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The Snowpark API allows developers to create User-Defined Functions (UDFs) in various languages, including Python, which is known for its ease of use and wide adoption in data-related tasks.Reference:Based on general programming and cloud data service knowledge as of 2021.

The SnowSQL file that can store connection information is named 'config'. It is used to store user credentials and connection details for easy access to Snowflake instances.Reference:Based on general database knowledge as of 2021.

Snowflake reorganizes data into its internal optimized, compressed, columnar format in the Database Storage layer.This process is part of how Snowflake manages data storage, ensuring efficient data retrieval and query performance

Even if a developer is granted ownership of a table with a masking policy, they will not be able to modify the table to read the masked data if their role does not have the necessary permissions. Ownership of a table does not automatically confer the ability to alter masking policies, which are designed to protect sensitive data.Masking policies are applied at the schema level and require specific privileges to modify12.[COF-C02] SnowPro Core Certification Exam Study GuideSnowflake Documentation on Masking Policies

Parquet is a columnar storage file format that is optimized for performance in Snowflake. It is designed to be efficient for both storage and query performance, particularly for complex queries on large datasets. Parquet files support efficient compression and encoding schemes, which can lead to significant savings in storage and speed in query processing, making it the most performant file format for loading data into Snowflake.[COF-C02] SnowPro Core Certification Exam Study GuideSnowflake Documentation on Data Loading1

The Information Schema and Account Usage Share in Snowflake provide metadata and historical usage data for various objects within a Snowflake account. Specifically, they offer storage information forTables,Databases, andInternal Stages. These schemas contain views and table functions that allow users to query object metadata and usage metrics, such as the amount of data stored and historical activity.Tables: The storage information includes data on the daily average amount of data in database tables.Databases: For databases, the storage usage is calculated based on all the data contained within the database, including tables and stages.Internal Stages: Internal stages are locations within Snowflake for temporarily storing data, and their storage usage is also tracked.

Reader accounts in Snowflake are designed to allow users to read data shared with them but do not have the capability to extract data for use outside of Snowflake. They are intended for consuming shared data within the Snowflake environment only.

Separate and distinct from Time Travel, Fail-safe ensures historical data is protected in the event of a system failure or other catastrophic event, e.g. a hardware failure or security breach. Fail-safe feature cannot be enabled or disabled from the user end.

The auto-suspend and auto-resume settings in Snowflake apply to the entire virtual warehouse. These settings allow the warehouse to automatically suspend when it's not in use, helping to save on compute costs. When queries or tasks are submitted to the warehouse, it can automatically resume operation. This functionality is designed to optimize resource usage and cost-efficiency.SnowPro Core Certification Exam Study Guide (as of 2021)Snowflake documentation on virtual warehouses and their settings (as of 2021)

When aCLUSTER BYclause is added to a Snowflake table, it specifies one or more columns to organize the data within the table's micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.Snowflake Documentation on Clustering Keys & Clustered Tables1.Community discussions on how source data's ordering affects a table with a cluster key