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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You have a Snowflake table 'PRODUCT CATALOG' with columns 'PRODUCT ID, 'PRODUCT NAME, and 'CATEGORY ID. You also have a table 'CATEGORY' with 'CATEGORY ID' and 'CATEGORY NAME. You need to create a Snowpark DataFrame that joins these two tables and includes only 'PRODUCT NAME and 'CATEGORY NAME. Assume a Snowpark Session object named 'session' is available. Which code snippet demonstrates creating the DataFrame using Snowpark's join functionality and column selection while using the 'table' method?

A)

B)

C)

D)

E)

2. You have a Snowpark DataFrame named 'sales df containing sales data for different products. The DataFrame includes columns product_id' (INTEGER), 'sale_date' (DATE), 'quantity' (INTEGER), and 'price' (FLOAT). You need to calculate the total revenue for each product on a monthly basis and store the result in a new DataFrame named Which of the following Snowpark code snippets will correctly achieve this, while maximizing performance and minimizing data shuffling?

A) ...python from snowflake.snowpark.functions import date_format, sum monthly_revenue_df = sales_df.withColumn('sale_month', date_format(sales_df['sale_date'], 'yyyy-MM')).groupBy('product_id', 'sale_month').agg(sum(sales_df['quantity'] sales_df['price']).alias('total_revenue'))
B) ...python from snowflake.snowpark.functions import monthname, sum monthly_revenue_df = sales_df.groupBy('product_id', monthname('sale_date').alias('sale_month')).agg(sum(sales_dfl'quantity'] sales_dfl'price']).alias('total_revenue'))
C) ...python from snowflake.snowpark.functions import date_part, sum monthly_revenue_df = sales_df.groupBy('product_id', date_part('month', 'sale_date').alias('sale_month')).agg(sum(sales_df['quantity'] sales_df['price']).alias('total_revenue'))
D) ...python from snowflake.snowpark.functions import to_date, date_trunc, sum monthly_revenue_df = sales_df.withColumn('sale_month', date_trunc('MM', sales_df['sale_date'])).groupBy('product_id', 'sale_month').agg(sum(sales_df['quantity'] sales_df['price']).alias('total_revenue'))
E) ...python from snowflake.snowpark.functions import month, sum monthly_revenue_df = sales_df.groupBy('product_id', month('sale_date').alias('sale_month')).agg(sum(sales_df['quantity'l sales_df['price']).alias('total_revenue'))

3. You are tasked with setting up secure authentication for your Snowpark application. You want to use key pair authentication for a service user. Which of the following steps are necessary and in the correct order?

A) 1. Generate an RSA key pair (private and public key). 2. Store the public key securely on the client machine. 3. Provide the path to the public key file in the Snowpark session configuration. 4. Associate the private key with the Snowflake user using the SALTER USER command.
B) 1. Generate an RSA key pair (private and public key). 2. Store the private key in a database table. 3. Use database credentials in the Snowpark session configuration. 4. Associate the public key with the Snowflake user using the 'ALTER USER command.
C) 1. Generate an RSA key pair (private and public key). 2. Store the private key securely on the client machine. 3. Provide the path to the private key file and passphrase (if any) in the Snowpark session configuration. 4. Associate the public key with the Snowflake user using the 'ALTER USER command.
D) 1. Generate an RSA key pair (private and public key). 2. Store the private key securely on the client machine. 3. Associate the private key with the Snowflake user using the SALTER USER command. 4. Provide the public key in the Snowpark session configuration.
E) 1. Generate an RSA key pair (private and public key). 2. Store the private key securely on the client machine. 3. Provide the path to the private key file in the

4. You are setting up a development environment for Snowpark using Anaconda and encounter the following error: 'ModuleNotFoundError: No module named 'snowflake.snowpark". You have already installed the package using pip. What is the MOST likely cause of this error and how do you resolve it?

A) The Snowflake account identifier is not properly configured in your environment variables. Verify that 'SNOWFLAKE ACCOUNT is correctly set.
B) The 'snowflake-snowpark-python' package was installed in a different Anaconda environment than the one you are currently using. Ensure you are in the correct environment when running your Snowpark code.
C) The Snowflake driver is not installed. Install the Snowflake driver using 'pip install snowflake-connector-python'
D) The 'snowflake-snowpark-python' package is not compatible with the version of Python installed in your Anaconda environment. Upgrade Python to the latest version.
E) The Anaconda environment is not activated. Activate the environment using 'conda activate

5. You are tasked with creating a Snowpark DataFrame from a Python list of tuples. Each tuple represents a customer record with the following structure: '(customer_id, signup_date, The 'customer _ id' should be an integer, 'signup_date' should be a date, and should be a decimal. You want to define the schema explicitly for type safety and performance. Which of the following code snippets correctly defines the schema and creates the Snowpark DataFrame?

A)

B)

C)

D)

E)

Solutions: