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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You have a Pandas DataFrame 'products df containing product information that you want to upload to a Snowflake table named 'PRODUCTS' within the schema 'SALES'. The table might or might not exist. If it doesn't, you want to create it automatically. The products df DataFrame has a column 'product_name' that contains Unicode characters. Furthermore, you need to specify the column types directly as part of the operation. Which of the following options provides the most appropriate approach to achieve this with Snowpark?

A)

B)

C)

D)

E)

2. Consider the following Snowpark Python code snippet designed to calculate a custom metric on financial data, using a vectorized UDF for performance. Identify potential performance bottlenecks and recommend optimization strategies.

Which of the following actions (may be more than one) would MOST likely improve the performance of this Snowpark application?

A) Ensure that the 'financial_data' table is clustered by 'ticker_symbor to optimize the 'groupBy' operation.
B) Change 'FloatType' to 'DoubleType' as it provides more precision.
C) Repartition the 'data' DataFrame by 'ticker_symbol' before the 'groupBy' operation using to improve data locality.
D) Use to explicitly declare the Pandas dependency.
E) Use before writing to the 'metric_table' , especially if the table is subsequently used downstream.

3. You're tasked with creating a Snowpark UDF to calculate the Haversine distance between two sets of latitude and longitude coordinates (point A and point B). Which of the following statements about deploying and using this UDF is/are TRUE?

A) The UDF can be written in Python, Java, or Scala. Using a Java UDF will likely offer best performance, especially when dealing with very large datasets. You'll need to stage the compiled JAR file on an internal stage that Snowpark can access.
B) The UDF can only be written in Python and must be deployed as an inline UDF within the Snowpark session.
C) The UDF can only be called directly from within the Snowpark session and cannot be used in standard Snowflake SQL queries.
D) When defining the UDF with input types, the Python types must exactly match the corresponding Snowflake data types.
E) The UDF, once defined, can be used inside of any DataFrame operation like 'select', 'filter' , and 'withColumn'

4. You are developing a Snowpark application that processes real-time streaming data'. The application needs to perform a complex calculation for each incoming event. To improve performance, you decide to leverage asynchronous execution and User-Defined Functions (UDFs). However, you are encountering issues with the order of results and ensuring that the processing order matches the arrival order of the events. Which of the following strategies MOST effectively addresses the challenge of maintaining processing order while leveraging asynchronous execution and UDFs in Snowpark?

A) Use synchronous UDF calls with a large Snowflake warehouse to minimize processing time and guarantee order.
B) Employ asynchronous UDF calls with 'block-False' and rely on Snowflake's internal optimization to maintain the processing order.
C) Abandon the use of UDFs altogether and reimplement the complex calculation using only built-in Snowpark DataFrame transformations to ensure order.
D) Use synchronous UDF calls with a small Snowflake warehouse to introduce artificial delays and ensure order.
E) Utilize asynchronous UDF calls with 'block-False' and implement a custom ordering mechanism based on a timestamp or sequence number associated with each event. Store the results in a temporary table and sort them based on the timestamp before further processing.

5. When using key pair authentication with Snowpark, what security best practices should you implement to protect your private key?
(Select all that apply)

A) Encrypt the private key at rest.
B) Grant broad access to the environment variable containing the private key to all developers.
C) Store the private key directly in the Snowpark code repository.
D) Regularly rotate the key pair.
E) Store the private key in an environment variable or a secure secret management system (e.g., HashiCorp Vault, AWS Secrets Manager, Azure Key Vault).

Solutions: