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Snowflake COF-C02 Practice Test - Questions Answers, Page 66

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What would cause different results to be returned when running the same query twice?

A.
SAMPLE is used and the seed is set
A.
SAMPLE is used and the seed is set
Answers
B.
sample is used and the seed is not set.
B.
sample is used and the seed is not set.
Answers
C.
Fraction-based sampling is used.
C.
Fraction-based sampling is used.
Answers
D.
Fixed-size sampling Is used.
D.
Fixed-size sampling Is used.
Answers
Suggested answer: B

Explanation:

When using the SAMPLE clause in a query, if the seed is not set, Snowflake will use a different random seed for each execution of the query. This results in different rows being sampled each time, leading to different results. Setting a seed ensures that the same rows are sampled each time the query is run.

References:

Snowflake Documentation: Sampling

Which MINIMUM set of privileges is required to temporarily bypass an active network policy by configuring the user object property MINS_TO_BYPASS_NETWORK_POLICY?

A.
Only while in the ACCOUNTADMIH role
A.
Only while in the ACCOUNTADMIH role
Answers
B.
Only while in the securityadmin role
B.
Only while in the securityadmin role
Answers
C.
Only the role with the ownership privilege on the network policy
C.
Only the role with the ownership privilege on the network policy
Answers
D.
Only Snowflake Support can set the value for this object property
D.
Only Snowflake Support can set the value for this object property
Answers
Suggested answer: A

Explanation:

To temporarily bypass an active network policy by configuring the user object property MINS_TO_BYPASS_NETWORK_POLICY, the minimum set of privileges required is having the ACCOUNTADMIN role. This role has the necessary privileges to make such changes, including modifying user properties that affect network policies.

References:

Snowflake Documentation: Network Policy Management

Which Snowflake table is an implicit object layered on a stage, where the stage can be either internal or external?

A.
Directory table
A.
Directory table
Answers
B.
Temporary table
B.
Temporary table
Answers
C.
Transient table
C.
Transient table
Answers
D.
A table with a materialized view
D.
A table with a materialized view
Answers
Suggested answer: A

Explanation:

A directory table in Snowflake is an implicit object layered on a stage, whether internal or external. It allows users to query the contents of a stage as if it were a table, providing metadata about the files stored in the stage, such as filenames, file sizes, and last modified timestamps.

References:

Snowflake Documentation: Directory Tables

What are type predicates used for?

A.
Extracting data from a variant column
A.
Extracting data from a variant column
Answers
B.
Casting a value in a variant column to a particular data type
B.
Casting a value in a variant column to a particular data type
Answers
C.
Determining if a value in a variant column is a particular data type
C.
Determining if a value in a variant column is a particular data type
Answers
D.
Manipulating objects and arrays in a VARIANT column
D.
Manipulating objects and arrays in a VARIANT column
Answers
Suggested answer: C

Explanation:

Type predicates in Snowflake are used to determine if a value in a VARIANT column is of a particular data type. This is useful when working with semi-structured data stored in VARIANT columns, as it allows for data type validation and conditional processing based on the data type.

References:

Snowflake Documentation: Type Predicates

In Snowflake, what allows users to perform recursive queries?

A.
QUALIFY
A.
QUALIFY
Answers
B.
LATERAL
B.
LATERAL
Answers
C.
PIVOT
C.
PIVOT
Answers
D.
CONNECT BY
D.
CONNECT BY
Answers
Suggested answer: D

Explanation:

In Snowflake, the CONNECT BY clause allows users to perform recursive queries. Recursive queries are used to process hierarchical or tree-structured data, such as organizational charts or file systems. The CONNECT BY clause is used in conjunction with the START WITH clause to specify the starting point of the hierarchy and the relationship between parent and child rows.

References:

Snowflake Documentation: Hierarchical Queries

Which table function is used to perform additional processing on the results of a previously-run query?

