Snowflake SnowPro Core Practice Test - Questions Answers, Page 54

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.

Parquet is a columnar storage file format that is optimized for efficiency in both storage and processing. It supports compression and encoding schemes that significantly reduce the storage space needed and speed up data retrieval operations, making it ideal for handling large volumes of data. Unlike JSON or TSV, which are row-oriented and typically uncompressed, Parquet is designed specifically for use with big data frameworks, offering advantages in terms of performance and cost when storing and querying semi-structured data.

Reference: Apache Parquet Documentation

The search optimization service in Snowflake enhances query performance by maintaining a persistent data structure. This structure indexes the values of table columns across micro-partitions, allowing Snowflake to quickly identify which micro-partitions contain relevant data for a query. By efficiently narrowing down the search space, this service reduces the amount of data scanned during query execution, leading to faster response times and more efficient use of resources.

Reference: Snowflake Documentation on Search Optimization Service

Snowflake implements Discretionary Access Control (DAC) by using a role-based access control model. In this model, access privileges are not directly assigned to individual objects or users but are encapsulated within roles. These roles are then assigned to users, effectively granting them the access privileges contained within the role. This approach allows for granular control over database access, making it easier to manage permissions in a scalable and flexible manner.

Reference: Snowflake Documentation on Access Control

In Snowflake, the consumption of credits by a virtual warehouse is determined by its size and the duration for which it runs. A size 3X-Large virtual warehouse consumes 128 credits if it runs continuously for 2 hours. This consumption rate is based on the principle that larger warehouses, capable of providing greater computational resources and throughput, consume more credits per hour of operation. The specific rate of consumption is defined by Snowflake's pricing model and the scale of the virtual warehouse.

Reference: Snowflake Pricing Documentation

The REMOVE command is used in Snowflake to delete files from a stage after they have been successfully ingested into Snowflake tables. This command helps manage storage by allowing users to clean up staged files that are no longer needed, ensuring that the stage does not accumulate unnecessary data over time. Unlike DELETE, DROP, or TRUNCATE commands, which are used for managing data within Snowflake tables or dropping objects, REMOVE specifically targets the management of files in stages.

Reference: Snowflake Documentation on Stages and File Management

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.

Reference: Snowflake Documentation on Data Types

When a virtual warehouse in Snowflake is suspended, the cache is dropped and is no longer available upon restart. This means that all cached data, including results and temporary data, are cleared from memory. The purpose of this behavior is to conserve resources while the warehouse is not active. Upon restarting the warehouse, it will need to reload any data required for queries from storage, which may result in a slower initial performance until the cache is repopulated. This is a critical consideration for managing performance and cost in Snowflake.

In Snowflake, network policies define the allowed IP address ranges from which users can connect to Snowflake, enhancing security by restricting access based on network location. The creation and management of network policies require sufficient privileges. Specifically, a user with the SECURITYADMIN role or any role with higher privileges, such as ACCOUNTADMIN, can create network policies. Additionally, a custom role can be granted the CREATE NETWORK POLICY privilege, enabling users assigned to that role to also create network policies. This approach allows for flexible and secure management of network access to Snowflake.

Reference: Snowflake Documentation on Network Policies