Topic 1 Question 58
Your company’s ecommerce website collects product reviews from customers. The reviews are loaded as CSV files daily to a Cloud Storage bucket. The reviews are in multiple languages and need to be translated to Spanish. You need to configure a pipeline that is serverless, efficient, and requires minimal maintenance. What should you do?
Load the data into BigQuery using Dataproc. Use Apache Spark to translate the reviews by invoking the Cloud Translation API. Set BigQuery as the sink.
Use a Dataflow templates pipeline to translate the reviews using the Cloud Translation API. Set BigQuery as the sink.
Load the data into BigQuery using a Cloud Run function. Use the BigQuery ML create model statement to train a translation model. Use the model to translate the product reviews within BigQuery.
Load the data into BigQuery using a Cloud Run function. Create a BigQuery remote function that invokes the Cloud Translation API. Use a scheduled query to translate new reviews.
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コメント(2)
- 正解だと思う選択肢: B
Dataflow is a fully managed
👍 3SaquibHerman2025/02/19 - 正解だと思う選択肢: B
The best option is B. Dataflow template with Cloud Translation API. Option B is best because Dataflow templates are serverless, managed, and efficient for data pipelines like translation. Option A (Dataproc/Spark) is incorrect because Dataproc is not serverless and adds maintenance. Option C (Cloud Run/BigQuery ML) is incorrect because training a BigQuery ML model for translation is overly complex for this. Option D (Cloud Run/Remote Function) is incorrect because it adds unnecessary complexity with remote functions and scheduled queries. Therefore, Option B, Dataflow template, is the most streamlined and best-fit serverless solution.
👍 1n21837128472025/03/05
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