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Snowflake COF-C02 Practice Test - Questions Answers, Page 47

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Question 461

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How are network policies defined in Snowflake?

They are a set of rules that define the network routes within Snowflake.
They are a set of rules that define the network routes within Snowflake.
They are a set of rules that dictate how Snowflake accounts can be used between multiple users.
They are a set of rules that dictate how Snowflake accounts can be used between multiple users.
They are a set of rules that define how data can be transferred between different Snowflake accounts within an organization.
They are a set of rules that define how data can be transferred between different Snowflake accounts within an organization.
They are a set of rules that control access to Snowflake accounts by specifying the IP addresses or ranges of IP addresses that are allowed to connect to Snowflake.
They are a set of rules that control access to Snowflake accounts by specifying the IP addresses or ranges of IP addresses that are allowed to connect to Snowflake.
Suggested answer: D

Explanation:

Network policies in Snowflake are defined as a set of rules that manage the network-level access to Snowflake accounts. These rules specify which IP addresses or IP ranges are permitted to connect to Snowflake, enhancing the security of Snowflake accounts by preventing unauthorized access. Network policies are an essential aspect of Snowflake's security model, allowing administrators to enforce access controls based on network locations.

References:

Snowflake Documentation: Network Policies

asked 23/09/2024
FL Ferdous Attaie
36 questions

Question 462

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What is the MAXIMUM number of clusters that can be provisioned with a multi-cluster virtual warehouse?

1
1
5
5
10
10
100
100
Suggested answer: C

Explanation:

In Snowflake, the maximum number of clusters that can be provisioned within a multi-cluster virtual warehouse is 10. This allows for significant scalability and performance management by enabling Snowflake to handle varying levels of query load by adjusting the number of active clusters within the warehouse. References: Snowflake documentation on virtual warehouses, particularly the scalability options available in multi-cluster configurations.

asked 23/09/2024
Arvind Prasad S
41 questions

Question 463

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The effects of query pruning can be observed by evaluating which statistics? (Select TWO).

Partitions scanned
Partitions scanned
Partitions total
Partitions total
Bytes scanned
Bytes scanned
Bytes read from result
Bytes read from result
Bytes written
Bytes written
Suggested answer: A, C

Explanation:

Query pruning in Snowflake refers to the optimization technique where the system reduces the amount of data scanned by a query based on the query conditions. This typically involves skipping unnecessary data partitions that do not contribute to the query result. The effectiveness of this technique can be observed through:

Option A: Partitions scanned. This statistic indicates how many data partitions were actually scanned as a result of query pruning, showing the optimization in action.

Option C: Bytes scanned. This measures the volume of data physically read during query execution, and a reduction in this number indicates effective query pruning, as fewer bytes are read when unnecessary partitions are skipped.

Options B, D, and E do not directly relate to observing the effects of query pruning. 'Partitions total' shows the total available, not the impact of pruning, while 'Bytes read from result' and 'Bytes written' relate to output rather than the efficiency of data scanning. References: Snowflake documentation on performance tuning and query optimization techniques, specifically how query pruning affects data access.

asked 23/09/2024
Gilbert Mendoza
38 questions

Question 464

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What is the default value in the Snowflake Web Interface (Ul) for auto suspending a Virtual Warehouse?

1 minutes
1 minutes
5 minutes
5 minutes
10 minutes
10 minutes
15 minutes
15 minutes
Suggested answer: C

Explanation:

The default value for auto-suspending a Virtual Warehouse in the Snowflake Web Interface (UI) is 10 minutes. This setting helps manage compute costs by automatically suspending warehouses that are not in use, ensuring that compute resources are efficiently allocated and not wasted on idle warehouses.

References:

Snowflake Documentation: Virtual Warehouses

asked 23/09/2024
Mike de Roo
29 questions

Question 465

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When unloading data, which file format preserves the data values for floating-point number columns?

Avro
Avro
CSV
CSV
JSON
JSON
Parquet
Parquet
Suggested answer: D

Explanation:

When unloading data, the Parquet file format is known for its efficiency in preserving the data values for floating-point number columns. Parquet is a columnar storage file format that offers high compression ratios and efficient data encoding schemes. It is especially effective for floating-point data, as it maintains high precision and supports efficient querying and analysis.

