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Advanced CAMS-Audit Certification Exam
- Exam Number/Code : Advanced-CAMS-Audit
- Exam Name : Advanced CAMS-Audit Certification Exam
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- Update Time: 2019-01-10
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NEW QUESTION: 1
データウェアハウスとしてMicrosoft Azure SQLデータベースを使用します。データベースは標準サービス層にあり、400個のエラスティックデータベーススループットユニット(eDTU)を備えています。
Azure Data Factoryを使用してデータベースにデータを読み込みます。
データのロードにかかる時間を短縮する必要があります。
解決方法:125のDTUを持つPremiumデータベースプールにデータベースを移動します。
解決策は目標を満たしていますか?
A. いいえ
B. はい
Answer: A
Explanation:
We need at least 400 eDTUs.
NEW QUESTION: 2
---
You are installing a new VNX and need to implement a Storage Pool on the array. Disks are available and must be set up as follows:
18, 400 GB SSD in R5 (4+1) for the Extreme Performance tier
30, 600 GB 15K SAS R10 (4+4) for the Performance tier
52, 4 TB NL-SAS R6 (6+2) for the Capacity tier
Disks for Fast Cache, Vault, and unbound disks for sparing, are allocated separately.
How should you lay out the private RAID Groups in the Storage Pool?
A. Extreme Performance tier: 3 R5 (4+1) + 1 R5 (2+1)
Performance tier: 2 R10 (4+4) + 1 R10 (7+7)
Capacity tier: 6 R6 (6+2) + 1 R6 (2+2)
B. Extreme Performance tier: 2 R5 (4+1) + 1 R5 (7+1)
Performance tier: 3 R10 (4+4) + 1 R10 (3+3)
Capacity tier: 6 R6 (6+2) + 1 R6 (2+2)
C. Extreme Performance tier: 3 R5 (4+1) + 1 R5 (2+1)
Performance tier: 3 R10 (4+4) + 1 R10 (3+3)
Capacity tier: 6 R6 (6+2) + 1 R6 (2+2)
D. Extreme Performance tier: 3 R5 (4+1) + 1 R5 (2+1)
Performance tier: 3 R5 (8+1)
Capacity tier: 5 R6 (6+2) + 1 R6 (10+2)
Answer: C
NEW QUESTION: 3
ユーザーが3 GBサイズと90 IOPSのPIOPS EBSボリュームを作成しようとしています。 AWSはボリュームを作成しますか?
A. いいえ、PIOPSとEBSのサイズ比は30未満なので
B. はい、EBSとIOPSの比率が30未満であるため
C. いいえ、EBSサイズは4GB未満です
D. はい、PIOPSは100より大きいため
Answer: C
Explanation:
説明
プロビジョンドIOPS(SSD)ボリュームのサイズは4 GiBから16 TiBの範囲であり、ボリュームごとに最大20,000 IOPSをプロビジョニングできます。
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html#EBSVolumeTypes_piops
NEW QUESTION: 4
What metadata is stored on a DataNode when a block is written to it?
A. None. Only the block itself is written.
B. Checksums for the data in the block, as a separate file.
C. Node location of each block belonging to the same namespace.
D. Information on the file's location in HDFS.
Answer: C
Explanation:
Each DataNode keeps a small amount of metadata allowing it to identify the cluster it participates in. If this metadata is lost, then the DataNode cannot participate in an HDFS instance and the data blocks it stores cannot be reached.
When an HDFS instance is formatted, the NameNode generates a unique namespace id for the instance. When DataNodes first connect to the NameNode, they bind to this namespace id and establish a unique "storage id" that identifies that particular DataNode in the HDFS instance. This data as well as information about what version of Hadoop was used to create the block files, is stored in a filed named VERSION in the ${dfs.data.dir}/current directory.
Note:Administrators of HDFS clusters understand that the HDFS metadata is some of the most precious bits they have. While you might have hundreds of terabytes of information stored in HDFS, the NameNode's metadata is the key that allows this information, spread across several million "blocks" to be reassembled into coherent, ordered files.
Reference:Protecting per-DataNode Metadata