Online Access Free GCP-DE Exam Questions

MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

• A.Rowkey: dateColumn data: device_id, data_point
• B.Rowkey: date#device_idColumn data: data_point
• C.Rowkey: device_idColumn data: date, data_point
• D.Rowkey: data_pointColumn data: device_id, date
• E.Rowkey: date#data_pointColumn data: device_id

You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

• A.Configure the job to use non-default Compute Engine machine types when needed.
• B.Monitor the total execution time for a sampling of job
• C.Use the diagnose command to generate an operational output archiv
• D.Monitor CPU utilization for the cluste
• E.Resize the number of worker nodes in your cluster via the command line.
• F.Locate the bottleneck and adjust cluster resources.
• G.Use Cloud Dataflow to run your transformation
• H.Use Cloud Dataproc to run your transformation
• I.Monitor the job system lag with Stackdrive
• J.Use Cloud Dataflow to run your transformation
• K.Use Cloud Dataproc to run your transformation
• L.Use the default autoscaling setting for worker instances.

You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

• A.Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
• B.Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
• C.Increase the number of nodes in the Cloud Bigtable cluster
• D.Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
• E.Configure your Cloud Dataflow pipeline to use local execution

You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

• A.Workflow Templates on Cloud Dataproc
• B.Cloud Composer
• C.Cloud Scheduler
• D.cron

Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

• A.Spark
• B.Pig
• C.YARN
• D.Hive