While Snowflake primarily deals with structured and semi-structured data, it also has the capability to handle unstructured data. Unstructured data can be stored in Snowflake using variants of SQL data types in tables, which can be permanent tables. These permanent tables, while traditionally used for structured or semi- structured data (like JSON, Avro, or Parquet), can also accommodate unstructured data in the form of binary formats or strings, offering flexibility in data storage and analysis. However, the management and querying of unstructured data in Snowflake may require additional considerations compared to structured data.
References: Snowflake Documentation on Data Types

The correct answer is B. SELECT * FROM table_A TABLESAMPLE (100); .
TABLESAMPLE (100) samples 100 percent of the table, so it returns all rows from table_A.
Why B is correct:
SELECT *
FROM table_A TABLESAMPLE (100);
This requests a 100 percent sample, which is effectively the full table.
Why the other options are incorrect:
A). TABLESAMPLE (0) returns 0 percent of the table, not all rows.
C). SAMPLE (10) returns approximately 10 percent of the rows, not all rows.
D). TABLESAMPLE BERNOULLI (10) samples each row with a 10 percent probability, not all rows.
Official Snowflake documentation reference:
Snowflake documentation explains that SAMPLE / TABLESAMPLE can specify a probability percentage. A value of 100 represents 100 percent of the table.
Reference: Snowflake Documentation - SAMPLE / TABLESAMPLE; SnowPro Core Study Guide - SQL and Snowflake Objects.
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