DYNAMIC PIVOT IMPLEMENTATION USING OBJECT AGGREGATION

    公开(公告)号:US20250094418A1

    公开(公告)日:2025-03-20

    申请号:US18525811

    申请日:2023-11-30

    Applicant: Snowflake Inc.

    Abstract: Examples provide a method for performing dynamic pivot queries employing PANDA-compatible semantics inside a cloud data platform workload. A SQL engine receives a pivot query specifying a pivot column for dynamically determining pivot values in a dynamic pivot operation. The SQL engine identifies, in the pivot query, a keyword or a subquery indicating dynamic determination of the pivot values. Based on identifying the keyword or the subquery indicating the dynamic determination of the pivot values, the SQL engine determines distinct pivot values for the pivot column by evaluating the keyword or executing the subquery. The evaluating of the keyword includes issuing a query to a data store to obtain the distinct pivot values for the pivot column. The SQL engine performs the dynamic pivot operation using the distinct pivot values for the pivot column.

    Row-order dependent dataframe workloads

    公开(公告)号:US12216648B1

    公开(公告)日:2025-02-04

    申请号:US18393324

    申请日:2023-12-21

    Applicant: Snowflake Inc.

    Abstract: A method includes receiving instructions to perform order-dependent DataFrame operation on data. In response to receiving the instructions, the framework analyzes the instructions to identify the order-dependent DataFrame operation, and generates an executable query corresponding to the identified order-dependent DataFrame operation. The framework executes the generated executable query on the data stored in the first database in the cloud data platform, creates a row position column that generates for each row a unique integer identifier, reproducible across multiple sessions and/or queries for the same underlying data to make the data accessible via positional indexing, and assigns each row of the first database a unique row index value based on the row position column and the row position column order. The framework orders a result from performing the order-dependent DataFrame operation based on the unique row index value assigned to each row of the first database, and returns the ordered result to the user.

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