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NEW QUESTION: 1
開発者は、サーバーレスのRESTfulAPIをAWSに繰り返し一貫してデプロイする必要があります。
どのテクニックが機能しますか？ （2つ選択してください。）
A. インラインSwagger定義を使用してSAMテンプレートをデプロイします。
B. Lambda関数でインラインSwagger定義を定義します。 Lambda関数を呼び出します。
C. Swaggerファイルを定義します。 AWS CodeDeployを使用して、Swaggerファイルをデプロイします。
D. Swaggerファイルを定義します。 Swaggerファイルを参照するSAMテンプレートをデプロイします。
E. Swaggerファイルを定義します。 AWS Elastic Beanstalkを使用して、Swaggerファイルをデプロイします。
Answer: A,D
Explanation:
Explanation
https://aws.amazon.com/about-aws/whats-new/2017/02/aws-serverless-application-model-aws-sam-supports-inli
https://aws.amazon.com/about-aws/whats-new/2017/02/aws-serverless-application-model-aws-sam-supports-inli
NEW QUESTION: 2
Click the Exhibit button. Given the information shown in the exhibit, what was used to determine mastership?
A. member uptime
B. highest serial number
C. manually assigned role
D. manually assigned priority
Answer: A
Explanation:
Explanation
When a Virtual Chassis configuration boots, the Juniper Networks Junos operating system (Junos OS) on the switches automatically runs a master election algorithm to determine which member switch assumes the role of master. The algorithm proceeds from the top condition downward until the stated condition is satisfied.
NEW QUESTION: 3
In the Huawei desktop cloud, after the iCache function is enabled, which of the following statements is incorrect?
A. Can ease to start storm
B. iCache can improve the read IO performance of the desktop
C. Need to modify the domain0 specification
D. You can specify that some data exists in iCache.
Answer: D
NEW QUESTION: 4
Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Each file would be split into two as the block size (64 MB) is less than the file size
(100 MB), so 200 mappers would be running.
Note:
If you're not compressing the files then hadoop will process your large files (say 10G), with a
number of mappers related to the block size of the file.
Say your block size is 64M, then you will have ~160 mappers processing this 10G file (160*64 ~=
10G). Depending on how CPU intensive your mapper logic is, this might be an
acceptable blocks size, but if you find that your mappers are executing in sub minute times, then
you might want to increase the work done by each mapper (by increasing the block size to 128,
256, 512m - the actual size depends on how you intend to process the data).
Reference: http://stackoverflow.com/questions/11014493/hadoop-mapreduce-appropriate-input-
files-size (first answer, second paragraph)