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Professional-Data-Engineer問題集を今すぐダウンロード
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Google Certified Professional Data Engineer Exam問題集を今すぐダウンロード
質問 43
Which of the following statements is NOT true regarding Bigtable access roles?
- A. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
- B. To give a user access to only one table in a project, you must configure access through your application.
- C. Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
- D. You can configure access control only at the project level.
正解: A
解説:
For Cloud Bigtable, you can configure access control at the project level. For example, you can grant the ability to:
Read from, but not write to, any table within the project. Read from and write to any table within the project, but not manage instances. Read from and write to any table within the project, and manage instances.
Reference: https://cloud.google.com/bigtable/docs/access-control
質問 44
What are two methods that can be used to denormalize tables in BigQuery?
- A. 1) Split table into multiple tables; 2) Use a partitioned table
- B. 1) Use a partitioned table; 2) Join tables into one table
- C. 1) Join tables into one table; 2) Use nested repeated fields
- D. 1) Use nested repeated fields; 2) Use a partitioned table
正解: C
解説:
The conventional method of denormalizing data involves simply writing a fact, along with all its dimensions, into a flat table structure. For example, if you are dealing with sales transactions, you would write each individual fact to a record, along with the accompanying dimensions such as order and customer information.
The other method for denormalizing data takes advantage of BigQuery's native support for nested and repeated structures in JSON or Avro input data. Expressing records using nested and repeated structures can provide a more natural representation of the underlying data. In the case of the sales order, the outer part of a JSON structure would contain the order and customer information, and the inner part of the structure would contain the individual line items of the order, which would be represented as nested, repeated elements.
質問 45
You are deploying MariaDB SQL databases on GCE VM Instances and need to configure monitoring and alerting. You want to collect metrics including network connections, disk IO and replication status from MariaDB with minimal development effort and use StackDriver for dashboards and alerts.
What should you do?
- A. Install the StackDriver Logging Agent and configure fluentd in_tail plugin to read MariaDB logs.
- B. Install the StackDriver Agent and configure the MySQL plugin.
- C. Install the OpenCensus Agent and create a custom metric collection application with a StackDriver exporter.
- D. Place the MariaDB instances in an Instance Group with a Health Check.
正解: A
質問 46
You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?
- A. Deploy the Cloud SQL Proxy on the Cloud Dataproc master
- B. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
- C. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
- D. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
正解: B
解説:
https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/init-actions
質問 47
You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings.
Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?
- A. Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.
- B. Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.
- C. Re-write the application to load accumulated data every 2 minutes.
- D. Convert the streaming insert code to batch load for individual messages.
正解: B
解説:
The data is first comes to buffer and then written to Storage. If we are running queries in buffer we will face above mentioned issues. If we wait for the bigquery to write the data to storage then we won't face the issue. So We need to wait till it's written to storage.
質問 48
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