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

To go back to the first version of a transient table created three days prior, one can use Time Travel if the DATA_RETENTION_TIME_IN_DAYS was set to at least 3 days. This allows the user to access historical data within the specified retention period. References: [COF-C02] SnowPro Core Certification Exam Study Guide

 The GET command is used to download files from a Snowflake stage to a local folder on a client’s machine2.

 In Snowflake’s access control model, the default owner of an object is the role that was used to create the object. This role has the OWNERSHIP privilege on the object and can grant access to other roles1

The ResultSet cache is leveraged to quickly return results for repeated queries. Actions that prevent leveraging this cache include stopping the virtual warehouse that the query is running against (B) and executing the RESULTS_SCAN() table function (D). Stopping the warehouse clears the local disk cache, including the ResultSet cache1. The RESULTS_SCAN() function is used to retrieve the result of a previously executed query, which bypasses the need for the ResultSet cache.

 In the Snowflake Enterprise Edition, the default Time Travel retention is set to 1 day, the maximum Time Travel retention can be set up to 90 days, and the Fail-safe retention time is 7 days3.

 The Snowflake Cloud Services layer manages various services, including authentication and metadata management. This layer ties together all the different components of Snowflake to process user requests, manage sessions, and control access3.

Snowflake recommends file sizes between 100-250 MB compressed when loading data to optimize parallel processing. Smaller, compressed files can be loaded in parallel, which maximizes the efficiency of the virtual warehouses and speeds up the data loading process

 The credit consumption for maintaining a materialized view is impacted by how often the base table changes © and whether the materialized view has a cluster key defined (D). Changes to the base table can trigger a refresh of the materialized view, consuming credits. Additionally, having a cluster key defined can optimize the performance and credit usage during the materialized view’s maintenance. References: SnowPro Core Certification materialized view credit consumption

A multi-cluster warehouse should be used in auto-scaling mode when there is a need to handle a large number of concurrent queries. Auto-scaling allows Snowflake to automatically add or remove compute clusters to balance the load, ensuring that performance remains consistent during varying levels of demand

The maximum Time Travel retention period for a temporary Snowflake table is 1 day. This is the standard retention period for temporary tables, which allows for accessing historical data within a 24-hour window

The Snowflake Cloud Services layer performs a variety of tasks, including the management of metadata and the parsing and optimization of queries. This layer is responsible for coordinating activities across Snowflake, including user session management, security, and query compilation3.

The Enterprise edition of Snowflake allows for a dedicated metadata store, providing additional features designed for large-scale enterprises

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:

CREATE TABLE my_table (... ) CLUSTER BY (column1, column2);

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ALTER TABLE my_table CLUSTER BY (column1, column2);

https://docs.snowflake.com/en/sql-reference/data-sharing-usage

Worksheets in Snowsight can be shared directly with other Snowflake users within the same account. This feature allows for collaboration and sharing of SQL queries or Python code, as well as other data manipulation tasks1.