Snowflake SOL-C01 Actual Questions

ADatabaseis the highest logical container for schemas and their objects in Snowflake.

Hierarchy:

Account → Database → Schema → Tables, Views, Stages, etc.

Schemas organize objects within a database; tables and views do not contain objects.

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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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The Snowsight Monitoring tab provides a centralized view of virtual warehouse usage metrics, enabling administrators and developers to evaluate how compute resources are being consumed. This includes critical insights such as credit usage, query load, concurrency levels, average queue times, execution durations, and auto-scaling activity (for multi-cluster warehouses). These metrics help determine whether a warehouse is correctly sized, whether concurrency issues are occurring, or whether workloads require scaling up or adding clusters.

Query history is available in a different section—“Activity → Query History”—not under Monitoring. Time Travel snapshots are not visualized within Monitoring; Time Travel is controlled via retention parameters and accessed with SQL (AT/BEFORE clauses). Schema change history is also not part of Monitoring and instead is discoverable through ACCOUNT_USAGE or specific metadata views.

The Monitoring tab exists specifically to help evaluate warehouse performance and resource consumption, enabling optimization of compute spending and better workload management.

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