Patent ID: 11880364
Assignee: SNOWFLAKE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A method comprising:
receiving, by one or more processors, a query directed to a set of source tables, each source table organized into a set of micro-partitions;
determining a set of metadata, the set of metadata comprising table metadata, query metadata, and historical data related to the query;
predicting, using a machine learning model, an indicator of an amount of computing resources for executing the query by applying the set of metadata comprising the table metadata, the query metadata, and the historical data related to the query as input to the machine learning model, the machine learning model trained to generate a prediction of the amount of computing resources for queries based on inputted table metadata, query metadata, and historical data related to queries, the amount of computing resources comprising a number of virtual warehouses predicted to execute the query, the predicting, using the machine learning model, further comprising: generating a prediction for allocation of a number of additional virtual warehouses for executing the query by:
identifying a parallelization limit for the received query, the parallelization limit corresponding to a number of virtual warehouses at which an execution time of the query no longer decreases as a result of increasing a number of additional virtual warehouses; and
determining that the predicted amount of computing resources for executing the query corresponds to the parallelization limit;

generating a query plan for executing the query based at least in part on the predicted indicator of the amount of computing resources; and
executing the query based at least in part on the query plan.