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Google Data Engineer 認定 GCP-DE 試験問題:

1. You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A) Create an application that provides an AP
B) Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.
C) Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
D) Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
E) Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
F) Create an application that writes to a Cloud SQL database to store the dat

2. 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) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
B) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
C) Deploy the Cloud SQL Proxy on the Cloud Dataproc master
D) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter

3. What are the minimum permissions needed for a service account used with Google Dataproc?

A) Execute to Google Cloud Storage; write to Google Cloud Logging
B) Read and write to Google Cloud Storage; write to Google Cloud Logging
C) Write to Google Cloud Storage; read to Google Cloud Logging
D) Execute to Google Cloud Storage; execute to Google Cloud Logging

4. You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A) Create a table on Cloud Spanner, and insert and delete rows with the job information
B) Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them
C) Create a table on Cloud SQL, and insert and delete rows with the job information
D) Create an API using App Engine to receive and send messages to the applications

5. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

A) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
B) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
C) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
D) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination

質問と回答：