Snowflake COF-R02 Online Practice Questions and Exam Preparation

Snowflake COF-R02 Online Questions & Answers

• Question 1:

  Which of the following are best practices for loading data into Snowflake? (Choose three.)

  A. Aim to produce data files that are between 100 MB and 250 MB in size, compressed.
  B. Load data from files in a cloud storage service in a different region or cloud platform from the service or region containing the Snowflake account, to save on cost.
  C. Enclose fields that contain delimiter characters in single or double quotes.
  D. Split large files into a greater number of smaller files to distribute the load among the compute resources in an active warehouse.
  E. When planning which warehouse(s) to use for data loading, start with the largest warehouse possible.
  F. Partition the staged data into large folders with random paths, allowing Snowflake to determine the best way to load each file.
  B. Load data from files in a cloud storage service in a different region or cloud platform from the service or region containing the Snowflake account, to save on cost.
  C. Enclose fields that contain delimiter characters in single or double quotes.
  E. When planning which warehouse(s) to use for data loading, start with the largest warehouse possible.

• Question 2:

  When loading data into Snowflake via Snowpipe what is the compressed file size recommendation?

  A. 10-50 MB
  B. 100-250 MB
  C. 300-500 MB
  D. 1000-1500 MB
  B. 100-250 MB

• Question 3:

  Each incremental increase in Virtual Warehouse size (e,g. Medium to Large) generally results in what? Select one.

  A. More micro-partitions
  B. Better query scheduling
  C. Double the numbers of servers In the compute duster
  D. Higher storage costs
  C. Double the numbers of servers In the compute duster

• Question 4:

  What type of query benefits the MOST from search optimization?

  A. A query that uses only disjunction (i.e., OR) predicates
  B. A query that includes analytical expressions
  C. A query that uses equality predicates or predicates that use IN
  D. A query that filters on semi-structured data types
  C. A query that uses equality predicates or predicates that use IN

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  Explanation/Reference:

  Reference: https://community.snowflake.com/s/article/Search-Optimization-When-How-To-Use

• Question 5:

  Which data types are supported by Snowflake when using semi-structured data? (Choose two.)

  A. VARIANT
  B. VARRAY
  C. STRUCT
  D. ARRAY
  E. QUEUE
  A. VARIANT
  D. ARRAY

• Question 6:

  What do the terms scale up and scale out refer to in Snowflake? (Choose two.)

  A. Scaling out adds clusters of the same size to a virtual warehouse to handle more concurrent queries.
  B. Scaling out adds clusters of varying sizes to a virtual warehouse.
  C. Scaling out adds additional database servers to an existing running cluster to handle more concurrent queries.
  D. Snowflake recommends using both scaling up and scaling out to handle more concurrent queries.
  E. Scaling up resizes a virtual warehouse so it can handle more complex workloads.
  F. Scaling up adds additional database servers to an existing running cluster to handle larger workloads.
  A. Scaling out adds clusters of the same size to a virtual warehouse to handle more concurrent queries.
  E. Scaling up resizes a virtual warehouse so it can handle more complex workloads.

• Question 7:

  True or False: A Virtual Warehouse can be resized while suspended.

  A. True
  B. False
  A. True

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  Explanation/Reference:

  Reference: https://docs.snowflake.com/en/user-guide/warehouses-tasks.html#effects-of-resizing-a-suspended-warehouse

• Question 8:

  Which data type can store more than one type of data structure?

  A. JSON
  B. BINARY
  C. VARCHAR
  D. VARIANT
  D. VARIANT

• Question 9:

  What is the minimum Snowflake edition needed for database failover and fail-back between Snowflake accounts for business continuity and disaster recovery?

  A. Standard
  B. Enterprise
  C. Business Critical
  D. Virtual Private Snowflake
  B. Enterprise

• Question 10:

  What is a limitation of a Materialized View?

  A. A Materialized View cannot support any aggregate functions
  B. A Materialized View can only reference up to two tables
  C. A Materialized View cannot be joined with other tables
  D. A Materialized View cannot be defined with a JOIN
  D. A Materialized View cannot be defined with a JOIN

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  Explanation/Reference:

  There are several limitations to using materialized views:

  A materialized view can query only a single table.

  Joins, including self-joins, are not supported.