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An analyst needs to reshape a table so that multiple columns representing quarterly sales (Q1_Sales, Q2_Sales, Q3_Sales, Q4_Sales) are converted into rows, with one row per quarter and sales amount. Which SQL construct should the analyst use to achieve this transformation?
UNPIVOT transforms columns into rows, which is exactly what's needed to convert the four quarterly sales columns into a single column of values paired with a quarter identifier column. PIVOT does the opposite, converting rows into columns. FLATTEN is used to expand semi-structured data (like arrays or objects) into rows, not for reshaping relational columns. QUALIFY is used to filter results of window functions, not for reshaping data.
A data integration team needs to load several large CSV files, each around 50 GB, from an internal stage into a table. They want to maximize load throughput by leveraging parallelism across multiple servers in a virtual warehouse. What is the recommended best practice for file sizing before loading?
Snowflake recommends splitting large files into compressed files roughly 100-250 MB in size to enable parallel loading across the nodes of a virtual warehouse. Very large single files limit parallelism because a single file can only be processed by one thread, while file compression reduces network transfer time and storage costs during staging.
A BI team runs the same aggregate query repeatedly throughout the day against a table that has not changed since the last execution. They notice that on the second and subsequent executions, the query returns instantly without consuming any warehouse credits, even after the warehouse was suspended and resumed in between.
This describes the query result cache, which is maintained by the Cloud Services layer independently of the virtual warehouse for 24 hours (extended each time the result is reused, up to 31 days). Because the underlying table data has not changed and the query text and context are identical, Snowflake returns the cached result without using any compute resources, even if the warehouse was suspended and resumed in between. The local disk (warehouse) cache would be lost on suspend, but the result cache persists independently.
A security administrator is configuring a new integration where an external identity provider will handle authentication for all users, and users should be able to sign in via a browser-based redirect without entering Snowflake credentials directly. Which authentication method should be configured?
SAML 2.0-based single sign-on (SSO) allows Snowflake to federate authentication to an external identity provider, redirecting users to the IdP's login page in a browser. Key pair authentication is used for programmatic/service account access, not browser redirects. OAuth is typically used for delegated authorization to third-party tools, and MFA adds a second factor but does not itself federate authentication to an external IdP.
A data engineering team notices that their virtual warehouse automatically suspends after 5 minutes of inactivity and resumes instantly when a new query is submitted. They want to understand which Snowflake architectural layer enables this behavior by separating compute from storage.
Snowflake's multi-cluster shared architecture separates compute (virtual warehouses) from storage. Virtual warehouses are independent compute clusters that can be suspended and resumed on demand without affecting the underlying data stored in the centralized storage layer. The Cloud Services layer coordinates activities like authentication and query parsing but does not perform the actual compute processing that suspends/resumes.
