SOL-C01 Question #272: Real Exam Question with Answer & Explanation

Question

You are tasked with loading data from a large number of small CSV files (each less than IOMB) stored in an S3 bucket into a single Snowflake table. You anticipate frequent additions of new CSV files to the bucket. Which of the following approaches would provide the MOST efficient and cost-effective solution for continuously loading this data into Snowflake, while minimizing operational overhead and latency? Select all that apply.

Options

• ACreating a Snowpipe that uses the 'AUTO INGEST = TRUE parameter and a notification
• BUsing the 'COPY INTO' command with the 'VALIDATION_MODE = RETURN_ERRORS
• CEmploying a third-party ETL tool to periodically extract data from the S3 bucket, transform it, and
• DCreating a Snowpipe that leverages an external function to preprocess each file before loading it
• ECreating a Snowpipe with SQS integration and a dedicated compute warehouse only configured

Explanation

Snowpipe with 'AUTO_INGEST = TRUE and a notification integration (SNS/SQS) is designed for continuous loading of files from cloud storage. This is the most efficient and cost-effective solution. Batch loading with 'COPY INTO' via a Task is less responsive and incurs unnecessary costs due to scheduled execution. Third-party ETL tools add complexity and cost. While Snowpipe can use external functions, it's generally not recommended for this simple scenario and adds unnecessary overhead. For Snowpipe dedicated compute warehouse is a important point for cost effective way

No community discussion yet for this question.