Snowflake Updated COF-C02 Exam Questions and Answers by addison

 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 .

 To view warehouse usage over time, the Query history view and the WAREHOUSE_METERING__HISTORY View can be utilized. The Query history view allows users to monitor the performance of their queries and the load on their warehouses over a specified period1. The WAREHOUSE_METERING__HISTORY View provides detailed information about the workload on a warehouse within a specified date range, including average running and queued loads2. References: [COF-C02] SnowPro Core Certification Exam Study Guide

A clustering key in Snowflake is used to co-locate similar data within the same micro-partitions to improve query performance, especially for large tables where data is not naturally ordered or has become fragmented due to extensive DML operations. The appropriate use of a clustering key can lead to improved scan efficiency and better column compression, resulting in faster query execution times.

The indicators that it may be appropriate to use a clustering key for a table include:

D. Queries on the table are running slower than expected: This can happen when the data in the table is not well-clustered, leading to inefficient scans during query execution.

E. The clustering depth for the table is large: A large clustering depth indicates that the table’s data is spread across many micro-partitions, which can degrade query performance as more data needs to be scanned.

References:

Snowflake Documentation on Clustering Keys & Clustered Tables

Snowflake Documentation on SYSTEM$CLUSTERING_INFORMATION

Stack Overflow discussion on cluster key selection in Snowflake

In Snowflake, Streams are the objects that track Data Manipulation Language (DML) changes made to tables, such as inserts, updates, and deletes. Streams record these changes along with metadata about each change, enabling actions to be taken using the changed data. This process is known as change data capture (CDC)2.