COF-C02 Exam Dumps - Snowflake SnowPro Core Certification Questions and Answers

The Query Profile statistics that indicate intermediate results do not fit in memory are the bytes spilled to local storage and bytes spilled to remote storage2.

A Stream object in Snowflake is used for change data capture (CDC), which records data manipulation language (DML) changes made to tables, including inserts, updates, and deletes3.

The search optimization service in Snowflake is designed to improve the performance of selective point lookup queries on large tables, which is ideal for scenarios where a query returns a small amount of data from a very large base table1. References: [COF-C02] SnowPro Core Certification Exam Study Guide

 The TO_JSON function is used to convert a VARIANT value into a string containing the JSON representation of the value. This function is suitable for unloading data from a relational table to JSON format. References: [COF-C02] SnowPro Core Certification Exam Study Guide

 A masking policy in Snowflake consists of a single data type, with one or more conditions, and one or more masking functions. These components define how the data is masked based on the specified conditions3.

 In Snowflake, if a temporary table and a permanent table have the same name within the same schema, the temporary table takes precedence over the permanent table within the session where the temporary table was created4.

Micro-partitioning is a Snowflake function that is maintained separately from the data and supports features such as Time Travel, Secure Data Sharing, and pruning. It allows Snowflake to efficiently manage and query large datasets by organizing them into micro-partitions1.

The LATERAL modifier for the FLATTEN function allows joining information outside the object (such as other columns in the source table) with the flattened data, creating a lateral view that correlates with the preceding tables in the FROM clause2345. References: [COF-C02] SnowPro Core Certification Exam Study Guide

The purpose of a Query Profile is to provide a detailed analysis of a particular query’s execution plan, including the mechanics, behavior, and performance. It helps in identifying potential performance bottlenecks and areas for optimization

The ACCESS_HISTORY view in Snowflake is utilized to support compliance auditing. It provides detailed information on data access within Snowflake, including reads and writes by user queries. This view is essential for regulatory compliance auditing as it offers insights into the usage of tables and columns, and maintains a direct link between the user, the query, and the accessed data1.

References: [COF-C02] SnowPro Core Certification Exam Study Guide

The LOOP type of loop in Snowflake Scripting does not have a built-in termination condition and requires a BREAK statement to stop executing4.

 Once an internal stage is dropped in Snowflake, it cannot be recovered or restored using Time Travel or UNDROP commands. The only option is to recreate the dropped stage

When federated authentication is activated in Snowflake, users authenticate via an external identity provider (IdP) rather than using Snowflake-managed credentials. Therefore, a user with a password defined by Snowflake will be unable to enter a password and must use their IdP credentials to log in.

QUSTION NO: 579

What value provides information about disk usage for operations where intermediate results do not fit in memory in a Query Profile?

A. IO

B. Network

C. Pruning

D. Spilling

Answer: D

In Snowflake, when a query execution requires more memory than what is available, Snowflake handles these situations by spilling the intermediate results to disk. This process is known as "spilling." The Query Profile in Snowflake includes a metric that helps users identify when and how much data spilling occurs during the execution of a query. This information is crucial for optimizing queries as excessive spilling can significantly slow down query performance. The value that provides this information about disk usage due to intermediate results not fitting in memory is appropriately labeled as "Spilling" in the Query Profile.

References:

Snowflake Documentation on Query Profile and Performance: This section explains the various components of the query profile, including the spilling metric, which indicates disk usage for operations where intermediate results exceed available memory.

When using the ALLOW_CLIENT_MFA_CACHING parameter, a cached Multi-Factor Authentication (MFA) token is valid for up to 4 hours. This allows for continuous, secure connectivity without users needing to respond to an MFA prompt at the start of each connection attempt to Snowflake within this timeframe2.

 A Query Profile provides detailed execution information for a query, which can be used to analyze the performance and behavior of queries. This information can help users optimize and right-size their virtual warehouses for better efficiency. References: [COF-C02] SnowPro Core Certification Exam Study Guide