COF-C02 Exam Dumps - Snowflake SnowPro Core Certification Questions and Answers

The TABLE_STORAGE_METRICS metadata table stores the storage utilization information, including for tables that have been dropped but are still incurring storage costs2.

Multi-Factor Authentication (MFA) provides increased login security for users connecting to Snowflake. Snowflake’s MFA is powered by Duo Security service, which adds an additional layer of security during the login process.

Snowflake supports semi-structured data types that can store complex data structures within a single column. The VARIANT data type can hold structured and semi-structured data formats such as JSON, Avro, ORC, Parquet, and XML. The ARRAY data type is also used for semi-structured data and can store an ordered list of elements. These data types enable users to work with semi-structured data directly in Snowflake without needing to flatten the data into a relational schema first.References: Snowflake Documentation on Semi-Structured Data Types

In Snowflake, a role is an access control entity that can be created as part of a hierarchy within an account. Roles are used to grant and manage privileges in a structured and scalable manner.

Understanding Roles:

Roles are logical entities that group privileges together.

They are used to control access to securable objects like tables, views, warehouses, and more.

Role Hierarchy:

Roles can be organized into a hierarchy, allowing for the inheritance of privileges.

A role higher in the hierarchy (parent role) can grant its privileges to a lower role (child role), simplifying privilege management.

Creating Roles:

Roles can be created using the CREATE ROLE command.

You can define parent-child relationships by granting one role to another.

Example Usage:

CREATE ROLE role1;

CREATE ROLE role2;

GRANT ROLE role1 TO role2;

In this example, role2 inherits the privileges of role1.

Benefits:

Simplifies privilege management: Hierarchies allow for efficient privilege assignment and inheritance.

Enhances security: Roles provide a clear structure for managing access control, ensuring that privileges are granted appropriately.

References:

Snowflake Documentation: Access Control in Snowflake

Snowflake Documentation: Creating and Managing Roles

In Snowflake, configuring a virtual warehouse to be in a "Maximized" mode implies maximizing the resources allocated to the warehouse for its duration. This is done to ensure that the warehouse has a consistent amount of compute resources available, enhancing performance for workloads that require a high level of parallel processing or for handling high query volumes.

To configure a virtual warehouse in maximized mode, you should set the same value for both MIN_CLUSTER_COUNT and MAX_CLUSTER_COUNT. This configuration ensures that the warehouse operates with a fixed number of clusters, thereby providing a stable and maximized level of compute resources.

Reference to Snowflake documentation on warehouse sizing and scaling:

Warehouse Sizing and Scaling

Understanding Warehouses

Access History in Snowflake is a feature designed to support auditing by tracking access to data within Snowflake, including when a user's query reads column data. It provides detailed information on queries executed, including the user who ran the query, the query text, and the objects (e.g., tables, views) accessed by the query. This feature is instrumental for auditing purposes, helping organizations to monitor and audit data access for security and compliance.

The ACCOUNTADMIN role in Snowflake has the highest level of privileges, including the ability to manage accounts, users, roles, and all objects within the account. This role is specifically granted the permission to rename an account and specify whether the original URL can be used to access the renamed account. The ACCOUNTADMIN role encompasses broad administrative capabilities, ensuring that users assigned this role can perform critical account management tasks.References: Snowflake Documentation on Roles and Permissions

While Snowflake primarily deals with structured and semi-structured data, it also has the capability to handle unstructured data. Unstructured data can be stored in Snowflake using variants of SQL data types in tables, which can be permanent tables. These permanent tables, while traditionally used for structured or semi-structured data (like JSON, Avro, or Parquet), can also accommodate unstructured data in the form of binary formats or strings, offering flexibility in data storage and analysis. However, the management and querying of unstructured data in Snowflake may require additional considerations compared to structured data.References: Snowflake Documentation on Data Types

The MERGE command in Snowflake is used for incremental loading based on column values in a source table or subquery. It enables the insertion, updating, or deletion of records in a target table depending on whether matching rows are found, making it ideal for loading data that changes incrementally, such as daily updates or modifications.

OPERATE. In Snowflake, to pause or resume a pipe, the OPERATE privilege is required on the pipe object. The OPERATE privilege allows users to perform operational tasks on specific objects such as pipes, tasks, and streams. Specifically, for a pipe, the OPERATE privilege enables the user to execute the ALTER PIPE ... SET PIPE_EXECUTION_PAUSED=TRUE or ALTER PIPE ... SET PIPE_EXECUTION_PAUSED=FALSE commands, which are used to pause or resume the pipe, respectively.

Here's a step-by-step explanation and reference:

Understanding Pipe Operations: Pipes in Snowflake are used for continuous data loading from staging areas into Snowflake tables. Managing pipes involves operations such as creating, monitoring, pausing, and resuming.

Privileges for Pipe Operations: The OPERATE privilege is essential for pausing and resuming pipes. This privilege is more specific than general object access privileges like SELECT or USAGE and is tailored for operational control.

Granting the OPERATE Privilege: To grant the OPERATE privilege on a pipe, an administrator or a user with the necessary grants can execute the SQL command:

GRANT OPERATE ON PIPE TO ROLE ;

Pausing and Resuming Pipes: Once the OPERATE privilege is granted, the user or role can pause the pipe using:

ALTER PIPE SET PIPE_EXECUTION_PAUSED=TRUE;

To resume the pipe, they use:

ALTER PIPE SET PIPE_EXECUTION_PAUSED=FALSE;

 In Snowflake, when the account is located on Microsoft Azure, a valid source for an external stage can be an Azure container or a folder path within an Azure container. This includes Azure Blob storage which is accessible via the azure:// endpoint. A Windows server file share on Azure, if configured properly, can be a valid source for staging data files for Snowflake. Options A, B, and C are not supported as direct sources for an external stage in Snowflake on Azure12. References: [COF-C02] SnowPro Core Certification Exam Study Guide

 External stages can be altered and dropped in Snowflake. An external stage points to an external location, such as an S3 bucket, where data files are stored. Users can modify the stage’s definition or drop it entirely if it’s no longer needed. This is in contrast to table stages, which are tied to specific tables and cannot be altered or dropped independently.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Stages1

 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.

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 external tables are read-only, which means data manipulation language (DML) operations like INSERT, RENAME, or ALTER cannot be performed on them. However, external tables can be used for query and join operations3.

References: [COF-C02] SnowPro Core Certification Exam Study Guide