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Answer: Store the common data encoded as Avro in Google Cloud Storage.
The correct answer is C. Storing the common data encoded as Avro in Google Cloud Storage is the best approach to ensure interoperability between BigQuery and Hadoop/Spark workloads. Avro is a widely used data serialization format compatible with both systems. Data stored in Google Cloud Storage can be accessed by BigQuery for analysis and by Dataproc for Hadoop/Spark jobs, providing a bridge between the two environments. This also allows for the use of data transformation pipelines in Dataproc.
Author: LeetQuiz Editorial Team
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Flowlogistic, a logistics company, aims to use Google BigQuery as their primary analysis platform. However, they are unable to migrate some of their existing Apache Hadoop and Spark workloads to BigQuery. They need a solution for storing data that needs to be accessed by both BigQuery and their Hadoop/Spark workloads. What should they do?
A. Store the common data in BigQuery as partitioned tables. B. Store the common data in BigQuery and expose authorized views. C. Store the common data encoded as Avro in Google Cloud Storage. D. Store the common data in the HDFS storage for a Google Cloud Dataproc cluster.
A
Store the common data in BigQuery as partitioned tables.
B
Store the common data in BigQuery and expose authorized views.
C
Store the common data encoded as Avro in Google Cloud Storage.
D
Store the common data in the HDFS storage for a Google Cloud Dataproc cluster.
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