DAA-C01 Exam Dumps | A Snowflake data pipeline utilizes Snowpipe to ingest data from cloud storage into a staging table. After

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Question 114

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Question 114/151

A Snowflake data pipeline utilizes Snowpipe to ingest data from cloud storage into a staging table. After the data is ingested, a series of transformation tasks process the data and load it into a target table. Due to network connectivity issues, Snowpipe occasionally experiences delays in loading data, causing downstream tasks to fail. Which strategies can be implemented to monitor the latency and improve the resilience of this pipeline?

A. Implement a check within the transformation tasks to verify that the staging table contains data newer than a specific timestamp before proceeding with the transformation. Use ' on the staging table to get the last updated timestamp.

B. Increase the 'MAX CONCURRENCY parameter of the Snowpipe to improve the ingestion rate.

C. Implement a retry mechanism within the transformation tasks that waits for a specified amount of time and then checks the staging table for new data before proceeding.

D. Configure a Snowflake resource monitor to track the Snowpipe's credit consumption and trigger alerts when consumption exceeds a threshold.

E. Implement error handling within the transformation tasks to gracefully handle the case where the staging table is empty and log the error to a dedicated logging table.

Correct Answer: A,C,E

Option A is correct because checking the last updated timestamp allows the task to skip its execution or alert if data isn't timely. Option C is correct as it offers a resilient approach. Option E is also a correct since error logging is a critical part of resilience. Option B addresses throughput, not necessarily latency or resilience related to external issues, increasing concurrency does not guarantee latency improvements if connectivity is the issue. Option D only monitors credit consumption, not pipeline latency.

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