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NEW QUESTION: 1
Which of the following is true about the generalization relationship?
A. It is a special form of aggregation
B. It is represented by a dashed arrow
C. It is often called inheritance
D. It is represented by a diamond symbol.
Answer: C

NEW QUESTION: 2
An administrator is using Amazon CloudFormation to deploy a three tier web application that consists of a web tier and application tier that will utilize Amazon DynamoDB for storage.
When creating the CloudFormation template which of the following would allow the application Instance access to the DynamoDB tables without exposing API credentials?
A. Use the Parameter section in the CloudFormation template to have the user input Access and Secret keys from an already created IAM user that has the permissions required to read and write from the required DynamoDB table.
B. Create an Identity and Access Management Role that has the required permissions to read and write from the .required DynamoDB table and associate the Role to the application instances by referencing an instance profile.
C. Create an Identity and Access Management user in the CloudFormation template that has permissions to read and write from the required DynamoDB table, use the GetAtt function to retrieve the Access and Secret keys and pass them to the application instance through user-data.
D. Create an Identity and Access Management Role that has the required permissions to read and write from the required DynamoDB table and reference the Role in the instance profile property of the application instance.
Answer: D

NEW QUESTION: 3
費用対効果の高い方法でデータを迅速に保存する必要があります。また、6か月以内に処理するデータ量がわからなくなり、処理が急増する可能性があります。どのビッグデータツールを使うべきですか？
正しい答えを選びなさい：
A. 機械学習
B. キネシス
C. EMR
D. 赤方偏移
Answer: C
Explanation:
With Amazon EMR, it is easy to resize a running cluster. You can add core nodes, which hold the Hadoop Distributed File System (HDFS), at any time to increase your processing power and increase the HDFS storage capacity (and throughput). Additionally, you can use Amazon S3 natively or using EMFS along with or instead of local HDFS, which allows you to decouple your memory and compute from your storage providing greater flexibility and cost efficiency. You can also add and remove task nodes at any time which can process Hadoop jobs but do not maintain HDFS. Some customers add hundreds of instances to their clusters when their batch processing occurs and remove the extra instances when processing completes. For example, you may not know how much data your clusters will be handling in 6 months, or you may have spikey processing needs. With Amazon EMR, you don't need to guess your future requirements or provision for peak demand because you can easily add or remove capacity at any time.
Reference:
https://d0.awsstatic.com/whitepapers/Big_Data_Analytics_Options_on_AWS.pdf