SOL-C01 Question #242: Real Exam Question with Answer & Explanation

Question

A Snowflake architect is designing a data lake solution using Snowflake's external tables. The data lake contains JSON files stored in AWS S3. The architect needs to ensure that Snowflake can automatically discover new JSON files added to the S3 bucket and make them available for querying through the external table. Which of the following approaches provides the MOST efficient and scalable solution for automatically refreshing the external table metadata? Schedule a daily task in Snowflake to execute 'ALTER EXTERNAL TABLE REFRESH' to manually update the metadata.

Options

• AConfigure an AWS Lambda function triggered by S3 events (e.g., `s3:ObjectCreated') to execute
• BEnable Snowflake's Event Tables and configure them to capture S3 events. Then, create a stream
• CUse Snowflake's Snowpipe with auto-ingest configured to automatically load data from the S3
• DUtilize Snowflake's automatic data clustering feature on the external table based on the file

Explanation

Using Event Tables (Option C) is the most efficient and scalable solution. Snowflake Event Tables are designed to capture and process events directly within Snowflake, making them ideal for this scenario. The stream and task can automatically trigger the refresh whenever a new S3 event is detected. Option A (scheduled task) is less efficient. Option B (Lambda function) adds external complexity. Option D (Snowpipe) loads data into Snowflake, not updating external table metadata. Option E (automatic data clustering) does not automatically update the metadata of external tables when new files are added.

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