DEA-C02 Exam Dumps | You are tasked with creating a resilient data pipeline using Snowpark Python. The pipeline transforms

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Question 22/149

You are tasked with creating a resilient data pipeline using Snowpark Python. The pipeline transforms data from a raw stage to a processed stage. A key transformation involves joining two DataFrames, 'dfl' and 'df2 , based on a common column, 'id'. You want to ensure that even if 'df2 is temporarily unavailable or contains unexpected data, the pipeline continues to process 'dfl' using a default value for missing data from 'df2. Which of the following approaches provides the best balance of resilience and data integrity? Assume you have defined a default dataframe 'df default' already.

A. Perform a 'left_outer' join of 'dfl' with 'df2. If the join fails, catch the exception and proceed without the join.

B. Use a 'try-except' block to catch any exceptions during the join operation. If an exception occurs, use the 'fillna()' method to replace missing values with the default data value.

C. Perform a 'left_outer' join of 'dfl' with 'df2. If 'df2 is unavailable or returns no data, replace 'df2' with a default DataFrame Cdf_default) and proceed with the join.

D. Use 'broadcast hint on 'df2 before performing the join to reduce the chances of join failure, assuming 'df2 is a small dataframe.

E. Write a custom Python UDF that attempts to retrieve the corresponding data from 'df2 based on the 'id' column. If the retrieval fails for a particular ID, return a default value.

Correct Answer: C

Option C provides the best balance. A join ensures that all rows from 'dfl are preserved, even if there's no matching row in 'df2. By replacing 'df2 with 'df_default' when 'df2' is unavailable/empty, the pipeline continues processing 'dfl with predefined defaults, maintaining data integrity. Option A only bypasses the exception without using default value. Option B is incorrect because 'fillna' may not handle the case where 'df2 is unavailable and the whole join fails. Option D may only help with performance but does not guarantee that df2 will be available at all times. Option E is also not efficient due to UDF being slower than joins.

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