Apply Clustering and Materialized Views ARA-C01 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   How does Snowflake use materialized views to improve query performance?

   • AIt creates an index on the materialized view to speed up lookups
   • BIt caches the materialized view in the virtual warehouse's memory
   • CIt automatically rewrites eligible queries to read from the materialized view
   • DIt requires the user to modify queries to reference the materialized view
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2. 2foundation · easy

   What information is stored in the clustering metadata for each micro-partition?

   • AThe query history for the table
   • BThe exact row-level data for each column
   • CThe minimum and maximum values for each column
   • DThe list of users who have accessed the table
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4. 3foundation · easy

   What is the primary purpose of creating a materialized view?

   • ATo enforce data integrity constraints on the base table
   • BTo provide a logical abstraction of the underlying tables
   • CTo create a backup of the base table
   • DTo precompute and store query results for faster access
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5. 4foundation · easy

   A table stores sales transactions and is frequently filtered by the `order_date` column in range predicates. Which column is most appropriate as the clustering key for this table?

   • Atotal_amount
   • Border_status
   • Ccustomer_id
   • Dorder_date
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6. 5application · medium

   A team is considering creating a materialized view on a table that receives frequent inserts and updates. They are concerned about the cost of maintaining the view. Which statement accurately describes the maintenance cost?

   • AMaintenance is free for all materialized views
   • BMaintenance runs only when the view is queried
   • CMaintenance consumes compute credits from the account's Snowflake-managed warehouse
   • DMaintenance requires a dedicated warehouse to be specified
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