GCP-DE 試験問題を無料オンラインアクセス

You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

• A.Re-create the tables using DD
• B.Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
• C.Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
• D.Partition the tables by a column containing a TIMESTAMP or DATE Type.
• E.Write an Apache Beam pipeline that creates a BigQuery table per data
• F.Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.

You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

• A.Set the BigQuery dataset to be regiona
• B.In the event of an emergency, use the backup copy of the table.
• C.Set the BigQuery dataset to be regiona
• D.Set the BigQuery dataset to be multi-regional
• E.Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
• F.In the event of an emergency, use the backup copy of the table.
• G.In the event of an emergency, use a point-in-time snapshot to recover the data.
• H.Set the BigQuery dataset to be multi-regional
• I.In the event of an emergency, use a point-in-time snapshot to recover the data.
• J.Create a scheduled query to make copies of the data to tables suffixed with the time of the backup

Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

• A.A processing time trigger
• B.An hourly watermark
• C.An event time trigger
• D.The with Allowed Lateness method

You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

• A.HiveQL using Hive
• B.Python using MapReduce
• C.PigLatin using Pig
• D.Java using MapReduce

What is the general recommendation when designing your row keys for a Cloud Bigtable schema?

• A.Keep your row key as long as the field permits
• B.Keep the row keep as an 8 bit integer
• C.Include multiple time series values within the row key
• D.Keep your row key reasonably short