Cloud Bigtable is a recommended option for storing very large amounts of
____________________________?

• A.multi-keyed data with very high latency
• B.multi-keyed data with very low latency
• C.single-keyed data with very low latency
• D.single-keyed data with very high latency

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An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

• A.BigQuery
• B.Cloud SQL
• C.Cloud BigTable
• D.Cloud Datastore

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You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patient records. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources. How should you adjust the database design?

• A.Add capacity (memory and disk space) to the database server by the order of 200.
• B.Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.
• C.Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.
• D.Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.

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You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

• A.Convert the streaming insert code to batch load for individual messages.
• B.Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.
• C.Re-write the application to load accumulated data every 2 minutes.
• D.Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.

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When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____.

• A.zone
• B.node
• C.label
• D.type

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