Snowflake SPS-C01

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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You are optimizing a Snowpark Python application that performs complex data transformations on a large dataset. You notice significant performance bottlenecks. Which of the following optimization techniques would be MOST effective in leveraging the Snowpark architecture to improve performance?

A) Exploiting lazy evaluation by chaining transformations together and avoiding unnecessary 'collect()' or 'toPandas()' calls.
B) Using 'session.sql()' whenever possible instead of Snowpark DataFrame operations.
C) Manually partitioning the DataFrame into smaller chunks before applying transformations.
D) Using User-Defined Functions (UDFs) written in Python for all transformations, ensuring they are vectorized where possible, instead of native Snowpark functions.
E) Converting all Snowpark DataFrames to Pandas DataFrames before performing any transformations.

2. You have a Snowpark DataFrame containing product information, and you want to persist it into a Snowflake table named PRODUCTS. You need to handle the following scenarios: 1. If the table 'PRODUCTS does not exist, create it. 2. If the table PRODUCTS' exists, append the data from 'df_products' to it. Which of the following methods can achieve this?

A)

B)

C)

D)

E)

3. You are using Snowpark Python to create a DataFrame from an existing Snowflake table "SALES DATA'. You want to apply a user- defined function (UDF) to each row of the DataFrame to calculate a custom sales metric. The UDF requires access to the 'session' object. Which of the following approaches is correct for defining and applying the UDF in Snowpark?

A)

B)

C)

D)

E)

4. You have a Snowpark Python stored procedure 'process_data' that takes a Snowpark DataFrame as input, performs several data transformations using functions defined in a separate Python module 'data utils.py', and returns a transformed DataFrame. The 'data utils.py' file is located in your local directory. You want to register this stored procedure so that it can be called from Snowflake. Which of the following code snippets demonstrate(s) the correct way to register the stored procedure, ensuring that the 'data utils.py' module is available within the Snowpark environment? (Select TWO)

A)

B)

C)

D)

E)

5. You are using Snowpark Python to build a machine learning pipeline. One step in the pipeline involves feature engineering using a large dataset. This feature engineering step is computationally expensive and involves several transformations. You want to optimize the performance of this step by caching intermediate results. Given the following code snippet, which of the following strategies would be MOST effective for optimizing the performance, considering the use of

A) Cache the initial raw data DataFrame before applying any transformations.
B) Cache each intermediate DataFrame after each individual transformation step, even if the DataFrame is only used once.
C) Avoid using altogether because it can introduce overhead and is not always beneficial.
D) Identify DataFrames that are reused multiple times and cache them using after the transformations that generate them.
E) Cache the final DataFrame only after all feature engineering steps are completed.

Solutions: