SOL-C01 Exam Dumps - Snowflake SnowPro Advanced Certification Questions and Answers

Snowflake warehouse sizes followT-shirt sizing, each representing a doubling of compute resources relative to the previous size. Valid Snowflake warehouse sizes includeX-Small,Small,Medium,Large, and up to6X-Large.

X-Smallis the smallest supported warehouse size and is commonly used for light data processing, development tasks, and low-volume operations.

Smalldoubles the compute capacity of X-Small, providing better performance for moderate workloads.

Mediumcontinues scaling upward, offering increased CPU, memory, and parallelism for heavier analytics or transformation workloads.

Tinyis not a Snowflake warehouse size. Snowflake never exposes a warehouse smaller than X-Small, ensuring consistent minimum compute capabilities.

These standardized size tiers allow predictable resource scaling and cost forecasting.

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A single VARIANT value in Snowflake has a maximum size limit of16 MB(uncompressed). This limit applies to semi-structured data stored in VARIANT, such as JSON, XML, Avro, and Parquet objects.

This limit ensures efficient storage, query performance, and micro-partitioning. Exceeding the size results in load or processing errors. For ingestion, when loading large JSON files, it’s recommended to break them into multiple objects or use JSON Lines formatting.

Snowflake has introduced an optional behavior change bundle (2025_03), increasing the limit to128 MBfor accounts that enable it, but the standard default remains 16 MB.

Thus, under default behavior,16MBis the correct maximum value size.

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ThePARSE_JSON()function converts a valid JSON string into aVARIANTvalue. This allows Snowflake to store and query nested, hierarchical data using dot and bracket notation.

Example:

SELECT PARSE_JSON('{"name":"John","age":30}') AS data;

After parsing, fields can be accessed like:

data:name or data['age']

Incorrect options:

TO_JSON()converts VARIANT to a JSON string (opposite direction).

CONVERT_JSONandEXTRACT_JSONare not Snowflake functions.

PARSE_JSON is essential for dynamically loading, transforming, or analyzing JSON content from files, streams, or external applications.

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Snowflake notebooks use the.ipynbfile extension, the standard format for Jupyter notebooks. This format stores executable code, markdown, metadata, and cell outputs in a structured JSON layout. Snowflake adopts this format to ensure compatibility with the broader Python ecosystem, thereby enabling seamless migration between Snowflake and external notebook environments.

The .ipynb structure allows mixed SQL and Python cells, visualizations, Streamlit components, documentation, and stepwise development within Snowsight. It supports reproducibility, collaboration, and integration with Snowpark and Cortex.

Incorrect formats:

.ipnbis a misspelling and invalid.

.sqlis used for SQL scripts only.

.txtcannot represent notebook metadata or cell structure.

Thus, .ipynb is the correct and only supported notebook format.

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