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>> Professional-Data-Engineer최고품질 덤프문제모음집 <<
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Google Certified Professional Data Engineer 자격증을 취득하면 구글 클라우드 플랫폼에서 데이터 처리 시스템을 설계하고 구축하는 데 필요한 지식과 기술을 보유한 개인임을 고용주와 동료에게 증명할 수 있습니다. 이 자격증은 새로운 직업 기회를 열어주며 개인이 현재 직무에서 승진하는 데도 도움이 될 수 있습니다.
질문 # 23
Your organization has two Google Cloud projects, project A and project B. In project A, you have a Pub/Sub topic that receives data from confidential sources. Only the resources in project A should be able to access the data in that topic. You want to ensure that project B and any future project cannot access data in the project A topic. What should you do?
정답:B
설명:
Identity and Access Management (IAM) is the recommended way to control access to Pub/Sub resources, such as topics and subscriptions. IAM allows you to grant roles and permissions to users and service accounts at the project level or the individual resource level. You can also use IAM conditions to specify additional attributes for granting or denying access, such as time, date, or origin. By using IAM conditions, you can ensure that only the resources in project A can access the data in the project A topic, regardless of the network configuration or the VPC Service Controls. You can also prevent project B and any future project from accessing the data in the project A topic by not granting them any roles or permissions on the topic.
Option A is not a good solution, as VPC Service Controls are designed to prevent data exfiltration from Google Cloud resources to the public internet, not to control access between Google Cloud projects. VPC Service Controls create a perimeter around the resources of one or more projects, and restrict the communication with resources outside the perimeter. However, VPC Service Controls do not apply to Pub/Sub, as Pub/Sub is not associated with any specific IP address or VPC network. Therefore, configuring VPC Service Controls with a perimeter around the VPC of project A would not prevent project B or any future project from accessing the data in the project A topic, if they have the necessary IAM roles and permissions.
Option B is not a good solution, as firewall rules are used to control the ingress and egress traffic to and from the VPC network of a project. Firewall rules do not apply to Pub/Sub, as Pub/Sub is not associated with any specific IP address or VPC network. Therefore, adding firewall rules in project A to only permit traffic from the VPC in project A would not prevent project B or any future project from accessing the data in the project A topic, if they have the necessary IAM roles and permissions.
Option C is not a good solution, as VPC Service Controls are designed to prevent data exfiltration from Google Cloud resources to the public internet, not to control access between Google Cloud projects. VPC Service Controls create a perimeter around the resources of one or more projects, and restrict the communication with resources outside the perimeter. However, VPC Service Controls do not apply to Pub/Sub, as Pub/Sub is not associated with any specific IP address or VPC network. Therefore, configuring VPC Service Controls with a perimeter around project A would not prevent project B or any future project from accessing the data in the project A topic, if they have the necessary IAM roles and permissions. Reference: Access control with IAM | Cloud Pub/Sub Documentation | Google Cloud, [Using IAM Conditions | Cloud IAM Documentation | Google Cloud], [VPC Service Controls overview | Google Cloud], [Using VPC Service Controls | Google Cloud], [Pub/Sub tier capabilities | Memorystore for Redis | Google Cloud].
질문 # 24
Dataproc clusters contain many configuration files. To update these files, you will need to use the --properties option. The format for the option is: file_prefix:property=_____.
정답:C
설명:
Explanation
To make updating files and properties easy, the --properties command uses a special format to specify the configuration file and the property and value within the file that should be updated. The formatting is as follows: file_prefix:property=value.
Reference: https://cloud.google.com/dataproc/docs/concepts/cluster-properties#formatting
질문 # 25
What is the HBase Shell for Cloud Bigtable?
정답:B
설명:
The HBase shell is a command-line tool that performs administrative tasks, such as creating and deleting tables. The Cloud Bigtable HBase client for Java makes it possible to use the HBase shell to connect to Cloud Bigtable.
질문 # 26
How can you get a neural network to learn about relationships between categories in a categorical feature?
정답:C
설명:
There are two problems with one-hot encoding. First, it has high dimensionality, meaning that instead of having just one value, like a continuous feature, it has many values, or dimensions. This makes computation more time-consuming, especially if a feature has a very large number of categories. The second problem is that it doesn't encode any relationships between the categories. They are completely independent from each other, so the network has no way of knowing which ones are similar to each other.
Both of these problems can be solved by representing a categorical feature with an embedding column. The idea is that each category has a smaller vector with, let's say, 5 values in it. But unlike a one-hot vector, the values are not usually 0. The values are weights, similar to the weights that are used for basicfeatures in a neural network. The difference is that each category has a set of weights (5 of them in this case).
You can think of each value in the embedding vector as a feature of the category. So, if two categories are very similar to each other, then their embedding vectors should be very similar too.
Reference: https://cloudacademy.com/google/introduction-to-google-cloud-machine-learning-engine-course/a- wide-and-deep-model.html
질문 # 27
What is the recommended action to do in order to switch between SSD and HDD storage for your Google Cloud Bigtable instance?
정답:D
설명:
When you create a Cloud Bigtable instance and cluster, your choice of SSD or HDD storage for the cluster is permanent. You cannot use the Google Cloud Platform Console to change the type of storage that is used for the cluster.
If you need to convert an existing HDD cluster to SSD, or vice-versa, you can export the data from the existing instance and import the data into a new instance. Alternatively, you can write a Cloud Dataflow or Hadoop MapReduce job that copies the data from one instance to another.
질문 # 28
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우리Fast2test 에서 여러분은 아주 간단히Google Professional-Data-Engineer시험을 패스할 수 있습니다. 만약 처음Google Professional-Data-Engineer시험에 도전한다면 우리의Google Professional-Data-Engineer시험자료를 선택하여 다운받고 고부를 한다면 생가보다는 아주 쉽게Google Professional-Data-Engineer시험을 통과할 수 있으며 무엇보다도 시험시의 자신감 충만에 많은 도움이 됩니다. 다른 자료판매사이트도 많겠지만 저희는 저희 자료에 자신이 있습니다. 우리의 시험자료는 모두 하이퀼러티한 문제와 답으로 구성되었습니다, 그리고 우리는 업데트를 아주 중요시 생각하기에 어느 사이트보다 더 최신버전을 보실 수 잇을것입니다. 우리의Google Professional-Data-Engineer자료로 자신만만한 시험 준비하시기를 바랍니다. 우리를 선택함으로 자신의 시간을 아끼는 셈이라고 생각하시면 됩니다.Google Professional-Data-Engineer로 빠른시일내에 자격증 취득하시고GoogleIT업계중에 엘리트한 전문가되시기를 바랍니다.
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그 외, Fast2test Professional-Data-Engineer 시험 문제집 일부가 지금은 무료입니다: https://drive.google.com/open?id=165hf0QKHQvG5IdmF1N9kKhUvufNWG165
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