage: Access to an unlimited pool of file systems to manage growth of structured and unstructured data.
Big Data and Analytics: Run analytic workloads and use to store persistent data.
Lift and Shift of Enterprise Applications: Migrate existing Oracle applications that need NFS storage, such as Oracle E-Business Suite and PeopleSoft.
Databases and Transactional Applications: Run test and development workloads with Oracle, MySQL, or other databases.
Backups, Business Continuity, and Disaster Recovery: Host a secondary copy of relevant file systems from on premises to the cloud for backup and disaster recovery purposes.
MicroServices and Docker: Deliver stateful persistence for containers. Easily scale as your container-based environments grow.

NEW QUESTION: 3
HOTSPOT
A company uses Azure to host virtual machines (VMs) and web apps.
Storage Analytics data for the web apps must be kept as long as possible. The solution must not result in additional costs.
You need to configure a storage policy for the analytics data.
How should you configure the policy? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
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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