Pass the Snowflake SnowPro Core Certification Exam COF-C02 Questions and answers with ValidTests

The Cloud Services layer in Snowflake is responsible for managing the result cache. When a query is executed, the results are stored in this cache, and subsequent identical queries can leverage these cached results without re-executing the entire query1.

The Search Optimization Service significantly improves the performance of selective point lookup queries on tables by creating and maintaining a persistent data structure called a search access path, which allows some micro-partitions to be skipped when scanning the table

An explain plan is beneficial because it allows for the evaluation of how a query will be processed without the need to actually execute the query. This can help in understanding the query’s performance implications and potential bottlenecks without consuming resources that would be used if the query were run

 When cloning a database in Snowflake, the clone includes all privileges on the database as well as existing child objects within the database, such as schemas, tables, views, etc. However, it does not include future child objects or privileges on schemas within the database2.

References = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation

The Snowflake Search Optimization Service is designed to support improved performance for selective point lookup queries. These are queries that retrieve specific records from a database, often based on a unique identifier or a small set of criteria3.

 Data encryption and Time Travel are part of Snowflake’s Continuous Data Protection (CDP) feature set that do not require additional configuration. Data encryption is automatically applied to all files stored on internal stages, and Time Travel allows for querying and restoring data without any extra setup

 Scaling out in Snowflake involves adding clusters of the same size to a virtual warehouse, which allows for handling more concurrent queries without affecting the performance of individual queries. Scaling up refers to resizing a virtual warehouse to increase its compute resources, enabling it to handle more complex workloads and larger queries more efficiently.

 By default, the Snowflake role required to create a share is ACCOUNTADMIN (D). This role has the necessary privileges to perform administrative tasks, including creating shares for data sharing purposes

Multi-cluster virtual warehouses in Snowflake are designed to manage user and query concurrency needs. They allow for the allocation of additional clusters of compute resources, either statically or dynamically, to handle increased loads and reduce or eliminate the queuing of concurrent queries2.

https://docs.snowflake.com/en/user-guide/warehouses-multicluste r.html#:~:text=Multi%2Dcluster%20warehouses%20enable%20you,during%20peak%20and%20off%20hours.

 Users are responsible for data storage costs in Snowflake until the data expires from the Fail-safe period. Fail-safe is the final stage in the data lifecycle, following Time Travel, and provides additional protection against accidental data loss. Once data exits the Fail-safe state, users are no longer billed for its storage

The list @my_stage command in Snowflake can be used to verify if data has been uploaded to an external stage named my_stage. This command provides a list of files that are present in the specified stage2.

Snowflake’s architecture is designed to operate entirely on cloud infrastructure. It uses the core compute and storage services of each cloud provider, which allows it to leverage the scalability and reliability of cloud resources. Snowflake’s services are deployed across multiple availability zones within a cloud provider’s region to ensure high availability and fault tolerance. References: [COF-C02] SnowPro Core Certification Exam Study Guide

 In Snowflake, a task allows a user to execute a single SQL statement/command using a predefined schedule (B). Tasks are used to automate the execution of SQL statements at scheduled intervals.

A well-clustered table in Snowflake means that the data is organized in such a way that related data points are stored close to each other within the micro-partitions. This optimizes query performance by reducing the amount of scanned data. The diagram indicated by option C shows a well-clustered table, as it likely represents a more evenly distributed range of values across the micro-partitions1.

References = Snowflake Micro-partitions & Table Clustering

Snowpipe via REST API can reference both named internal stages within Snowflake and external stages, such as Amazon S3, Google Cloud Storage, or Microsoft Azure1. This means that Snowpipe is not limited to only external stages as a source for data loading.

References = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation1