Snowflake Updated COF-C02 Exam Questions and Answers by alfie-james

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, a table's clustering depth indicates the degree of micro-partition overlap based on the clustering keys defined for the table. A clustering depth of 1 implies that the table has no overlapping micro-partitions. This is an optimal scenario, indicating that the table's data is well-clustered according to the specified clustering keys. Well-clustered data can lead to more efficient query performance, as it reduces the amount of data scanned during query execution and improves the effectiveness of data pruning.

References:

• Snowflake Documentation on Clustering: Understanding Clustering Depth

Snowflake's Streams feature is specifically designed for change data capture (CDC). A stream records insert, update, and delete operations performed on a table, and allows users to query these changes. This enables actions to be taken on the changed data, facilitating processes like incremental data loads and real-time analytics. Streams provide a powerful mechanism for applications to respond to data changes in Snowflake tables efficiently.References: Snowflake Documentation on Streams

In Snowflake, the system-defined, read-only view that displays information on column lineage, which specifies how data flows from source to target in a SQL write operation, is ACCESS_HISTORY. This view is instrumental in auditing and analyzing data access patterns, as it provides detailed insights into how and from where the data is being accessed and manipulated within Snowflake.

Reference to Snowflake documentation on ACCESS_HISTORY:

• Using Access History to Audit Data Access