Snowflake SnowPro-Core - SnowPro Core Certification Exam

In Snowflake, Cloud Services costs are incurred when the Cloud Services usage exceeds 10% of the compute usage (measured in credits). Therefore, scenarios A and E would result in Cloud Services charges because the Cloud Services usage is more than 10% of the compute credits used.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake’s official documentation on billing and usage1

The PUT command is used to load data into an internal stage in Snowflake. This command uploads data files from a local file system to a named internal stage, making the data available for subsequent loading into a Snowflake table using the COPY INTO command.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Data Loading

When a virtual warehouse in Snowflake is resized, specifically when it is increased in size, the additional compute resources become immediately available to all running and queued queries. This means that the performance of these queries can improve due to the increased resources. Conversely, when the size of a warehouse is reduced, the compute resources are not removed until they are no longer being used by any current operations1.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Virtual Warehouses2

 Snowflake supports several methods for authenticating users, including federated authentication, key-pair authentication, and OAuth. Federated authentication allows users to authenticate using their organization’s identity provider. Key-pair authentication uses a public-private key pair for secure login, and OAuth is an open standard for access delegation commonly used for token-based authentication. References: Authentication policies | Snowflake Documentation, Authenticating to the server | Snowflake Documentation, External API authentication and secrets | Snowflake Documentation.

Snowflake credits are the unit of measure for the compute resources used in Snowflake. The number of credits consumed depends on the size of the virtual warehouse and the time it is running. Larger warehouses consume more credits per hour than smaller ones, and credits are billed for the time the warehouse is active, regardless of the actual usage within that time.

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

When loading data into Snowflake, it is recommended to:

C. Load files that are approximately 100-250 MB (or larger): This size is optimal for parallel processing and can help to maximize throughput. Smaller files can lead to overhead that outweighs the actual data processing time.

D. Avoid using embedded characters such as commas for numeric data types: Embedded characters can cause issues during data loading as they may be interpreted incorrectly. It’s best to clean the data of such characters to ensure accurate and efficient data loading.

These best practices are designed to optimize the data loading process, ensuring that data is loaded quickly and accurately into Snowflake.

References:

Snowflake Documentation on Data Loading Considerations

[COF-C02] SnowPro Core Certification Exam Study Guide

When the COPY INTO command is executed in Snowflake, it processes all files present in the specified stage that have not been ingested before or marked as already loaded. Since the user did not remove the original 10 files after the first load, running the same COPY INTO command again will result in all 20 files being processed. This means that the data from the original 10 files will be appended to the table again, along with the data from the new 10 files, potentially leading to duplicate records for the original data set.

References:

Snowflake Documentation on Data Loading

SnowPro® Core Certification Study Guide

Secure sharing in Snowflake allows users to share specific objects with other Snowflake accounts without physically copying the data, thus not consuming additional storage. Tables and Secure User Defined Functions (UDFs) are among the objects that can be shared using this feature. Materialized views, sequences, and procedures are not shareable objects in Snowflake.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Secure Data Sharing1

 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 .

 Virtual Warehouses in Snowflake can indeed be resized while they are suspended. Resizing a warehouse involves changing the number of compute resources (servers) allocated to it, which can be done to adjust performance and cost. When a warehouse is suspended, it is not currently running any queries, but its definition and metadata remain intact, allowing for modifications like resizing.

 The correct statement to accommodate the request for a marketing co-worker to change the size of their medium virtual warehouse called mktg__WH is to grant the MODIFY privilege on the warehouse to the ROLE MARKETING. This privilege allows the role to change the warehouse size among other properties.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Access Control Privileges1

When a cloned table is replicated to a secondary database in Snowflake, the following occurs:

C. The physical data is replicated: The actual data of the cloned table is physically replicated to the secondary database. This ensures that the secondary database has its own copy of the data, which can be used for read-only purposes or failover scenarios1.

E. Metadata pointers to cloned tables are replicated: Along with the physical data, the metadata pointers that refer to the cloned tables are also replicated. This metadata includes information about the structure of the table and any associated properties2.

It’s important to note that while the physical data and metadata are replicated, the secondary database is typically read-only and cannot be used for write operations. Additionally, while there may be additional storage costs associated with the secondary account, this is not a direct result of the replication process but rather a consequence of storing additional data.

References:

SnowPro Core Exam Prep — Answers to Snowflake’s LEVEL UP: Backup and Recovery

Snowflake SnowPro Core Certification Exam Questions Set 10

When a CLUSTER BY clause is added to a Snowflake table, it specifies one or more columns to organize the data within the table’s micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.

References:

Snowflake Documentation on Clustering Keys & Clustered Tables1.

Community discussions on how source data’s ordering affects a table with a cluster key