Free Snowflake COF-C02 Practice Exam with Questions & Answers | Set: 9

To provide a user with the necessary access to create a materialized view in a schema, the user must be granted a role that has the CREATE MATERIALIZED VIEW privilege on that schema. First, the role is granted to the user, and then the privilege is granted to the role

Snowflake uses a technique called pruning to limit the number of micro-partitions scanned by each query. Pruning effectively filters out unnecessary micro-partitions based on the query’s filter conditions, which can significantly improve query performance by reducing the amount of data scanned1.

 Snowflake’s secure data sharing feature allows sharing of certain database objects with other Snowflake accounts. Among the options provided, external tables and secure UDFs can be shared

 To grant a role the privilege to select data from all current and future tables in a schema, two separate commands are needed. The first command grants the SELECT privilege on all existing tables within the schema, and the second command grants the SELECT privilege on all tables that will be created in the future within the same schema. 

Assigning the custom role to the SYSADMIN role is considered a best practice because it allows the SYSADMIN role to manage objects created by the custom role. This is important for maintaining proper access control and ensuring that the SYSADMIN can perform necessary administrative tasks on objects created by users with the custom role.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Section 1.3 - SnowPro Core Certification Study Guide1

For data loading using Snowpipe, the recommended file size is a compressed file greater than 10 MB and up to 100 MB. This size range is optimal for Snowpipe’s continuous, micro-batch loading process, allowing for efficient and timely data ingestion without overwhelming the system with files that are too large or too small.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Snowpipe1

The PUT command is used to load data into an internal stage in Snowflake. This command uploads data files from a local file system to a named internal stage, making the data available for subsequent loading into a Snowflake table using the COPY INTO command.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Data Loading

 Snowflake Time Travel is a powerful feature that allows users to access historical data within a defined period. It enables two key capabilities:

B. Restoring data-related objects that have been deleted within the past 90 days: Time Travel can be used to restore tables, schemas, and databases that have been accidentally or intentionally deleted within the Time Travel retention period.

C. Conducting point-in-time analysis for BI reporting: It allows users to query historical data as it appeared at a specific point in time within the Time Travel retention period, which is crucial for business intelligence and reporting purposes.

While Time Travel does allow querying of past data, it is limited to the retention period set for the Snowflake account, which is typically 1 day for standard accounts and can be extended up to 90 days for enterprise accounts. It does not enable querying or restoring objects created or deleted beyond the retention period, nor does it provide analysis over all periods of time.

References:

Snowflake Documentation on Time Travel

SnowPro® Core Certification Study Guide

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

The Snowflake storage layer is responsible for storing data in an optimized, compressed, columnar format. This includes micro-partitions, which are the fundamental storage units that contain the actual data stored in Snowflake. Additionally, persisted query results, which are the results of queries that have been materialized and stored for future use, are also kept within this layer. This design allows for efficient data retrieval and management within the Snowflake architecture1.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Key Concepts & Architecture | Snowflake Documentation2

 Materialized views in Snowflake are a feature that allows for the pre-computation and storage of query results for faster query performance. This feature is available starting from the Enterprise Edition of Snowflake. It is not available in the Standard Edition, and while it is also available in higher editions like Business Critical and Virtual Private Snowflake, the Enterprise Edition is the minimum requirement.

References:

Snowflake Documentation on CREATE MATERIALIZED VIEW1.

Snowflake Documentation on Working with Materialized Views

https://docs.snowflake.com /en/sql-reference/sql/create-materialized-view.html#:~:text=Materialized%20views%20require%20Enterprise%20Edition,upgrading%2C%20please%20contact%20Snowflake%20Support.

In Snowflake, Cloud Services costs are incurred when the Cloud Services usage exceeds 10% of the compute usage (measured in credits). Therefore, scenarios A and E would result in Cloud Services charges because the Cloud Services usage is more than 10% of the compute credits used.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake’s official documentation on billing and usage1

The most efficient way to get files into Snowflake, especially when new files are being written to a cloud storage location at frequent intervals, is to use Snowpipe with auto-ingest. Snowpipe is Snowflake’s continuous data ingestion service that loads data as soon as it becomes available in a cloud storage location. By setting up cloud provider notifications, Snowpipe can be triggered automatically whenever new files are written to the storage location, ensuring that the data is loaded into Snowflake with minimal latency and without the need for manual intervention or scheduling frequent tasks.

References:

Snowflake Documentation on Snowpipe

SnowPro® Core Certification Study Guide

 The command list @mystage; is used to view the list of files that have been uploaded to an internal stage in Snowflake. The list command displays the metadata for all files in the specified stage, which in this case is mystage. This command is particularly useful for verifying that files have been successfully unloaded from a Snowflake table to the stage and for managing the files within the stage.

References:

Snowflake Documentation on Stages

SnowPro® Core Certification Study Guide

Snowflake’s Time Travel feature is used for both querying historical data in tables and restoring and cloning historical data in databases, schemas, and tables3. It allows users to access historical data within a defined period (1 day by default, up to 90 days for Snowflake Enterprise Edition) and is a key feature for data recovery and management. References: [COF-C02] SnowPro Core Certification Exam Study Guide