Question 1

You stream order data by using a Dataflow pipeline, and write the aggregated result to Memorystore. Youprovisioned a Memorystore for Redis instance with Basic Tier. 4 GB capacity, which is used by 40 clients forread-only access. You are expecting the number of read-only clients to increase significantly to a few hundredand you need to be able to support the demand. You want to ensure that read and write access availability isnot impacted, and any changes you make can be deployed quickly. What should you do?

Options :

A : Create multiple new Memorystore for Redis instances with Basic Tier (4 GB capacity) Modify theDataflow pipeline and new clients to use all instances

B : Create a new Memorystore for Redis instance with Standard Tier Set capacity to 4 GB and read replicato No read replicas (high availability only). Delete the old instance.

C : Create a new Memorystore for Memcached instance Set a minimum of three nodes, and memory pernode to 4 GB. Modify the Dataflow pipeline and all clients to use the Memcached instance Delete theold instance.

D : Create a new Memorystore for Redis instance with Standard Tier Set capacity to 5 GB and createmultiple read replicas Delete the old instance.

Answer: D

Question 2

A data analyst currently has the bigquery.dataViewer role and can successfully query a materialized view. They also want to be able to refresh the materialized view. You want to use a predefined role but not grant them any more permissions than needed to refresh the materialized view. What predefined role would you grant to the user?

Options :

A : bigquery.dataOwner

B : bigquery.admin

C : bigquery.dataEditor

D : bigquery.mvUpdater

Answer: C

Question 3

Your company is running their first dynamic campaign, serving different offers by analyzing real-time data during the holiday season. The data scientists are collecting terabytes of data that rapidly grows every hour during their 30-day campaign. They are using Google Cloud Dataflow to preprocess the data and collect the feature (signals) data that is needed for the machine learning model in Google Cloud Bigtable. The team is observing suboptimal performance with reads and writes of their initial load of 10 TB of data. They want to improve this performance while minimizing cost. What should they do?

Options :

A : Redefine the schema by evenly distributing reads and writes across the row space of the table.

B : The performance issue should be resolved over time as the site of the BigDate cluster is increased.

C : Redesign the schema to use a single row key to identify values that need to be updated frequently in the cluster.

D : Redesign the schema to use row keys based on numeric IDs that increase sequentially per user viewing the offers.

Answer: A

Question 4

Messages are unexpectedly accumulating in service using Cloud Pub/Sub. A developer unfamiliar with Cloud Pub/Sub has asked for our help in diagnosing the problem. What would you point out with respect to how messages are removed from Cloud Pub/Sub topics?

Options :

A : Once at least one subscriber for each topic has acknowledged the message it will be deleted from storage.

B : Once at least one subscriber for each bucket has acknowledged the message it will be deleted from storage.

C : Once at least one subscriber for any subscription has acknowledged the message it will be deleted from storage.

D : Once at least one subscriber for each subscription has acknowledged the message it will be deleted from storage.

Answer: D

Question 5

You are designing an Apache Beam pipeline to enrich data from Cloud Pub/Sub with static reference data from BigQuery. The reference data is small enough to fit in memory on a single worker. The pipeline should write enriched results to BigQuery for analysis. Which job type and transforms should this pipeline use?

Options :

A : Batch job, PubSubIO, side-inputs

B : Streaming job, PubSubIO, JdbcIO, side-outputs

C : Streaming job, PubSubIO, BigQueryIO, side-inputs

D : Streaming job, PubSubIO, BigQueryIO, side-outputs

Answer: C

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