You work for a car manufacturer and have set up a data pipeline using Google Cloud Pub/Sub to capture anomalous sensor events. You are using a push subscription in Cloud Pub/Sub that calls a custom HTTPS endpoint that you have created to take action of these anomalous events as they occur. Your custom HTTPS endpoint keeps getting an inordinate amount of duplicate messages. What is the most likely cause of these duplicate messages?

• A.The message body for the sensor event is too large.
• B.Your custom endpoint has an out-of-date SSL certificate.
• C.The Cloud Pub/Sub topic has too many messages published to it.
• D.Your custom endpoint is not acknowledging messages within the acknowledgement deadline.

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Your company is streaming real-time sensor data from their factory floor into Bigtable and they have noticed extremely poor performance. How should the row key be redesigned to improve Bigtable performance on queries that populate real-time dashboards?

• A.Use a row key of the form <timestamp>.
• B.Use a row key of the form <sensorid>.
• C.Use a row key of the form <timestamp>#<sensorid>.
• D.Use a row key of the form >#<sensorid>#<timestamp>.

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You need to create a new transaction table in Cloud Spanner that stores product sales data. You are deciding what to use as a primary key. From a performance perspective, which strategy should you choose?

• A.The current epoch time
• B.A concatenation of the product name and the current epoch time
• C.A random universally unique identifier number (version 4 UUID)
• D.The original order identification number from the sales system, which is a monotonically increasing integer

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

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

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What are two of the benefits of using denormalized data structures in BigQuery?

• A.Reduces the amount of data processed, reduces the amount of storage required
• B.Increases query speed, makes queries simpler
• C.Reduces the amount of storage required, increases query speed
• D.Reduces the amount of data processed, increases query speed

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