References:

Snowflake Documentation: Using the Parquet File Format for Unloading Data

asked 23/09/2024
Scott McNeill
32 questions

Question 466

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A user has semi-structured data to load into Snowflake but is not sure what types of operations will need to be performed on the data. Based on this situation, what type of column does Snowflake recommend be used?

ARRAY
ARRAY
OBJECT
OBJECT
TEXT
TEXT
VARIANT
VARIANT
Suggested answer: D

Explanation:

When dealing with semi-structured data in Snowflake, and the specific types of operations to be performed on the data are not yet determined, Snowflake recommends using the VARIANT data type. The VARIANT type is highly flexible and capable of storing data in multiple formats, including JSON, AVRO, BSON, and more, within a single column. This flexibility allows users to perform various operations on the data, including querying and manipulation of nested data structures without predefined schemas.

References:

Snowflake Documentation: Semi-structured Data Types

asked 23/09/2024
Jaimie Lloyd
39 questions

Question 467

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Which activities are included in the Cloud Services layer? {Select TWO).

Data storage
Data storage
Dynamic data masking
Dynamic data masking
Partition scanning
Partition scanning
User authentication
User authentication
Infrastructure management
Infrastructure management
Suggested answer: D, E

Explanation:

The Cloud Services layer in Snowflake is responsible for a wide range of services that facilitate the management and use of Snowflake, including:

D . User authentication: This service handles identity and access management, ensuring that only authorized users can access Snowflake resources.

E . Infrastructure management: This service manages the allocation and scaling of resources to meet user demands, including the management of virtual warehouses, storage, and the orchestration of query execution.

These services are part of Snowflake's fully managed, cloud-based architecture, which abstracts and automates many of the complexities associated with data warehousing.

References:

Snowflake Documentation: Overview of Snowflake Cloud Services

asked 23/09/2024
Maritza Van Der Merwe
36 questions

Question 468

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How long is a query visible in the Query History page in the Snowflake Web Interface (Ul)?

60 minutes
60 minutes
24 hours
24 hours
14 days
14 days
30 days
30 days
Suggested answer: C

Explanation:

In the Snowflake Web Interface (UI), the Query History page displays the history of queries executed in Snowflake for up to 14 days. This allows users to review and analyze their query performance, troubleshoot issues, and understand their query patterns over a two-week period. The Query History page is a critical tool for monitoring and optimizing the use of Snowflake.

References:

Snowflake Documentation: Using the Web Interface

asked 23/09/2024
Nicholas Roy
43 questions

Question 469

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Which Snowflake mechanism is used to limit the number of micro-partitions scanned by a query?

Caching
Caching
Cluster depth
Cluster depth
Query pruning
Query pruning
Retrieval optimization
Retrieval optimization
Suggested answer: C

Explanation:

Query pruning in Snowflake is the mechanism used to limit the number of micro-partitions scanned by a query. By analyzing the filters and conditions applied in a query, Snowflake can skip over micro-partitions that do not contain relevant data, thereby reducing the amount of data processed and improving query performance. This technique is particularly effective for large datasets and is a key component of Snowflake's performance optimization features.

References:

Snowflake Documentation: Query Performance Optimization

asked 23/09/2024
Coleman Owie
39 questions

Question 470

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How does a Snowflake user extract the URL of a directory table on an external stage for further transformation?

Use the SHOW STAGES command.
Use the SHOW STAGES command.
Use the DESCRIBE STAGE command.
Use the DESCRIBE STAGE command.
Use the GET_ABSOLUTE_PATH function.
Use the GET_ABSOLUTE_PATH function.
Use the GET_STAGE_LOCATION function.
Use the GET_STAGE_LOCATION function.
Suggested answer: C

Explanation:

To extract the URL of a directory table on an external stage for further transformation in Snowflake, the GET_ABSOLUTE_PATH function can be used. This function returns the full path of a file or directory within a specified stage, enabling users to dynamically construct URLs for accessing or processing data stored in external stages.

References:

Snowflake Documentation: Working with Stages

asked 23/09/2024
Alfred Macaraeg
31 questions
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