COF-C02 Exam Dumps - SnowPro Core Certification Exam

Storing non-native values, such as dates and timestamps, in a VARIANT column in Snowflake can lead to slower query performance and increased storage consumption. VARIANT is a semi-structured data type that allows storing JSON, AVRO, ORC, Parquet, or XML data in a single column. When non-native data types are stored as VARIANT, Snowflake must perform implicit conversion to process these values, which can slow down query execution. Additionally, because the VARIANT data type is designed to accommodate a wide variety of data formats, it often requires more storage space compared to storing data in native, strongly-typed columns that are optimized for specific data types.

The performance impact arises from the need to parse and interpret the semi-structured data on the fly during query execution, as opposed to directly accessing and operating on optimally stored data in its native format. Furthermore, the increased storage consumption is a result of the overhead associated with storing data in a format that is less space-efficient than the native formats optimized for specific types of data.

References:

Snowflake Documentation on Semi-Structured Data: Semi-Structured Data

Snowflake uses both Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) to manage access control. DAC allows object owners to grant access privileges to other users. RBAC assigns permissions to roles, and roles are then granted to users, making it easier to manage permissions based on user roles within the organization.

References:

Snowflake Documentation: Access Control in Snowflake

In Snowflake, the system-defined, read-only view that displays information on column lineage, which specifies how data flows from source to target in a SQL write operation, is ACCESS_HISTORY. This view is instrumental in auditing and analyzing data access patterns, as it provides detailed insights into how and from where the data is being accessed and manipulated within Snowflake.

Reference to Snowflake documentation on ACCESS_HISTORY:

Using Access History to Audit Data Access

When a query containing a WHERE clause is running longer than expected, and the Query Profile shows that all micro-partitions are being scanned, the query can be optimized by adding a clustering key to the table.

Understanding Micro-Partitioning in Snowflake:

Snowflake automatically partitions tables into micro-partitions for efficient storage and query performance.

Each micro-partition contains metadata about the range of values it holds, which helps in pruning irrelevant partitions during query execution.

Role of Clustering Keys:

A clustering key defines how data in a table is organized within micro-partitions.

By specifying a clustering key, you can control the physical layout of data, ensuring that related rows are stored together.

This organization improves query performance by reducing the number of micro-partitions that need to be scanned.

Optimizing Queries with Clustering Keys:

Adding a clustering key based on columns frequently used in WHERE clauses helps Snowflake quickly locate and scan relevant micro-partitions.

This minimizes the amount of data scanned and reduces query execution time.

Example:

ALTER TABLE my_table CLUSTER BY (column1, column2);

This command adds a clustering key to my_table using column1 and column2.

Future queries that filter on these columns will benefit from improved performance.

Benefits:

Reduced query execution time: Fewer micro-partitions need to be scanned.

Improved resource utilization: More efficient data retrieval leads to lower compute costs.

References:

Snowflake Documentation: Clustering Keys

Snowflake Documentation: Query Profile

To list all network policies available in an account, the correct command is SHOW NETWORK POLICIES. Network policies in Snowflake are used to define and enforce rules for how users can connect to Snowflake, including IP whitelisting and other connection requirements. The SHOW NETWORK POLICIES command provides a list of all network policies defined within the account, along with their details.

The DESCRIBE SESSION POLICY and DESCRIBE NETWORK POLICY commands do not exist in Snowflake SQL syntax. The SHOW SESSION POLICIES command is also incorrect, as it does not pertain to the correct naming convention used by Snowflake for network policy management.

Using SHOW NETWORK POLICIES without any additional parameters will display all network policies in the account, which is useful for administrators to review and manage the security configurations pertaining to network access.

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

In Snowflake, cloning is available for certain types of objects, allowing quick duplication without copying data:

Schemas: These can be cloned, enabling users to replicate entire schema structures, including tables and views, for development or testing.

Internal named stages: These stages, used to store data files within Snowflake, can also be cloned, preserving configurations for data loading.

Users and external objects (like external stages or tables) cannot be cloned due to their dependency on external data and configurations outside Snowflake.

The type of Snowflake table that persists until it is explicitly dropped, is available for all users with relevant privileges across sessions, and does not have a Fail-safe period, is a Transient table. Transient tables are designed to provide temporary storage similar to permanent tables but with some reduced storage costs and without the Fail-safe feature, which provides additional data protection for a period beyond the retention time. Transient tables are useful in scenarios where data needs to be temporarily stored for longer than a session but does not require the robust durability guarantees of permanent tables.