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NEW QUESTION: 1
부서는 회사의 로그 파일에서 정기적 인 분석 보고서를 생성합니다. 모든 로그 데이터는 Amazon S3에서 수집되어 Amazon Redshift 데이터웨어 하우스에 대해 매일 PDF 보고서와 CSV 형식으로 집계 된 테이블을 생성하는 매일 Amazon Elastic MapReduce (EMR) 작업으로 처리됩니다.
CFO는이 시스템의 비용 구조를 최적화하도록 요청합니다.
다음 대안 중 어느 것이 시스템의 평균 성능이나 원시 데이터의 데이터 무결성을 손상시키지 않으면 서 비용을 절감 할 수 있습니까?
A. Amazon S3에서는 PDF 및 .csv 데이터에 대해 중복 중복 저장소 (RRS)를 사용합니다. 스팟 인스턴스를 Amazon EMR 작업에 추가하십시오. Amazon Redshift에 예약 인스턴스를 사용하십시오.
B. S3에서 PDF 및 .csv 데이터에 대해 중복 중복 저장소 (RRS)를 사용하십시오. 스팟 인스턴스를 EMR 작업에 추가하십시오.
Amazon Redshift에 스팟 인스턴스를 사용하십시오.
C. S3의 모든 데이터에 대해 중복 중복 저장소 (RRS)를 사용하십시오. Amazon EMR 작업에 스팟 인스턴스와 예약 인스턴스를 함께 사용하십시오. Amazon Redshift에 예약 인스턴스를 사용하십시오.
D. Amazon S3의 모든 데이터에 대해 중복 중복 스토리지 (RRS)를 사용하십시오. 스팟 인스턴스를 Amazon EMR 작업에 추가하십시오. Amazon Redshift에 예약 인스턴스를 사용하십시오.
Answer: A
Explanation:
설명
Using Reduced Redundancy Storage Amazon S3 stores objects according to their storage class. It assigns the storage class to an object when it is written to Amazon S3. You can assign objects a specific storage class (standard or reduced redundancy) only when you write the objects to an Amazon S3 bucket or when you copy objects that are already stored in Amazon S3. Standard is the default storage class. For information about storage classes, see Object Key and Metadata.
In order to reduce storage costs, you can use reduced redundancy storage for noncritical, reproducible data at lower levels of redundancy than Amazon S3 provides with standard storage. The lower level of redundancy results in less durability and availability, but in many cases, the lower costs can make reduced redundancy storage an acceptable storage solution. For example, it can be a cost-effective solution for sharing media content that is durably stored elsewhere. It can also make sense if you are storing thumbnails and other resized images that can be easily reproduced from an original image.
Reduced redundancy storage is designed to provide 99.99% durability of objects over a given year. This durability level corresponds to an average annual expected loss of 0.01% of objects. For example, if you store
10,000 objects using the RRS option, you can, on average, expect to incur an annual loss of a single object per year (0.01% of 10,000 objects).
Note:
This annual loss represents an expected average and does not guarantee the loss of less than 0.01% of objects in a given year.
Reduced redundancy storage stores objects on multiple devices across multiple facilities, providing 400 times the durability of a typical disk drive, but it does not replicate objects as many times as Amazon S3 standard storage. In addition, reduced redundancy storage is designed to sustain the loss of data in a single facility.
If an object in reduced redundancy storage has been lost, Amazon S3 will return a 405 error on requests made to that object. Amazon S3 also offers notifications for reduced redundancy storage object loss: you can configure your bucket so that when Amazon S3 detects the loss of an RRS object, a notification will be sent through Amazon Simple Notification Service (Amazon SNS). You can then replace the lost object. To enable notifications, you can use the Amazon S3 console to set the Notifications property of your bucket.

NEW QUESTION: 2
You have an Azure Kubernetes cluster in place.
You have to deploy an application using an Azure Container registry image.
Which of the following command can be used for this requirement?
A. az kubernetes deploy
B. kubectl apply
C. docker run
D. New-AzKubernetes set
Answer: B
Explanation:
Explanation
kubectl apply : Correct Choice
The kubectl command can be used to deploy applications to a Kubernetes cluster.
az kubernetes deploy : Incorrect Choice
This command is used to manage Azure Kubernetes Services. This is not used to deploy applications to a Kubernetes cluster.
New-AzKubernetes set : Incorrect Choice
This command is used to create a new managed Kubernetes cluster. This is not used to deploy applications to a Kubernetes cluster.
docker run : Incorrect Choice
This is run command in a new container. This is not used to deploy applications to a Kubernetes cluster.
Reference:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#apply
https://docs.microsoft.com/en-us/cli/azure/aks?view=azure-cli-latest
https://docs.microsoft.com/en-us/powershell/module/az.aks/New-AzAks?view=azps-3.8.0&viewFallbackFrom=
https://docs.docker.com/engine/reference/commandline/run/

NEW QUESTION: 3
You have a Python data frame named salesData in the following format:
The data frame must be unpivoted to a long data format as follows:
You need to use the pandas.melt() function in Python to perform the transformation.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: dataFrame
Syntax: pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None)[source] Where frame is a DataFrame Box 2: shop Paramter id_vars id_vars : tuple, list, or ndarray, optional Column(s) to use as identifier variables.
Box 3: ['2017','2018']
value_vars : tuple, list, or ndarray, optional
Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.
Example:
df = pd.DataFrame({'A': {0: 'a', 1: 'b', 2: 'c'},
'B': {0: 1, 1: 3, 2: 5},
'C': {0: 2, 1: 4, 2: 6}})
pd.melt(df, id_vars=['A'], value_vars=['B', 'C'])
A variable value
0 a B 1
1 b B 3
2 c B 5
3 a C 2
4 b C 4
5 c C 6
References:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html

NEW QUESTION: 4
What effect does the following command have on TCP packets?
iptables- A INPUT -d 10.142.232.1 -p tcp --dport 20:21 -j ACCEPT
A. Drop all TCP traffic coming from 10.142.232.1 destined for port 20 or 21.
B. Forward all TCP traffic not on port 20 or 21 to the IP address 10.142.232.1
C. Accept only TCP traffic from 10.142.232.1 destined for port 20 or 21.
D. Accept all TCP traffic on port 20 and 21 for the IP address 10.142.232.1
Answer: C
Explanation:
Explanation/Reference:
https://help.ubuntu.com/community/IptablesHowTo

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