SPS-C01 Exam Dumps | You have a Snowpark application processing streaming data from an event table. You observe that the application

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Question 94/151

You have a Snowpark application processing streaming data from an event table. You observe that the application frequently fails with transient errors related to network connectivity or Snowflake service unavailability. You want to implement a robust error handling strategy to ensure the application can recover from these transient failures without losing data'. Which of the following approaches would be MOST appropriate and effective in this scenario, ensuring idempotent processing?

A. Implement a try-except block around the Snowpark DataFrame operations, logging the error and retrying the entire application from the beginning upon failure.

B. Use Snowflake's built-in retry mechanism for SQL queries by setting the 'CLIENT_SESSION PARAMETER to a non-zero value.

C. Implement a message queue (e.g., Kafka, SQS) to buffer the incoming event data. The Snowpark application consumes data from the queue, allowing for retries and ensuring no data is lost during transient failures.

D. Utilize Snowpark's 'cache()' method to cache the intermediate DataFrame results in memory, reducing the impact of transient failures.

E. Implement exponential backoff and jitter in your retry logic when catching exceptions during Snowpark operations. Store the last successfully processed event ID in a metadata table and resume processing from that point after a retry. Ensure all operations are idempotent.

Correct Answer: C,E

Implementing a message queue provides a buffer that isolates the Snowpark application from transient data source failures. E is correct because adding an exponential backoff mechanism with jitter is crucial to prevent overwhelming the system with retries and helps to ensure idempotent processing. Option B can address some internal Snowflake errors, but not connectivity issues. The other approaches do not address data loss or idempotent operation.

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