A.
QUERY_HISTORY
A.
QUERY_HISTORY
Answers
B.
RESULT_SCAN
B.
RESULT_SCAN
Answers
C.
DESCRIBE_RESULTS
C.
DESCRIBE_RESULTS
Answers
D.
QUERY HISTORY BY SESSION
D.
QUERY HISTORY BY SESSION
Answers
Suggested answer: B

Explanation:

The RESULT_SCAN table function is used in Snowflake to perform additional processing on the results of a previously-run query. It allows users to reference the result set of a previous query by its query ID, enabling further analysis or transformations without re-executing the original query.

References:

Snowflake Documentation: RESULT_SCAN

Which actions can be performed using a resource monitor in Snowflake? (Select TWO).

A.
Monitor the performance of individual queries in real-time
A.
Monitor the performance of individual queries in real-time
Answers
B.
Automatically allocate more storage space to a virtual warehouse
B.
Automatically allocate more storage space to a virtual warehouse
Answers
C.
Modify the queries being executed within a virtual warehouse.
C.
Modify the queries being executed within a virtual warehouse.
Answers
D.
Suspend a virtual warehouse when its credit usage reaches a defined limit.
D.
Suspend a virtual warehouse when its credit usage reaches a defined limit.
Answers
E.
Trigger a notification to account administrators when credit usage reaches a specified threshold
E.
Trigger a notification to account administrators when credit usage reaches a specified threshold
Answers
Suggested answer: D, E

Explanation:

Resource monitors in Snowflake can perform actions such as suspending a virtual warehouse when its credit usage reaches a defined limit and triggering a notification to account administrators when credit usage reaches a specified threshold. These actions help manage and control resource usage and costs within Snowflake.

References:

Snowflake Documentation: Resource Monitors

Which Snowflake native tool can be used to diagnose and troubleshoot network connections?

A.
SnowSQL
A.
SnowSQL
Answers
B.
Snowflake Python connector
B.
Snowflake Python connector
Answers
C.
Snowsight
C.
Snowsight
Answers
D.
SnowCD
D.
SnowCD
Answers
Suggested answer: A

Explanation:

SnowSQL, Snowflake's command-line client, can be used to diagnose and troubleshoot network connections. SnowSQL provides various commands and options to test connectivity, configure network settings, and troubleshoot issues related to network connections between the client and Snowflake.

References:

Snowflake Documentation: SnowSQL

Why would a Snowflake user load JSON data into a VARIANT column instead of a string column?

A.
A VARIANT column is more secure than a string column
A.
A VARIANT column is more secure than a string column
Answers
B.
A VARIANT column compresses data and a string column does not.
B.
A VARIANT column compresses data and a string column does not.
Answers
C.
A variant column can be used to create a data hierarchy and a string column cannot
C.
A variant column can be used to create a data hierarchy and a string column cannot
Answers
D.
A VARIANT column will have a better query performance than a string column.
D.
A VARIANT column will have a better query performance than a string column.
Answers
Suggested answer: C

Explanation:

A VARIANT column in Snowflake is specifically designed to store semi-structured data, such as JSON, and allows for the creation of a data hierarchy. Unlike string columns, VARIANT columns can natively handle JSON data structures, enabling complex querying and manipulation of hierarchical data using functions designed for semi-structured data.

References:

Snowflake Documentation: VARIANT Data

Which statistics on a Query Profile reflect the efficiency of the query pruning? (Select TWO).

A.
Partitions scanned
A.
Partitions scanned
Answers
B.
Partitions total
B.
Partitions total
Answers
C.
Bytes spilled
C.
Bytes spilled
Answers
D.
Bytes scanned
D.
Bytes scanned
Answers
E.
Bytes written
E.
Bytes written
Answers
Suggested answer: A, D

Explanation:

In a Snowflake Query Profile, the statistics 'Partitions scanned' and 'Bytes scanned' reflect the efficiency of query pruning. Query pruning refers to the ability of the query engine to skip unnecessary data, thereby reducing the amount of data that needs to be processed. Efficient pruning results in fewer partitions and bytes being scanned, improving query performance.

References:

Snowflake Documentation: Understanding Query Profiles

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