What are the main differences between the account usage views and the information schema views? (Select TWO).
No active warehouse to needed to query account usage views but one is needed to query information schema views.
Account usage views do not contain data about tables but information schema views do.
Account issue views contain dropped objects but information schema views do not.
Data retention for account usage views is 1 year but is 7 days to 6 months for information schema views, depending on the view.
Information schema views are read-only but account usage views are not.
The account usage views in Snowflake provide historical usage data about the Snowflake account, and they retain this data for a period of up to 1 year. These views include information about dropped objects, enabling audit and tracking activities. On the other hand, information schema views provide metadata about database objects currently in use, such as tables and views, but do not include dropped objects. The retention of data in information schema views varies, but it is generally shorter than the retention for account usage views, ranging from 7 days to a maximum of 6 months, depending on the specific view.References: Snowflake Documentation on Account Usage and Information Schema
What is the MINIMUM size requirement when creating a Snowpark-optimized virtual warehouse?
X-Small
Small
Medium
Large
When creating a Snowpark-optimized virtual warehouse in Snowflake, the minimum size requirement is Small. Snowpark is designed to handle data processing workloads efficiently, and the Small size ensures adequate resources for such tasks.
Virtual Warehouse Sizes:
Snowflake offers different sizes for virtual warehouses, ranging from X-Small to 6X-Large.
Each size corresponds to a specific level of compute resources.
Minimum Size Requirement for Snowpark:
A Small virtual warehouse is the minimum size required to optimize performance and resource allocation for Snowpark workloads.
This ensures that the warehouse has sufficient capacity to handle data processing and transformation tasks efficiently.
References:
Snowflake Documentation: Virtual Warehouse Sizes
While preparing to unload data in Snowflake, the file format option can be specified in which commands? (Select TWO).
GET
CREATE STAGE
PUT
COPY INTO
CREATE PIPE
The file format option in Snowflake can be specified in the following commands:
CREATE STAGE: This command allows users to define the file format when creating a stage, which applies to any data loaded or unloaded via that stage.
COPY INTO <location>: This command enables data export from a table to an external location, where the file format can be specified to ensure the data is structured as needed for downstream systems.
Other commands, such as PUT or GET, do not support the specification of file formats directly within the command syntax.
What is the MINIMUM size of a table for which Snowflake recommends considering adding a clustering key?
1 Kilobyte (KB)
1 Megabyte (MB)
1 Gigabyte (GB)
1 Terabyte (TB)
Snowflake recommends considering adding a clustering key to a table when its size reaches 1 Terabyte (TB) or larger. Clustering keys help optimize the storage and query performance by organizing the data in a table based on the specified columns. This is particularly beneficial for large tables where data retrieval can become inefficient without proper clustering.
Why Clustering Keys Are Important: Clustering keys ensure that data stored in Snowflake is physically ordered in a way that aligns with the most frequent access patterns, thereby reducing the amount of scanned data during queries and improving performance.
Recommendation Basis: The recommendation for tables of size 1 TB or larger is based on the observation that smaller tables generally do not benefit as much from clustering, given Snowflake's architecture. However, as tables grow in size, the benefits of clustering become more pronounced.
Implementing Clustering Keys:
To set a clustering key for a table, you can use the CLUSTER BY clause during table creation or alter an existing table to add it:
CREATE TABLE my_table (... ) CLUSTER BY (column1, column2);
Or for an existing table:
ALTER TABLE my_table CLUSTER BY (column1, column2);
What action should be taken if a Snowflake user wants to share a newly created object in a database with consumers?
Use the automatic sharing feature for seamless access.
Drop the object and then re-add it to the database to trigger sharing.
Recreate the object with a different name in the database before sharing.
Use the grant privilege ... TO share command to grant the necessary privileges.
When a Snowflake user wants to share a newly created object in a database with consumers, the correct action to take is to use the GRANT privilege ... TO SHARE command to grant the necessary privileges for the object to be shared. This approach allows the object owner or a user with the appropriate privileges to share database objects such as tables, secure views, and streams with other Snowflake accounts by granting access to a named share.
The GRANT statement specifies which privileges are granted on the object to the share. The object remains in its original location; sharing does not duplicate or move the object. Instead, it allows the specified share to access the object according to the granted privileges.
For example, to share a table, the command would be:
GRANT SELECT ON TABLE new_table TO SHARE consumer_share;
This command grants the SELECT privilege on a table named new_table to a share named consumer_share, enabling the consumers of the share to query the table.
Automatic sharing, dropping and re-adding the object, or recreating the object with a different name are not required or recommended practices for sharing objects in Snowflake. The use of the GRANT statement to a share is the direct and intended method for this purpose.
Why is a federated environment used for user authentication in Snowflake?
To enhance data security and privacy
To provide real-lime monitoring of user activities
To separate user authentication from user access
To enable direct integration with external databases
Which key access control concept does Snowflake descibe as a defined level of access to an object?
Grant
Privilege
Role
Session
In Snowflake, the term "privilege" refers to a defined level of access to an object. Privileges are specific actions that roles can perform on securable objects in Snowflake, such as tables, views, warehouses, databases, and schemas. These privileges are granted to roles and can be further granted to users through their roles, forming the basis of Snowflake’s access control framework.References: Snowflake Documentation on Access Control Privileges
What is a characteristic of a tag associated with a masking policy?
A tag can be dropped after a masking policy is assigned
A tag can have only one masking policy for each data type.
A tag can have multiple masking policies for each data type.
A tag can have multiple masking policies with varying data types
In Snowflake, a tag can be associated with only one masking policy for each data type. This means that for a given data type, you can define a single masking policy to be applied when a tag is used. Tags and masking policies are part of Snowflake's data classification and governance features, allowing for data masking based on the context defined by the tags.
References:
Snowflake Documentation: Tag-Based Masking Policies
When an object is created in Snowflake. who owns the object?
The public role
The user's default role
The current active primary role
The owner of the parent schema
In Snowflake, when an object is created, it is owned by the role that is currently active. This active role is the one that is being used to execute the creation command. Ownership implies full control over the object, including the ability to grant and revoke access privileges. This is specified in Snowflake's documentation under the topic of Access Control, which states that "the role in use at the time of object creation becomes the owner of the object."
References:
Snowflake Documentation: Object Ownership
What is the benefit of using the STRIP_OUTER_ARRAY parameter with the COPY INTO
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