You have an HTTP Cloud Function that is called via POST. Each submission's request body has a flat, unnested JSON structure containing numeric and text data. After the Cloud Function completes, the…

Question

Options

• ADirectly persist each POST request's JSON data into Datastore.
• BTransform the POST request's JSON data, and stream it into BigQuery.
• CTransform the POST request's JSON data, and store it in a regional Cloud SQL cluster.
• DPersist each POST request's JSON data as an individual file within Cloud Storage, with the file

• A
  9% (5)
• B
  83% (48)
• C
  5% (3)
• D
  3% (2)

Explanation

BigQuery is Google Cloud's fully managed, serverless data warehouse purpose-built for complex analytical queries at massive scale. Streaming the Cloud Function's JSON payload into BigQuery via the Streaming API makes data immediately queryable (no batch delay), and BigQuery's distributed architecture supports many concurrent users running complex queries simultaneously - exactly matching the requirement. Option A (Datastore) is a document database optimized for transactional lookups, not large-scale analytics. Option C (Cloud SQL) is a relational database that struggles with high-concurrency complex analytics at scale. Option D (Cloud Storage as individual files) requires additional ETL before analytics are possible and does not support direct SQL-based analysis.

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