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  1. Home
  2. Snowflake Certification
  3. COF-C02 Exam
  4. Snowflake.COF-C02.v2025-08-26.q885 Dumps
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Question 796

Which type of join will list a I rows in the specified table, even if those rows have no match in the other table?

Correct Answer: D
An outer join, specifically a left outer join, will list all rows from the left table and match them with rows from the right table. If there is no match, the result will still include the row from the left table, with NULLs for columns from the right table. References: Based on general SQL knowledge as of 2021.
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Question 797

Which Snowflake object can be used to record DML changes made to a table?

Correct Answer: C
Snowflake Streams are used to track and record Data Manipulation Language (DML) changes made to a table. Streams capture changes such as inserts, updates, and deletes, which can then be processed by other Snowflake objects or external applications.
* Creating a Stream:
CREATE OR REPLACE STREAM my_stream ON TABLE my_table;
* Using Streams: Streams provide a way to process changes incrementally, making it easier to build efficient data pipelines.
* Consuming Stream Data: The captured changes can be consumed using SQL queries or Snowflake tasks.
References:
* Snowflake Documentation: Using Streams
* Snowflake Documentation: Change Data Capture (CDC) with Streams
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Question 798

What is the MINIMUM Snowflake edition required to add masking policies to selectively mask plain-text data in a table or in view columns at query time?

Correct Answer: C
* Masking policies in Snowflake require a minimum of the Business Critical Edition.
* This feature enables dynamic masking of plain-text data at query time to meet compliance and security requirements.
* Example:
sql
CopyEdit
CREATE MASKING POLICY ssn_mask AS (val STRING)
RETURNS STRING ->
CASE
WHEN CURRENT_ROLE() IN ('DATA_ANALYST') THEN '***-**-****'
ELSE val
END;
References:
* Snowflake Documentation: Dynamic Data Masking
* Snowflake Editions Comparison
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Question 799

What is the benefit of using the STRIP_OUTER_ARRAY parameter with the COPY INTO <table> command when loading data from a JSON file into a table?

Correct Answer: B
The STRIP_OUTER_ARRAY parameter in the COPY INTO <table> command is used when loading data from a JSON file into a table. This parameter removes the outer array structure from the JSON data and loads separate rows of data into the table.
Understanding the STRIP_OUTER_ARRAY Parameter:
JSON files often contain data in an array format where multiple records are nested within a single outer array.
The STRIP_OUTER_ARRAY parameter helps in simplifying the loading process by removing this outer array, allowing each element within the array to be loaded as a separate row in the target table.
How It Works:
When the STRIP_OUTER_ARRAY parameter is set to TRUE, Snowflake treats each item within the outer array as an individual record.
This eliminates the need for additional parsing or transformation steps that would otherwise be required to handle nested arrays.
Example Usage:
FROM @my_stage/file.json
FILE_FORMAT = (TYPE = 'JSON' STRIP_OUTER_ARRAY = TRUE);
In this example, the JSON file containing an array of objects is loaded into the table my_table.
Each object within the array is loaded as a separate row, without the outer array structure.
Benefits:
Simplifies data loading: By removing the outer array, the data is directly loaded into the table without additional manipulation.
Enhances performance: Streamlines the loading process, reducing the complexity and potential errors in handling nested JSON structures.
Reference:
Snowflake Documentation: COPY INTO <table>
Snowflake Documentation: JSON File Format Options
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Question 800

What are the default Time Travel and Fail-safe retention periods for transient tables?

Correct Answer: C
Transient tables in Snowflake have a default Time Travel retention period of 1 day, which allows users to access historical data within the last 24 hours. However, transient tables do not have a Fail-safe period. Fail- safe is an additional layer of data protection that retains data beyond the Time Travel period for recovery purposes in case of extreme data loss. Since transient tables are designed for temporary or intermediate workloads with no requirement for long-term durability, they do not include a Fail-safe period by default1.
References:
* Snowflake Documentation on Storage Costs for Time Travel and Fail-safe
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