SNOWPRO-CORE practice question 34 of 35

What are benefits of using Snowpark with Snowflake? (Select TWO).

Domain Snowflake Overview and Architecture

Answer options

A: Snowpark uses a Spark engine to generate optimized SQL query plans.

B: Snowpark automatically sets up Spark within Snowflake virtual warehouses.

C: Snowpark does not require that a separate cluster be running outside of Snowflake. Correct answer

D: Snowpark allows users to run existing Spark code on virtual warehouses without the need to reconfigure the code. Correct answer

E: Snowpark executes as much work as possible in the source databases for all operations including User-Defined Functions (UDFs).

Correct Answer:

C. Snowpark does not require that a separate cluster be running outside of Snowflake.; D. Snowpark allows users to run existing Spark code on virtual warehouses without the need to reconfigure the code.

Explanation

Snowpark is a developer framework for Snowflake that allows data engineers and developers to write code in languages like Python, Java, and Scala to query and process data. A primary benefit is that all operations are executed lazily on the Snowflake platform, leveraging its elastic compute resources (virtual warehouses). This eliminates the need to manage and maintain separate compute clusters, such as Spark, simplifying the data architecture. Furthermore, the Snowpark DataFrame API is intentionally designed to be familiar to developers who have used Apache Spark, which allows them to leverage existing skills and code patterns with minimal modifications.

Why Incorrect

A. Snowpark does not use a Spark engine. It translates DataFrame operations into SQL that runs on Snowflake’s native query processing engine.
B. Snowpark utilizes Snowflake's virtual warehouses for compute; it does not set up or manage a Spark environment within them.
E. Snowpark executes operations within the Snowflake data cloud platform, not by pushing computation back to external source databases.

References

1. Snowflake Documentation - Introduction to Snowpark: "With Snowpark, you can execute this logic where your data resides, using Snowflake’s virtual warehouses for compute. This means you don’t need to create and manage a separate cluster for the client application." This directly supports option C.

2. Snowflake Documentation - Snowpark Developer Guide for Python: "The Snowpark API provides programming language constructs for building SQL statements... The API is designed to provide an experience that is familiar to developers who have used DataFrames in other frameworks (e.g. Apache Spark, pandas)." This supports the principle behind option D.

3. Snowflake Documentation - How Snowpark Code is Executed: "The Snowpark library works by translating this code [DataFrame operations] into SQL statements that are executed on the server." This refutes options A and B, which incorrectly claim Snowpark uses a Spark engine.

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