The correct answer is D. DataFrame .
In Snowpark, a DataFrame represents a lazily evaluated relational data set. It provides methods to operate on data, such as selecting columns, filtering rows, joining data sets, grouping data, and applying transformations.
Why D is correct:
A Snowpark DataFrame is the primary abstraction for working with data in Snowpark. It represents data in Snowflake and lets developers build transformations using supported programming languages such as Python, Java, or Scala.
Example concept:
df = session.table( " CUSTOMERS " )
filtered_df = df.filter(df[ " COUNTRY " ] == " USA " )
The DataFrame represents the data set, and operations on it are translated into SQL that runs in Snowflake.
Why the other options are incorrect:
A). A list is a general programming data structure, not the primary Snowpark data set abstraction.
B). A table stores data in Snowflake, but in Snowpark, the object used to represent and operate on a data set programmatically is a DataFrame.
C). An array is a data structure or semi-structured type, not the main Snowpark abstraction for data operations.
Official Snowflake documentation reference:
Snowflake documentation describes Snowpark DataFrames as objects that represent a lazily evaluated relational data set and provide methods for transforming and analyzing data.
Reference: Snowflake Documentation - Snowpark DataFrames; Snowflake Documentation - Snowpark API; SnowPro Core Study Guide - SQL and Snowflake Objects.
==