ADP by Google Actual Free Exam Questions And Answers

Question 1

You are designing a pipeline to process data files that arrive in Cloud Storage by 3:00 am each day. Data processing is performed in stages, where the output of one stage becomes the input of the next. Each stage takes a long time to run. Occasionally a stage fails, and you have to address the problem. You need to ensure that the final output is generated as quickly as possible. What should you do?

A. Design a Spark program that runs under Dataproc. Code the program to wait for user input when an error is detected. Rerun the last action after correcting any stage output data errors.

B. Design the workflow as a Cloud Workflow instance. Code the workflow to jump to a given stage based on an input parameter. Rerun the workflow after correcting any stage output data errors.

C. Design the pipeline as a set of PTransforms in Dataflow. Restart the pipeline after correcting any stage output data errors.

D. Design the processing as a directed acyclic graph (DAG) in Cloud Composer. Clear the state of the failed task after correcting any stage output data errors.

Discussion 0

Correct Answer: D Vote an answer

Question 2

You have a Dataflow pipeline that processes website traffic logs stored in Cloud Storage and writes the processed data to BigQuery. You noticed that the pipeline is failing intermittently. You need to troubleshoot the issue. What should you do?

A. Use Cloud Logging to create a chart displaying the pipeline's error logs. Use Metrics Explorer to validate the findings from the chart.

B. Use Cloud Logging to identify error groups in the pipeline's logs. Use Cloud Monitoring to create a dashboard that tracks the number of errors in each group.

C. Use Cloud Logging to view error messages in the pipeline's logs. Use Cloud Monitoring to analyze the pipeline's metrics, such as CPU utilization and memory usage.

D. Use the Dataflow job monitoring interface to check the pipeline's status every hour. Use Cloud Profiler to analyze the pipeline's metrics, such as CPU utilization and memory usage.

Discussion 0

Correct Answer: C Vote an answer

Question 3

Your data science team needs to collaboratively analyze a 25 TB BigQuery dataset to support the development of a machine learning model. You want to use Colab Enterprise notebooks while ensuring efficient data access and minimizing cost. What should you do?

A. Copy the BigQuery dataset to the local storage of the Colab Enterprise runtime, and analyze the data using Pandas.

B. Create a Dataproc cluster connected to a Colab Enterprise notebook, and use Spark to process the data in BigQuery.

C. Use BigQuery magic commands within a Colab Enterprise notebook to query and analyze the data.

D. Export the BigQuery dataset to Google Drive. Load the dataset into the Colab Enterprise notebook using Pandas.

Discussion 0

Correct Answer: C Vote an answer

Question 4

Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

A. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.

B. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.

C. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.

D. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.

Discussion 0

Correct Answer: B Vote an answer

Question 5

Your organization plans to move their on-premises environment to Google Cloud. Your organization's network bandwidth is less than 1 Gbps. You need to move over 500 ## of data to Cloud Storage securely, and only have a few days to move the dat a. What should you do?

A. Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.

B. Connect to Google Cloud using Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.

C. Connect to Google Cloud using VPN. Use Storage Transfer Service to move the data to Cloud Storage.

D. Request multiple Transfer Appliances, copy the data to the appliances, and ship the appliances back to Google Cloud to upload the data to Cloud Storage.

Discussion 0

Correct Answer: D Vote an answer

Question 6

You are migrating data from a legacy on-premises MySQL database to Google Cloud. The database contains various tables with different data types and sizes, including large tables with millions of rows and transactional dat a. You need to migrate this data while maintaining data integrity, and minimizing downtime and cost. What should you do?

A. Export the MySQL database to CSV files, transfer the files to Cloud Storage by using Storage Transfer Service, and load the files into a Cloud SQL for MySQL instance.

B. Use Database Migration Service to replicate the MySQL database to a Cloud SQL for MySQL instance.

C. Use Cloud Data Fusion to migrate the MySQL database to MySQL on Compute Engine.

D. Set up a Cloud Composer environment to orchestrate a custom data pipeline. Use a Python script to extract data from the MySQL database and load it to MySQL on Compute Engine.

Discussion 0

Correct Answer: B Vote an answer

Question 7

You need to create a data pipeline that streams event information from applications in multiple Google Cloud regions into BigQuery for near real-time analysis. The data requires transformation before loading. You want to create the pipeline using a visual interface. What should you do?

A. Push event information to a Pub/Sub topic. Create a BigQuery subscription in Pub/Sub.

B. Push event information to a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.

C. Push event information to Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.

D. Push event information to a Pub/Sub topic. Create a Cloud Run function to subscribe to the Pub/Sub topic, apply transformations, and insert the data into BigQuery.

Discussion 0

Correct Answer: B Vote an answer

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