Google Associate Data Practitioner

Choose your answer

• A

  Create a Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.

• B

  Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.

• C

  Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.

• D

  Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.

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Choose your answer

• A

  Migrate the Spark jobs to Dataproc Serverless.

• B

  Configure a Google Kubernetes Engine cluster with Spark operators, and deploy the Spark jobs.

• C

  Migrate the Spark jobs to Dataproc on Google Kubernetes Engine.

• D

  Migrate the Spark jobs to Dataproc on Compute Engine.

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Choose your answer

• A

  Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.

• B

  Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.

• C

  Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.

• D

  Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.

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Choose your answer

• A

  Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.

• B

  Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.

• C

  Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.

• D

  Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.

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Choose your answer

• A

  Use Cloud Scheduler to schedule the jobs to run.

• B

  Use Cloud Tasks to schedule and run the jobs asynchronously.

• C

  Create directed acyclic graphs (DAGs) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.

• D

  Create directed acyclic graphs (DAGs) in Apache Airflow deployed on Google Kubernetes Engine. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.

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