DAA-C01 Exam Dumps | You have a large table 'WEB EVENTS with columns 'EVENT TIMESTAMP, 'USER ID', 'PAGE URL', and 'EVENT

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Question 56

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Question 56/151

You have a large table 'WEB EVENTS with columns 'EVENT TIMESTAMP, 'USER ID', 'PAGE URL', and 'EVENT _ TYPE. You need to create a materialized view that efficiently calculates the daily unique user count for a specific set of 'PAGE URL' values. The 'WEB EVENTS table is frequently updated. Which of the following approaches would be MOST performant and scalable for this scenario?

A. Create a materialized view that directly selects 'COUNT(DISTINCT USER_ID)' grouped by ' and with filtering on the desired 'PAGE URL' values.

B. Create a materialized view that first calculates the total number of events for each user on each day and then aggregates that data to calculate the unique user count.

C. Create a standard view that filters the 'WEB_EVENTS' table and calculates 'COUNT(DISTINCT USER_ID)' grouped by and 'PAGE URL'.

D. Create a materialized view using a window function to calculate the running total of unique users each day, then extract the final value for each day.

E. Ingest the daily unique user count data via a 3rd party tool into a new table and create a view using that table.

Correct Answer: A

Calculating 'COUNT(DISTINCT directly in the materialized view is the most efficient approach. Pre-calculating unnecessary aggregates adds overhead. Standard views do not provide the performance benefits of materialized views. Window functions are generally less performant than direct aggregations in this scenario, and the new data can be calculated directly in Snowflake, avoiding dependency with 3rd party tools.

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