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Pass Guaranteed Professional SOL-C01 - Latest Snowflake Certified SnowPro Associate - Platform Certification Exam Answers
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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q108-Q113):
NEW QUESTION # 108
You have a Snowflake virtual warehouse named 'REPORTING that is consistently experiencing performance issues during peak hours. You suspect that resource contention is the primary cause. Which of the following actions, when performed together , would be the MOST effective in mitigating these performance issues and ensuring consistent query performance for reporting?
- A. Enable multi-cluster warehouse for with a minimum of 2 clusters and a maximum of 4 clusters. Set the scaling policy to 'Standard'. Increase the size of the warehouse to Large.
- B. Monitor warehouse load using Snowsight and manually increase the warehouse size when performance degrades.
- C. Enable multi-cluster warehouse for 'REPORTING with a minimum of 2 clusters and a maximum of
4 clusters. Set the scaling policy to 'Economy'. - D. Increase the size of from Small to Medium and enable auto-suspend after 5 minutes of inactivity.
- E. Enable auto-suspend after 5 minutes of inactivity and implement query tagging to identify long- running queries.
Answer: A
Explanation:
Option C is the most effective solution. Enabling a multi-cluster warehouse allows Snowflake to automatically scale out by adding more compute resources when the load increases. Setting the scaling policy to 'Standard' prioritizes performance over cost, ensuring that new clusters are started quickly when needed. Increasing the warehouse size to 'Large' provides more resources to each individual cluster. Option A only increases the warehouse size but doesn't address concurrency. Option B uses the 'Economy' scaling policy, which might delay the creation of new clusters, thus not solving the performance issue. Option D only addresses inactivity and identifies long-running queries but doesn't resolve the resource contention. Option E relies on manual intervention, which is not ideal for consistently addressing peak hour performance issues.
NEW QUESTION # 109
You are tasked with creating an external stage pointing to an Azure Blob Storage container. You need to choose the MOST SECURE method for authentication. Which combination of the following options provides the highest level of security for accessing data in the Azure Blob Storage from Snowflake? (Select TWO)
- A. Creating a Managed Identity for Snowflake to access Azure Blob Storage.
- B. Using a Shared Access Signature (SAS) token with limited permissions and expiry.
- C. Using a storage account access key directly in the stage definition.
- D. Using Azure Active Directory (Azure AD) to authenticate Snowflake.
- E. Granting `READ permissions to the `PUBLIC' container in Azure Blob Storage.
Answer: A,D
Explanation:
Options C and E provide the most secure ways to access Azure Blob Storage. Using Azure AD authentication and Managed Identity eliminates the need to store credentials within Snowflake, leveraging Azure's security mechanisms for authentication and authorization. Option A is insecure as it involves storing a long-term secret directly in the stage definition. Option B, while better than Option A, still involves managing and rotating SAS tokens. Option D is extremely insecure, making the data publicly accessible.
NEW QUESTION # 110
You're writing a Snowflake Notebook that needs to dynamically create tables based on a list of table names stored in a Python list called 'table_names'. You want to iterate through this list and execute a CREATE TABLE statement for each table name. However, the names might include spaces and special characters. Which approach or approaches can you use to achieve this goal safely and effectively?
- A. Option C
- B. Option A
- C. Option D
- D. Option B
- E. Option E
Answer: B,C
Explanation:
Options A and D are correct. Option A uses double quotes to safely enclose the table name within the CREATE TABLE statement. This is the standard way to handle identifiers with spaces or special characters in SQL. Option D provides a Snowpark DataFrame-centric approach that automatically handles identifier quoting when creating the table using `saveAsTable' . Option B modifies the table names by replacing spaces. Option C's reliance on shell escaping ('shlex.quote') is not relevant or necessary when executing SQL within a Snowpark session.
Option E is unsafe as it does not handle the case where table names have spaces or other special characters and will result in SQL errors.
NEW QUESTION # 111
Within a Snowflake Notebook, you have defined a Python variable named 'warehouse_size' with a value of 'X-SMALL'. You want to dynamically set the warehouse size for the Snowpark session using this variable. Which of the following code snippets correctly sets the warehouse size using Python variable substitution?
- A.

- B.

- C.

- D.

- E.

Answer: E
Explanation:
Option D, , is the correct and preferred method for changing the active warehouse within a Snowpark session. Snowpark provides a dedicated function for this purpose. Options A, B, C, and E, while they might seem to work using SQL commands, are less efficient and less Snowpark API idiomatic, or does not work as intended. In particular, options A, C, and E incur overhead of executing DDL statements and there are no direct command to execute SQL statement in session in the Snowflake.
NEW QUESTION # 112
You are using the 'SNOWFLAKE.ML.COMPLETE function in Snowflake Cortex to generate creative text formats, specifically poems, based on customer feedback. You have a table
'FEEDBACK' with a 'TEXT column. However, you are consistently encountering the following error: 'SQL compilation error:
Unsupported feature 'External functions". What is the MOST likely cause of this error?
- A. The 'SNOWFLAKE.ML.COMPLETE function requires a minimum Snowflake edition (e.g., Enterprise), and your account is running on a lower edition.
- B. The 'SNOWFLAKE.ML.COMPLETE function is disabled at the account level. Requires enabling it with ALTER ACCOUNT SET ENABLE EXTERNAL FUNCTIONS-TRUE;
- C. The user executing the query lacks the necessary privileges to call external functions.
- D. The virtual warehouse being used does not have sufficient resources allocated to it.
- E. The 'SNOWFLAKE.ML.COMPLETE function is only available in specific regions, and your Snowflake account is not in a supported region.
Answer: B
Explanation:
The error `Unsupported feature 'External functions" strongly indicates that external functions are disabled at the account level. While other options might contribute to issues in other scenarios, this error message directly points to the need to enable external functions using the provided ALTER ACCOUNT statement. Snowflake Cortex ML Complete function is implemented as extemal function internally.
NEW QUESTION # 113
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